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Pulp and paper mill effluent (PPME), a rich cellulosic material, was found to have great potential for biohydrogen production through a photofermentation process. However, pretreatments were needed for degrading the complex structure of PPME before biohydrogen production. The aim of this study was to gain further insight into the effect of an ultrasonication process on PPME as a pretreatment method and on photofermentative biohydrogen production using Rhodobacter sphaeroides NCIMB. The ultrasonication amplitudes and times were varied between 30–90% and 15–60 min, respectively, and no dilution or nutrient supplementation was introduced during the biohydrogen production process. A higher biohydrogen yield, rate, light efficiency and COD removal efficiency were attained in conditions using ultrasonicated PPME. Among these different pretreatment conditions, PPME with ultrasonication pretreatment employing an amplitude of 60% and time of 45 min (A60:T45) gave the highest yield and rate of 5.77 mL H 2 /mL medium and 0.077 mL H 2 /mL h, respectively, while the raw PPME without ultrasonication showed a significantly lower yield and rate of 1.10 mL H 2 /mL medium and 0.015 mL H 2 /mL h, respectively. The results of this study demonstrated the potential of using ultrasonication as a pretreatment for PPME because the yield and rate of biohydrogen production were highly enhanced compared to the raw PPME. Economic analysis was also performed in this study, and in comparison with raw PPME, the highest net saving was $0.2132 for A60:T45. [ABSTRACT FROM AUTHOR]

[Display omitted] • Various carbon nanotube-based devices are developed for solar energy utilization. • The water evaporation system can generate freshwater (1.28 kg m−2h−1). • The solar-thermoelectric system can output a voltage and charge a cellphone. • The supercapacitor performs an areal specific capacitance of 19.6 mF cm−2. • The hybrid energy system can produce freshwater, generate and store electric power. Nowadays, multi-functional systems driven by solar energy have been explored to alleviate the crisis of energy and freshwater scarcity. However, it remains a great challenge to integrate multi-functions into one hybrid system with a monolithic material, which can harvest, convert and store solar energy synergistically. Here, we firstly propose a multi-functional carbon nanotube paper, which starts from a material level to solve these problems. The carbon nanotube paper is fabricated by vacuum filtration. It exhibits high efficiency of solar-thermal conversion. Secondly, three types of energy conversion/storage systems (e.g., solar-thermal evaporation system, solar-thermoelectric generation system, and supercapacitor) are constructed based on the carbon nanotube paper, which extend the research to a device level. The solar-thermal evaporation system shows an evaporation rate of 1.28 kg m-2h−1 under simulated sunlight irradiation of 1 kW m−2. The solar-thermoelectric generation system demonstrates a stable electric power generation with an output voltage of 100 mV under light irradiation of 1 kW m−2. The supercapacitors perform the energy storage function with an areal specific capacitance of 19.6 mF cm−2. These devices and systems can be used in freshwater generation (0.84 kg m-2h−1, sunlight irradiation of 1 kW m−2), water purification/desalination (inorganic ions rejection larger than 99.9%) and portable solar charging system (maximum output voltage of 5 V). Finally, a hybrid energy system is innovatively proposed from the system level to simultaneously produce freshwater, generate and store electric power. Through the synergetic coupling of solar conversion and storage technologies, the hybrid energy system can supply sustainable freshwater and electricity for remote areas in daily life, highlighting the superiority of multi-energy (thermal energy, electrical energy, and electrochemical energy) complementary. [ABSTRACT FROM AUTHOR]

[Display omitted] • Novel method to estimate total technical potential for improving energy efficiency. • Bottom-up sector energy model used to characterize energy demands and opportunities. • Technology-explicit analysis framework used to estimate integrated energy savings. • Application to Canada's pulp & paper sector indicates major savings are possible. • Technical potential to reduce natural gas use by 95% and net electricity by 54% Industrial energy efficiency has long been recognized as a critical tool for energy management and emissions reduction and is increasingly considered to be an energy resource in its own right. However, the complexity of most industrial sectors creates barriers for modellers, companies, and policymakers in understanding and achieving the overall potential for efficiency-driven energy savings. To address this gap, we have developed a novel method that combines disaggregated bottom-up sector energy modelling with analysis of a comprehensive set of technology-explicit energy efficiency measures. This approach overcomes the deficiencies of top-down analyses and better represents the complexities of multi-measure efficiency investments compared to piecewise studies of individual measures. In this study, we demonstrated application of our method to the case of the Canadian pulp and paper sector. Our analysis shows that the sector can reduce its natural gas and electricity use by 95% and 41%, respectively, by adopting economical efficiency measures. This equates to 71 PJ of natural gas and 44 PJ of electricity saved annually and would result in cost savings of $81 per tonne of output sector-wide. Notably, we find that efficiency and fuel switching have the technical potential to reduce natural gas consumption by 98% across the sector. Taken together, the results provide quantitative evidence that energy efficiency is an underestimated resource for cost-effective energy savings in the Canadian pulp and paper sector. Our analysis framework can be applied to any industrial sector in any region to provide insights regarding energy conservation strategies and policy design. [ABSTRACT FROM AUTHOR]

• Operation and construction of an energy hub based upon the flexibility. • The flexibility index covers maximum system capacity and system response time. • Effect of energy hub flexibility on battery aging. • Consumer participation rate prediction in demand response programs by deep learning. Energy hubs (EHs), hold promise for improving energy efficiency and mitigating carbon emissions. The increasing renewable energy resources, with its inherent uncertainty and variability in power generation, presents challenges for power systems, thereby highlighting the importance of flexibility. This paper proposes a multi-objective framework for enhancing EH flexibility. It is expected that flexibility can induce battery aging which is demonstrated in this paper. The framework leverages a novel flexibility index encompassing both capacity and response time to optimize EH configuration and operation. In this paper employs a data-driven approach to analyze battery degradation under varying flexibility demands. This analysis informs the acceleration of aging associated with increased flexibility. Given the critical role of flexibility, this paper investigates the tripartite relationship between flexibility, time, and battery lifespan. Additionally, considering Demand Response Programs as crucial flexibility resources, the proposed framework utilizes deep learning to forecast consumer participation rates. Utilizing historical data on temperature, price, and participation, various deep learning models are compared. Results indicate a 30% reduction in operating costs associated with a 12% increase in flexibility. However, this flexibility comes at the cost of increased manufacturing expenses and a 20% decrease in battery lifespan due to operational fluctuations. [ABSTRACT FROM AUTHOR]

• A novel wind power prediction method based on influencing factors is proposed. • A multivariate model based on TCN-ReOSELM is proposed for the first time. • PC technology is utilized to process the input data of the model. • An improved AHA algorithm is introduced to optimize the TCN-ReOSELM model. • The superiority of the proposed model is verified by ten benchmark models. Highly accurate wind power prediction is important for the operation and management of wind farms, energy utilization and power supply. In recent years, in order to further improve prediction accuracy, some researchers have considered utilizing factors such as wind speed and wind direction to establish prediction models. However, this often results in input redundancy due to a lack of technical means. In this paper, a multivariate prediction model for wind power based on variational mode decomposition (VMD), fuzzy entropy (FE), partial auto-correlation function and cross-correlation function (PACF&CCF, abbreviated as PC), improved artificial hummingbird algorithm (IAHA), temporal convolutional network (TCN), and regularized online sequential extreme learning machine (ReOSELM) is proposed. To address the nonlinearity and non-stationarity of the original wind power time series and decrease computational costs, the VMD combined with FE data preprocessing technique is employed. Considering the information redundancy in the multivariate data, the PC technique is utilized to conduct correlation analysis on the input data and select highly correlated features as inputs. When the input is multivariate and high-dimensional, the ReOSELM model struggles to achieve satisfactory prediction performance. Therefore, a new model based on TCN-ReOSELM is constructed. Additionally, to overcome the drawbacks of manual parameter adjustment, an IAHA algorithm is proposed, which integrates Latin hypercube sampling and chaotic local search strategies, to optimize the crucial parameters of TCN-ReOSELM. The experimental results demonstrate that the multivariate method proposed in this paper reduces the RMSE by 31% compared to the univariate method. Specifically, the proposed VMD-FE-PC-TCN-ReOSELM model reduces the RMSE, MAE, and SMAPE by 60–64%, 55–58%, and 10–36%, respectively, compared to the PC-TCN-ReOSELM model. [ABSTRACT FROM AUTHOR]

• Proposed a novel advanced solar-driven combined heat and power system. • Constructed the overall heat current model and exergy analysis expression. • Analyzed the exergy loss and efficiencies of each component and the system. • Analyzed the influences of various parameters on the system exergy efficiency. Conducting research on advanced cycle of distributed energy system and improving energy utilization efficiency is an important approach to promote the development of distributed energy systems. The paper proposed a novel solar-driven supercritical carbon dioxide-heat pump cogeneration system based on solar power tower system and performed the overall modeling of the system using the heat current method. The overall exergy loss calculation model of the system was established by applying the exergy analysis method incorporating the standard thermal resistance-based entropy generation rate expression. The calculation results present that under rated condition, irreversible loss mainly occurs in the solar energy conversion part, accounting for 73.83 %, and the system exergy efficiency is 34.69 %. Besides, the paper investigated the steady state performance of the system under different working conditions and the influence of the turbine inlet temperature and the intermediate pressure on the system performance. When the direct normal irradiance increases, the proportion of exergy loss in solar energy conversion part increases by 62.13 %, while the change of system exergy efficiency depends on the operating state of the system. The optimum intermediate pressure is 11.72 kPa, when the net power output and the exergy efficiency of the whole system reaches the maximum. Finally, the proposed system contributes to the improvement of cascade utilization of energy, and the modeling method is effective for solar-driven supercritical carbon dioxide cogeneration systems. [ABSTRACT FROM AUTHOR]

• The thermal, rheological, and optical properties of ferrofluids and how they change with magnetic fields were discussed. • The utilization of ferrofluids in solar energy systems was detailed in a state-of-the-art analysis. • The recommendations aimed to optimize the use of ferrofluids and magnetic fields in energy systems to enhance performance. Solar energy technologies play a crucial role in the transition to sustainable energy sources; however, there is an ongoing challenge in optimizing their efficiency and performance. This review paper thoroughly exposes the potential for enhancing solar systems by incorporating ferrofluids and utilizing magnetic fields. It provides a comprehensive examination of the rheological, thermal, and optical properties of ferrofluids, as well as their behavior when exposed to magnetic fields. The paper emphasizes the ability of ferrofluids to improve heat transfer efficiency, adapt to changing conditions, and enable precise control in the conversion of solar energy. Furthermore, the review addresses the obstacles and limitations associated with integrating ferrofluids into solar technologies, proposing potential solutions and outlining future research directions. [ABSTRACT FROM AUTHOR]

In their quest to enhance energy efficiency and carbon footprint management, many enterprises are turning their attention towards optimizing their facilities through amplified data monitoring and innovative control methods. In this context, this research highlights a practical solution in a commercial building located in the United States. It explains the creation, implementation, and costs of a universally applicable model predictive control (MPC) framework for the building's heating, ventilation, and air conditioning (HVAC) system. The paper elaborates on both the hardware and software used to accumulate pertinent data and the formulation of the MPC system. This approach leverages cloud-based microservices and can be seamlessly integrated into current building management systems. In this regard, this paper presents three innovative strategies: Proportional–integral (PI)+Preheating, MPC, and occupancy-based control. These scenarios were designed to improve energy efficiency and thermal comfort significantly by reducing temperature fluctuations and adhering more closely to the setpoint temperature. The implementation of these strategies resulted in substantial energy savings, with reductions in energy consumption of 12.83%, 19.21%, and 14.98%, respectively. • A novel cloud-based MPC scheme is proposed for controlling the educational building HVAC system. • Real-world case installation details are provided with a focus on cost and sensor information. • A comprehensive discussion on thermal modeling, occupants' comfort, and control performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • Assessed concepts combine biogas- and electricity-based methanol production • Adding electricity-based hydrogen increases methanol production by 28 to 67% • Tri-reforming enables high biogas conversion for a total carbon utilization of 97% • Bi-reforming exceeds energy efficiency of tri-reforming by 5%pt. in overall concept • Methanol production costs are estimated at 1,300 € 2022 /t The limited potential of sustainably available biomass requires efficient conversion to defossilize future demands of carbon-based chemicals and energy carriers. Therefore, integrating electricity-derived hydrogen into biomass-based production concepts appears promising, maximizing carbon utilization while minimizing biomass requirement. However, specific process concepts and analyses are still lacking to quantify the potential technical and economic benefits of such hybrid production processes. Thus, this research paper investigates this novel approach for decentralized methanol production from biogas within a techno-economic analysis, considering two production configurations. One configuration (BiRef) utilizes electrically heated bi-reforming for syngas generation, while the other configuration (TriRef) uses autothermal tri-reforming. Based on stationary process simulations, in-depth knowledge about process behavior is gained, efficiencies and costs are determined, and influencing factors are assessed. Within the reference case, the BiRef configuration achieves a carbon efficiency of 93 %, while the TriRef configuration reaches 97 % due to its enhanced methane conversion. Energy efficiency is 5 %pt. higher within the BiRef configuration (74 %), primarily due to the lower hydrogen demand. Carbon and energy efficiency are crucially affected by reforming temperature and inert gas fraction in the syngas. The economic analysis shows methanol production costs of ca. 1,300 € 2022 /t for both configurations. Variations in economic parameters emphasize advantages for the TriRef configuration when low hydrogen costs (<6 € 2022 /kg) are achievable. The comparison with purely biogas-based methanol production shows that hydrogen addition increases production capacity by up to 67 %. Cost advantages result against purely electricity-based production, while cost parity is achieved with purely biogas-based production. This paper demonstrates the potential of hybrid methanol production for efficient biogas utilization and highlights decisive parameters influencing technical and economic efficiency. [ABSTRACT FROM AUTHOR]

[Display omitted] • Sorting strategies based on source, physical and chemical properties were compared. • The gasification efficiency of sorted RMSW was 40.89% higher than that of unsorted. • The yield of syngas can be increased by 37.14% after waste sorting. • The emission of CO 2 can be reduced by 81 t·per year after waste sorting. • Elemental composition based sorting method benefited to efficient gasification. Gasification is a promising way to convert residual municipal solid waste (RMSW) to high-valued syngas. Waste sorting is helpful to alleviate the heterogeneity problem of waste on gasification. This paper aimed to search for an optimal sorting strategy and evaluate the influence of waste sorting on downstream gasification. A sorting strategy based on elemental composition was proposed and compared with common source and density based strategies. The results validated the enhancement of waste sorting on RMSW gasification, where the elemental composition based strategy showed optimal gasification. The yield of syngas, cold gas efficiency, the lower heating value of syngas and H 2 /CO were increased by 37.14 %, 38.95 %, 2.18 % and 8.81 %, respectively. It also showed a good effect on the improvement of air gasification compared with the literature, especially for H 2 /CO. This paper also discussed the economic and environmental potential of the elemental composition based sorting method. The waste sorting can help increase 29,250 RMB/year and reduce CO 2 emission by 81 t/year. This method has potential for industrial application. It is suggested that further fast elemental composition characterization technologies and intelligent sorting equipment can be developed. Limitations and future perspectives were discussed from gasification simulation models, more energy utilization technologies, the underlying logic of waste sorting and sustainability evaluation. It is hoped that this work can provide insightful fundamentals to their applications in RMSW sorting, thus benefiting resource recovery and circular economy. [ABSTRACT FROM AUTHOR]

The objective of this paper is to implement an automated system for the control of all energy resources and devices within smart buildings. The paper develops a Two-Layer Electric Water Heater Management (TL-EWHM) system tailored for efficient power distribution within a smart microgrid connected to both a photovoltaic (PV) system and the Electric Grid (EG). The TL-EWHM consists of two distinct layers: the Offline Optimization Layer (OFF-OL) and the Online Optimization Layer (ON-OL). Within the OFF-OL, an optimization algorithm known as Particle Swarm Optimization (PSO) is employed to determine the optimal power settings for Electric Water Heaters (EWH) based on forecasts of several factors including PV generation, ambient temperature (A T), water demand (W D), and the consumption of fixed appliances (F A C) for the upcoming 24 h. These parameters are forecasted using a novel prediction algorithm referred to as regressor stacking, which is developed based on actual data. Within the ON-OL, real-time data is effectively utilized, and an Extremum-Seeking (ES) Controller is employed to continuously adapt the EWH power settings in response to uncertainties in the predictions. Furthermore, a strategic approach is being devised to generate the water temperature setpoints (W T S) by considering dynamic data factors like P V power, total energy consumption (P L), and the water demand profile to ensure that user comfort is maintained. A comprehensive comparative analysis is carried out to evaluate the effectiveness of our strategy approach. This strategy is characterized by the inclusion of a Water Temperature Setpoint Generator (W T S G) and the integration of a two-layer optimization methodology that combines the OFF-OL and the ON-OL. In this comparative study, our strategy is assessed in comparison to other conventional approaches, with the objective of highlighting the distinctive advantages of our method in terms of cost reduction and the enhancement of user comfort. On the one hand, comparisons are made with strategies that give priority to offline optimization. On the other hand, the strategy that maintains a constant water temperature setpoint throughout the day. The results of this paper establish the effectiveness of the proposed strategy. In particular, the energy cost savings associated with the two-layer optimization approach is 13.73%. Even more noteworthy is the significant reduction in energy costs, which reaches an impressive 18.63% when the variation of water temperature setpoints is taken into account. These results underscore the significant benefits of using a two-stage optimization strategy over relying solely on offline optimization. They also underscore the value of incorporating a WTSG as opposed to maintaining WTSC. • Real-time optimization of a electric water heater (EWH) under model uncertainties. • The two-layer management approach enhances robustness to operating conditions. • This paper proposes a new strategy for variable water temperature setpoints. • The objective is to minimize energy costs while maximizing occupant comfort. • MLP stacking reduces overfitting, boosts flexibility by diverse dataset training. [ABSTRACT FROM AUTHOR]

• A new DPV-5G BS-ES communication and power mutual coupling system is developed. • A BSSCP model is proposed to minimize the number of 5G base station deployments. • The ISOM model is used to optimize the microgrid connection lines in 3D space. • Economically optimal simulation experiments are conducted for different PV systems. The emergence of ultra-dense 5G networks and a large number of connected devices will bring with them significant increases in energy consumption, operating costs, and CO 2 emissions. At the same time, the deployment of distributed photovoltaic (DPV) in megacities plays an important role in promoting the integration of "building-photovoltaic", adjusting the city's clean energy supply system, and building a green, and low-carbon smart city. The development of a new "DPV-5G Base Station-Energy Storage (DPV-5G BS-ES)" coupled DC microgrid system and its pre-deployment investment costs are fundamental factors to be considered when the problem of large-scale DPV and BS deployment in cities has to be addressed. There are almost no published papers on this issue in the literature, which only consider the problem of maximizing the deployment of 5G BS service coverage or only perform optimization analyses for the performance of microgrid systems without considering the economic optimality and low-carbon green issues in the construction of urban utilities. In order to solve the problem of 5G BS deployment and economic optimization of topology in the "DPV-5G BS-ES" coupled DC microgrid system, a novel deployment strategy is proposed in this paper. The strategy is divided into: (a) The Geographic Information System (GIS) for extracting and analyzing 3D data from all buildings in the area. (b) A GIS-based formulation of a mixed integer quadratic constrained planning model (BSSCP) under discrete fixed radius coverage constraints is used to delineate building clusters within the area and determine the optimal deployment location of 5G BS under each sub-cluster. (c) An Improved Self-Organizing Mapping (ISOM) model combines GIS and microgrid performance parameters to address the economically optimal connection of grid lines for DPV in 3D space. (d) Simulation experiments were conducted for the power output and profitability of eight different PV panels and tracking systems to calculate the economically optimal type of DPV generation hardware. The experimental results show that the BSSCP model proposed in this study reduced the 5G BS deployment cost input by up to 35.8974 % compared to that of the control experimental model. Meanwhile, the ISOM model obtained an average reduction of 52.3741 % in the cost of connecting cables for the optimized 25 DPV planning and DC microgrid topology. [ABSTRACT FROM AUTHOR]

• Linear planning models of two types of compressed air energy storage are proposed. • A novel electricity-gas coupled energy hub for cascade utilization is structured. • Comparisons between energy-based and capacity-based energy storage are analyzed. Large-scale long-duration energy storage (LDES), like compressed air energy storage (CAES) and liquid air energy storage (LAES), is promising for high-penetration renewable energy consumption in the city-scale integrated energy system (IES). Due to high installation costs and challenges in decentralized control of distributed energy storage, this paper proposes an optimal planning model for an urban electricity-gas coordination hub (UEGCH) with centralized energy storage using large-scale LDES. Firstly, the UEGCH with energy cascade utilization is designed, where process-based linearized models of advanced adiabatic compressed air energy storage (AACAES) and LAES are established to make a trade-off between solving accuracy and speed. Then, a city-scale integrated electricity and gas system (IEGS) is constructed with multiple regions considering line-packing. Finally, a multi-scenario planning method is proposed based on X-means for scenario reduction, and the global optimum is obtained through linearization. Results show that compared with traditional gas storage tank (GST) in the UEGCH, the utilization of AACAES and LAES requires as little as 7 % and 0.7 % of the construction volume with lower carbon emissions and can be cost-competitive in terms of future advancement. As for different EESs, in contrast to the energy-based energy storage (EBES) (i.e., battery (BT)), the levelized cost of energy (LCOE) of the capacity-based energy storage (CBES), which includes AACAES and LAES, can be reduced by nearly 0.1 $/kWh, bringing an annual economic benefit of $ 3 million. Besides, the discharge duration of CBES can be increased to 13 h, demonstrating the application prospect in 100 % renewable consumption and islanding operation. Compared with AACAES, LAES can reach 11.67 times the energy density, with a drop of 6.11 % in operating cost. The abilities of EBES and CBES to locally consume renewables are respectively weaker and stronger than that of power-to-gas (P2G) combined with line-packing. Meanwhile, this paper further analyzes the impacts of temperature, discharge duration, renewable penetration, energy tariff, and demand on the operation and sizing of centralized energy storage. [ABSTRACT FROM AUTHOR]

• A hierarchical convex optimization framework for HEV-PCC is proposed. • A TSI-MPC approach is designed to address the speed planning problem. • An energy management strategy that combines regression model with PMP is designed. Predictive Cruise Control (PCC) achieves automated driving with improved vehicle economy by incorporating road gradient information from high-precision maps. However, existing research on PCC has primarily centered around conventional gasoline vehicles. Hybrid Electric Vehicle (HEV) offer superior fuel efficiency compared to their traditional counterparts. To further enhance vehicle economy by integrating the PCC system with HEVs, this paper proposes a hierarchical control architecture for HEV-PCC based on convex optimization. Firstly, considering spatial slope information from the road ahead, this paper introduces a Time-Space Integration Model Predictive Control (TSI-MPC) based on the principles of kinetic energy. Secondly, the paper combines a current regression model with the Pontryagin Minimum Principle (PMP) to present a Regression Analysis - Pontryagin Minimum Principle (RA-PMP) approach for the direct analytical solution of the energy management problem. Finally, the strategy is validated through simulation analysis and Hardware-in-Loop (HIL) testing on various real road scenarios. The result indicate that, in comparison to the Equivalent Consumption Minimization Strategy (ECMS) with constant speed cruising (CC), this method achieves an average fuel economy improvement of 9.45%. [ABSTRACT FROM AUTHOR]

[Display omitted] • SAMA, a new open-source microgrid optimization software, was introduced an validated. • Validation compared SAMA's results with industry-standard, Homer Pro proved accuracy. • Results for different locations and climates, confirming SAMA's reliability and accuracy. • SAMA introduces unique emission optimization and top-down pricing methodology for first time. • SAMA is open-source and free, which ensures accessibility and fosters innovation. • SAMA is broadly applicable for renewable, off-grid, grid-tied, and backup power systems. Although there are many software tools for simulations of hybrid energy systems, Homer Pro and Homer Grid are the only tools offering optimal sizing of hybrid energy systems. Originally developed as open-source software, they have been closed, which limits user-developers abilities to adapt and improve the software. In addition, all current proprietary offering suffer from the following limitations: i) high costs that limit accessibility to low-resource labs and individuals, ii) incapable of conducting multi-objective optimization, iii) constrained on any new innovations in hybrid energy system design and operation, iv) difficulties for users to specifically define prices and costs in inputs, v) inability to model different electric utility billing structures, vi) complex pricing methodology, and vii) the absence of machine learning-based predictive modeling. To overcome these limitations, this paper introduces and validates SAMA (Solar Alone Multi-objective Advisor), an open-source microgrid optimization software program designed to optimize hybrid energy system sizes economically using metaheuristic algorithms based on specific load profiles and meteorological data. Through rigorous validation exercises, SAMA's outcomes are compared against those generated by the Homer Pro software across distinct climatic conditions and geographical locations (i.e., Sacramento, California in the marine west coast and New Bern in humid continental climate zones of U.S., respectively). The results demonstrate congruence between SAMA and Homer Pro. SAMA can be used for a diverse array of applications from renewable energy systems to off-grid and grid-tied configurations, and from policy formulation to feasibility assessment. Unique features of SAMA include multi-objective optimizer, levelized emission optimization, different pre-defined utility billing structures, and a top-down pricing methodology. These features further enhance SAMA's adaptability, allowing users to tailor the software to their specific needs and system configurations. Finally, the paper anticipates future advancements that could refine component modeling, accelerate optimization processes, and incorporate advanced data analysis techniques such as machine learning to predict energy demand and production patterns. [ABSTRACT FROM AUTHOR]

• Providing an inclusive, up-to-date, and organized review of the published research. • Taxonomy of microgrid based on control structures, specifications and components. • Energy management summation and classification based on several significant factors. • Discussing some of the skilled methodologies and techniques developed or adopted. • Taxonomy of the different modeling and handling methods of the uncertainty. Energy is one of the essential foundations for the sustainable development of human society, so its management is necessary. Energy management system (EMS) can be explained as the procedure of optimizing, planning, controlling, monitoring, and saving energy to maximize operations and efficiency and minimize consumption. Microgrid (MG) requires EMS as an efficient and optimal tool owing to the stochastic nature of electrical loads and renewable sources. Moreover, energy management system is responsible for operation of a MG in reliable, secure and economical manner in either states of grid-connected or disconnected. Many literatures have recently focused on the expansion of advanced strategies of the MG energy management for establishing a self-sustained MG in both industrial and academic research. Thus, a comparative research is needed for having a 360° viewpoint of the energy management domain in MGs. In this regard, this research investigates a comparative and critical analysis of the developed strategies of the energy management for the MGs from different views and aspects from 2009 to 2022. The review strategy systematically adopted by the author includes: (i) Extracting research papers relevant to energy management in MGs; (ii) Filtering the significant papers to prepare a database of related research papers (iii) Classifying the used methods for EMS based on the technique, control strategies, and structure; (iv) Discussing potential directions for future studies. In a wider outlook, this research provides a systematic and updated review of energy management strategies for MGs developed by different researchers. The author hopes that academicians and practitioners can use the suggested framework as well as the offers presented for further studies on this significant yet sophisticated issue. [ABSTRACT FROM AUTHOR]

• Feasibility of a renewable hydrogen fed solid oxide fuel cell was investigated. • Fuel utilisation ratio affects the system's key performance indicators differently. • Levelised cost of £191/tCO 2 was predicted under 2050 scenario. Direct air carbon capture, as a negative emissions technology, is pivotal to lowering carbon dioxide concentration in the atmosphere. Accompanying the development and application of this technology, the high energy demand and substantial capital cost associated with direct air carbon capture have been persistent concerns. This paper aims to analyse the technical and economic feasibility of utilising a hydrogen fed solid oxide fuel cell as a source of both electricity and high-grade heat for the process of direct air carbon capture. It is vital that a renewable form of hydrogen production is used for this process to be sustainable, therefore a renewable hydrogen fed 50 MW solid oxide fuel cell is modelled, integrated with a direct air carbon capture process, resulting in a system with the capacity to remove carbon dioxide just over 270 kt/year directly from the air. The current levelised cost of capture for the system varies widely with the price of renewable hydrogen production, with an estimated range of £314–1,505 per tonne of carbon dioxide captured. As the cost of renewable hydrogen declines in the future, such a process could become a feasible alternative to natural gas fed direct air capture, with a 2050 levelised cost of capture anticipated to be £191 per tonne. [ABSTRACT FROM AUTHOR]

[Display omitted] • A high-temperature superconductor (HTS) magnet system for the maglev application. • Magnet energy-robustness, -density, and -economy improved by 96.8%, 66.7%, and 52.5%. • High defect tolerance reaching 716 A/mm2 current density and 25 T magnetic field. • A practical solution for energy bottleneck in HTS magnets/maglevs development. The blooming ultrahigh-speed SC maglev (superconducting magnetically levitated train) prompts green travel worldwide. We utilized high-temperature superconductor (HTS) magnets and have developed an energy-economical SC maglev prototype (Energ. Convers. Manage. (291)117247). In this paper, as a continuation, we further improve and maximize the performance of its key part – the HTS magnets, especially in compact high magnetic field and energy density operating conditions, by innovating an HTS magnet technology named the Shunted Extreme-NI Concept. The operational energy-robustness, -density, and -economy of HTS magnets, compared to the conventional type, are improved by 96.8%, 66.7%, and 52.5%, respectively. For a full-scale maglev equipped with this technology, the estimated energy consumption per passenger kilometer can be further reduced to below 20% of that of airplanes under the same cruising speed of 1000 km/h. This work is dedicated to advancing the energy performances of HTS magnets, heading to the future sustainable maglev transportation. [ABSTRACT FROM AUTHOR]

• The cost of carbon dioxide capture and storage is significantly reduced. • The output product of the system is methanol only. • Renewable energy utilization reaches 97.62 %. • The carbon emission is negative, about −0.344 kg carbon dioxide /kg methanol. • The levelized cost of methanol is 1.34 $/kg. Power-to-methanol technology represents a promising energy storage solution to manage the fluctuating supply and demand of renewable energy effectively. A novel methanol production process based on an off-grid wind/solar/Oxy-fuel power plant is presented in the paper, which consists of solar-wind energy, oxy-fuel combined cycle, proton exchange membrane electrolyzer, and carbon dioxide hydrogenation to methanol unit. The hydrogen produced by the proton exchange membrane electrolyzer is used to synthesize methanol, and the by-product oxygen is used in the oxy-fuel combined cycle. At the same time, low-cost carbon capture is achieved with liquefied natural gas cold energy utilization, and the collected carbon dioxide is used to synthesize methanol. The system carbon emission is negative, about −0.344 kg carbon dioxide/kg methanol, the system has no other products except methanol. The structure of renewable energy has a significant impact on the technical and economic performance of the system. Therefore, a comparative analysis of different wind/photovoltaic installed capacity ratios is carried out. The case study shows that the proposed system has the best performance when the wind/photovoltaic installed capacity ratio is 25 %/75 %, with a renewable energy utilization of 97.62 %, methanol production cost of 1.34 $/kg methanol, and an energy efficiency of 63.5 %. The proposed system may be a practical solution for methanol production from renewable energy. [ABSTRACT FROM AUTHOR]

• New efficient integrations of absorption, adsorption, and HDH plants are investigated. • Four innovative scenarios are proposed and compared to productivity and energy utilization. • The maximum improvement in productivity was between 1.57 and 2.94 m3.day−1 at 120 °C. • The maximum obtained GOR was between 1.38 and 1.75 at 120 °C. • The proposed integration demonstrates remarkable energy utilization efficiency. Thermal desalination technologies have been developed recently to solve some pressing problems, such as high energy expenditure, increasing fuel costs, and environmental problems related to conventional plants. However, these technologies still need to be enhanced in terms of water production and gain output ratio (GOR). This paper presents innovative and efficient combined thermal desalination plants consisting of absorption (ABDS), adsorption (ADDS), and humidification-dehumidification (HDH) desalination units to enhance energy utilization, water production, and overall system performance. Four innovative combined desalination plants employing different external heat recovery scenarios are presented and compared. The result from each scenario is evaluated and compared with those of the standalone ABDS and with other studies found in the literature at the same heat source temperatures. The heat source is mainly utilized to drive the ABDS plant. The ADDS and HDH are driven by the heat rejection from the ABDS components with different external heat recovery scenarios. Results illustrated that the maximum freshwater production generated from the proposed scenarios ranges between 1.57 and 2.94 m3.day−1 with a GOR of between 1.38 and 1.75 at 120 °C. Raising heat source temperatures from 55 to 120 °C decreased the improvement in the water productivity from 618.5 to 224 % and decreased the enhancement in the GOR from 222.8 to 99 %. In scenarios where the ADDS and HDH are driven by the heat rejection from the absorption and condensation process of the ABDS, the maximum freshwater production results from the ABDS unit. On the other hand, in scenarios where the ADDS and HDH are driven by the outlet hot water from the ABDS-generator, the maximum freshwater production is obtained from the HDH unit. The finding provided that the proposed innovative scenarios have an effective improvement in overall system performance indicators. [ABSTRACT FROM AUTHOR]

• The maximum treatment capacity of 1167.44 g is achieved in Mode 1 systems. • Optimization of operating conditions enhances energy efficiency and reduces costs. • Systems in Mode 2 exhibit higher energy efficiency but a lower COD removal value. • Switching modes maximize energy utilization across different application scenarios. A multi-stage reverse electrodialysis reactor (MSREDR) wastewater treatment system with an independent strategy is researched theoretically in this paper. The influences of operating conditions on the system performance and levelized costs are explored. Results illustrate that reducing the number of membrane pairs not only enhances the system performance but also decreases the levelized cost of wastewater treatment. A high concentration of concentrated solution facilitates enhancing the total COD removal value and reducing the levelized cost, but it adversely affects the energy conversion efficiency of the system. The optimal total COD removal value and energy efficiency are respectively 1164.77 g and 3.58 % under the given conditions. However, when the wastewater discharge rate from the plant is lower than the maximum treatment capacity, it transitions from a wastewater treatment mode to a combined power generation and wastewater treatment mode. Compared to the system operating in the wastewater treatment mode, the system operating in the combined power generation and wastewater treatment mode exhibits higher effective energy and energy efficiency but a lower COD removal value. This research successfully achieves the flexible adjustment of operating modes based on real-world applications, thereby maximizing energy efficiency and establishing a theoretical foundation for practical implementations. [ABSTRACT FROM AUTHOR]

[Display omitted] • PCM energy storage and PV/T coupled multi-source heat pump systems were combined. • The thermal performance, energy efficiency, and economy of the system were analyzed. • The performance of paraffin C17 and water as energy storage materials were compared. • The performance of six low-temperature PCMs applied to the system were analyzed. • Compared to the existing system, it saves 56 % of energy and 27.7 % of operating costs. To improve the application of renewable energy in the heating zone, as well as to address the limitations of air and water source heat pump. The study presents a PV/T (photovoltaic/thermal) coupled air–water source heat pump system integrated with phase change energy storage. A theoretical analytical model and TRNSYS simulation model of the system were developed to evaluate the thermal performance, energy efficiency and economics of the system. The performance of phase change energy storage was compared with that of water storage, and the effect of different phase change materials on the system characteristics. The results show that the coupled system achieves a seasonal performance factor of 2.3, a 56 % reduction in energy consumption, and a 27.7 % reduction in operating costs compared to a conventional gas boiler system. Comparative analysis with the water storage system showed that the system equipped with phase change materials performed well in terms of energy consumption, operating costs and heating stability. In addition, the density of the phase change material has a biased effect on the overall performance of the system. This paper can provide a reference value for the study of renewable energy heating systems in cold zone. [ABSTRACT FROM AUTHOR]

• A cogeneration system based on CAES, ORC and hybrid refrigeration system is investigated. • The maximum to minimum pressure ratio of CAES tank is scrutinized as a critical parameter in present paper. • Energetic and exergetic efficiencies of the CCHP system and its subsystems are analyzed. • All the components, working fluids and subsystems are environmentally-friendly. • T-S diagrams of the CAES, ORC and compression-absorption refrigeration are presented. Combined cooling heating and power (CCHP) is a promising energy supply technology which is widely installed in buildings due to its feasibility from techno-economic, performance and environmental points of view. In present paper, a novel cogeneration system based on compressed air energy storage (CAES), organic rankine cycle (ORC) and hybrid compression-absorption refrigeration cycle is proposed. The main objective of the proposed system is to improve the efficiency of the CAES system by providing cooling capacity from the rest of hot gases in turbine exhaust through employing an ORC driven refrigeration system. Also, the effect of the maximum to minimum pressure ratio of CAES vessel as a critical parameter on CAES volume and round trip efficiency (RTE) has been scrutinized. Using the environmentally-friendly compression-absorption refrigeration system, high temperature thermal energy storage (HTES) and R407C as the organic working fluid decrease fossil fuel consumption and make the proposed system fully environmentally-friendly. The results indicate that 2280 kW electrical energy and 416.7 kW cooling capacity are simultaneously generated during peak period. As a result, with 13.15% RTE enhancement in comparison to the individual CAES system, it reaches to 65.15% based on the proposed modification. Also, the results show that the overall exergy efficiency and total exergy destruction of the components are 49.17% and 1419 kW, in which the pressure regulating valve and the air turbine have the highest irreversibility and exergy destruction. [ABSTRACT FROM AUTHOR]

• In gas turbines optimization no ideal vs perfect gas comparisons exist in literature. • Maximum errors up to 15% are found when perfect gas model is used in SFC optimization. • Greater uncertainty is found in the specific power of the SFC – optimized cycle (up to 30%). • Huge errors are found in compressor pressure ratio values of optimal SFC. The optimization of a gas power cycle can be thermodynamical, techno-economical, thermo-economical and so on but, in general, the thermodynamic modeling is mandatory to solve the problem. Once the thermodynamic model is established the properties of the gases present in the cycle must be evaluated and the simplifications made for this evaluation could lead to inaccurate and even misleading results. In this paper the effect of using the perfect gas model in the optimization of the Specific Fuel Consumption (SFC) of the open simple cycle gas turbine has been analyzed. The results are obtained for compressor and turbine inlet temperatures (CIT and TIT) between 260 K–320 K and 1200 K–1800 K respectively. The optimization yields the minimum of SFC but also the corresponding values of compressor pressure ratio and specific power. In this work the optimization is first performed with a highly accurate ideal gas modeling approach in order to generate benchmark results. Afterward, the optimization is performed with a perfect gas modeling approach using four different methods (named A, B, C and D) to evaluate the constant value needed of the isobaric heat capacity. It is found that the optimization results can depend strongly on the method or rule used to evaluate the heat capacity. As an example, the uncertainty in the optimal value of SFC is between 8.5% and 14.9% with method C and below 3.2% with method D. In general, huge deviations in the compressor pressure ratio are found. Values higher than 16% for CIT below 300 K regardless the TIT value are found with methods A, B and C. In the worst case this deviation can be even higher than 100%. In general, this uncertainty gives rise to higher deviations in the specific power than in optimal SFC values. For example, with the method B and a TIT of 1800 K the ranges of the relative error are 56%–112%, 4.9%–6.2% and 17.8%–26.7% in the compressor pressure ratio, optimal SFC and specific power respectively. With respect to the CIT and TIT dependence the deviations in the compressor pressure ratio and specific power increase for high TIT and low CIT. This work is an extension of a previous paper publish by the author where the detailed development of the modeling approaches used in this work can be consulted. [ABSTRACT FROM AUTHOR]

Highlights • A large-scale of 15,488 EnergyPlus simulations for commercial buildings in the U.S. • Nationwide energy savings for a single and combinations of multiple ECMs. • Nationwide energy savings for the ECM of fault detection and diagnostics. Abstract Buildings consumed 40% of the energy in the United States, which is more than any other sectors of the U.S. economy, including transportation and industry. The majority of this energy was used for lighting, space heating, cooling, ventilation, and water heating in the buildings. It is well known that the carbon emission is proportional to the energy consumption. Enhancing building efficiency becomes one of the easiest, most immediate and most cost-effective ways to reduce carbon emissions. This paper focuses on the simulation-based nationwide energy savings analysis of different energy conservation measures (ECMs) to enhance building energy performance. The study includes 44 different ECMs, which were simulated in 16 different climate zones for 11 different commercial building types in the U.S. Simulations were conducted using a whole building simulation program, EnergyPlus. Commercial prototype building models from the U.S. Department of Energy [1] were used as the baselines. Model input files were automatically modified to incorporate with 44 different ECMs using scripts. The baselines were based on American Society of Heating, Refrigeration, and Air-conditioning Engineers (ASHRAE) [2] Standard 90.1 and International Energy Conservation Code (IECC). A total of 15,488 simulations were conducted to study the nationwide energy savings potentials. The details of these 44 proposed ECMs and their corresponding nationwide saving potentials are presented and discussed in this paper. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Energy storage systems for series hybrid excursion ships are studied. • CO2 emission are avoided during the casting-off and the docking maneuvers. • Full model using Energetic Macroscopic Representation (EMR) is described. • 1.39 kg of CO2 during the casting-off/docking maneuvers can be avoided. • Global consumption and emissions can be reduced by 20%. Abstract Ecological areas visits require appropriate management of key ecological features. In protected reserves innovative systems should be developed to facing problems of pollution, exhaust fumes and noise. These underlying conditions lead to special challenges for excursions ships. The switching to a cleaner, safer and quieter transport system seems to be a sustainable long-term solution for the problems of ecological areas, where more electric ship can be an important part of the solution and principally for the last mile. This paper presents a design approach of a hybrid Energy Storage Systems (ESS) for new generation of series hybrid excursion ship devoted to ecological areas to avoid any emission during the casting-off and the docking maneuvers. The main purpose of the paper is to show that, even if the hybrid ESS plus series-hybrid propulsion were already used to other vehicles, the gain for a ship with no regenerative capability is not evident. The proposed hybridization is built upon a fully-active parallel topology with battery and supercapacitors. The sizing methodology and the configuration of the ESS are detailed. For a real mission profile in Alster Lake (Hamburg, Germany) it is shown that a small battery pack of 2 kWh with a supercapacitor bank of 0.54 kWh are necessary to have zero-emission maneuvers. The graphical formalism Energetic Macroscopic Representation (EMR) is used to describe the model and to establish an energy analysis tool. An inversion-based control scheme is then deduced from the EMR and simulation results are provided to validate the proposed methodology. The usage of hybrid ESS avoids 1.39 kg of CO 2 during the casting-off and docking maneuvers despite increasing consumption of 0.2 l (+8%). However, the plug-in capability can be introduced and a recharge of the battery when the ship is docked could reduce the global consumption and emissions by 20% in comparison to the original ship. [ABSTRACT FROM AUTHOR]

District Heating (DH) systems will play an important role in future sustainable energy systems. Existing networks can be optimized by lowering primary return temperatures in order to improve the use of geothermal resources. This can be done by installing triple-pipe systems. This paper defines the concept of triple-pipe configurations as it is understood in France. The objective of this paper is to demonstrate the relevance of those configurations for optimizing geothermal DH system efficiency. A dynamic thermal-hydraulic model was developed using the programming language Modelica. A generic case study is modeled considering the extension of an existing network. It is shown that triple-pipe configurations offer lower return temperatures and gas consumption, while increasing of the renewable energy share in the network energy mix. [ABSTRACT FROM AUTHOR]

• A novel fully-active PEMFC-Lithium battery hybrid power system was proposed. • Direct power supply was realized by automatic ON/OFF switches to avoid energy loss. • Simple and effective mode switch strategy was designed for the energy management. • The proposed construction can extend the service-life of PEMFC and Lithium battery. High-performance unmanned aerial vehicles (UAVs) have become increasingly popular in applications across industrial inspection, forest patrol, and aerial photography. For high-performance UAVs, hybrid power systems consisting of proton exchange membrane fuel cells (PEMFCs) and Lithium batteries are usually recommended for improving their flight endurance. In this paper, a novel fully-active PEMFC-Lithium battery hybrid power system is designed for UAV applications. The proposed construction employs an automatic ON/OFF switch in parallel with a DC-DC converter to control the PEMFC and a second automatic ON/OFF switch replacing the commonly used DC-DC converter to control the Lithium battery. With this design, we enable the two energy sources to directly supply power through control of the ON/OFF state of the two automatic switches, thereby significantly avoiding energy loss in the DC-DC converter. The design further allows for separate or joint operation modes of the PEMFC-Lithium battery hybrid power system to be actively selected through combined control of the automatic ON/OFF switches and the DC-DC converter. On this basis, a simple and effective rule-based strategy can be designed for the energy management between the PEMFC and Lithium battery. Experimental results successfully demonstrate the feasibility of the proposed fully-active PEMFC-Lithium battery hybrid power system, with numerous simulations results showing that the proposed fully-active hybrid power system reduces hydrogen consumption by 5.6 g and improves energy utilization by 7% in UAV applications when compared with the conventional fully-active hybrid power system under the same power requirement. Additionally, the active mode switch control can effectively alleviate voltage degradation of the PEMFC as well as improve the output performance of the Lithium battery, which would effectively extend the service-life of the hybrid power system. This paper successfully demonstrates the advantages of the proposed fully-active PEMFC-Lithium hybrid power system in UAV applications. [ABSTRACT FROM AUTHOR]

This paper proposes a Multi-stage Energy Management System (MS-EMS) for power distribution in a smart microgrid comprising a photovoltaic system (PV), an Energy Storage System (ESS), and connected to an Electrical Power Grid (EPG). The proposed MS-EMS consists of two layers, the Anticipative Layer (AL) and the Reactive Layer (RL). The AL uses a Multi-objective particle swarm optimization (MOPSO) algorithm to determine the optimal power setpoints for each source over the next 24 h based on predicted energy demand and solar power generation. The RL utilizes real-time data collection and Extremum-Seeking optimization (ES) to compensate for prediction uncertainties by adjusting the ideal power setpoints in real-time. In addition, this paper addresses both the issues of management and prediction. It introduces a forecasting system that effectively predicts the next 24 h of load demand and PV power generation using actual data, by integrating a physical model with artificial neural networks (ANN). The efficiency of the proposed MS-EMS is highlighted using experimental data collected in real-time on a physical bench in Morocco. The performances of the proposed MS-EMS system are compared with those of existing EMS strategies, including an existing industrial solution. The comparison shows that the proposed MS-EMS substantially overperforms in terms of three criteria: energy bill, battery degradation cost, and peak-to-Average Ratio (PAR). Despite forecasting uncertainties, the experimental test shows a remarkable 6% gain in the reduction of the energy bill and PAR compared to an offline strategy (where uncertainties were not considered). Furthermore, it achieved a 5% and a 3% gain in the reduction of the energy bill and PAR, respectively compared to an online strategy (focused on real-time optimization). Additionally, compared to an existing industrial solution, the MS-EMS achieves a reduction in energy bill and PAR of 9% and 56% respectively while taking into account battery degradation constraints described in this study. • Multi-stage approach for Multi-Objectives Grid Management with Forecast Uncertainties. • Extremum Seeking approach for real-time energy management problem solving. • Artificial Intelligence for electrical load and PV power forecasting. • Experimental comparison of the proposed strategy with an existing industrial solution. • Experimental test shows a reduction in energy bill and PAR of 9% and 56% respectively. [ABSTRACT FROM AUTHOR]

[Display omitted] • Evaporation affects ignition in homogeneous conditions by changing thermal states. • Stratification causes preferential ignition, front propagation and scalar dissipation. • Induction timescale is analyzed by statistics in turbulent environments. • Enhanced turbulence and scalar dissipation cause non-monotonic deflagration speed. • Turbulence affects ignition front by changing spatial gradients of ignition delay. Internal combustion engines are the dominant power sources in transport, accounting for significant amounts of fuel consumption and pollutant emissions. Low-temperature combustion is a promising technology for engine combustion, whose main challenge is the complex control of two-stage auto-ignition that determines the performance of a low-temperature combustion engine. This paper systematically reviews the state-of-the-art advances in auto-ignition modeling which is an essential tool to understand auto-ignition mechanisms and provides valuable guidance for designing more efficient and cleaner engines. This paper focuses on turbulence, evaporation and chemistry effects without the consideration of inter-droplet interactions. Five models with increasing complexity are discussed and compared, including homogeneous models without and with evaporation (models 1 and 2), droplet simulation in static environments (model 3), and direct numerical simulation without and with evaporation (models 4 and 5). Rapid mixing leads to homogeneous conditions in models 1 and 2, in which two-stage auto-ignition is divided into low-temperature induction, low-temperature auto-ignition, high-temperature induction and high-temperature auto-ignition. Model 1 only considers chemical reactions and auto-ignition is determined for a certain thermal state. Droplet evaporation affects the auto-ignition evolution in model 2 through evaporation-induced changes in the thermal state. Compared with homogeneous models, droplet evaporation in model 3 leads to compositional and temperature stratifications which cause three new phenomena: preferential auto-ignition, reaction front propagation and non-zero scalar dissipation rate. Models 4 and 5 introduce turbulent effects on induction timescale and front propagation. Finally, challenges and future directions in auto-ignition modeling are outlined. [ABSTRACT FROM AUTHOR]

• A two-layer framework is proposed for building HVAC and associated multi-energy consumption optimization. • 100% renewable complementarities are proposed for building multi-energy supplies. • A R-C thermodynamic network is formulated to model the building HVAC. • AC slow charging and DC fast charging types of EVs are considered and managed via a novel real-time supply–demand pricing. Building heating, ventilation, and air conditioning (HVAC) and associated energy consumption make up the more and more important part of the world, whose reduction provides a cost-effective path to the "dual carbon" goal. This paper proposes a two-layer management of HVAC-based multi-energy buildings under proactive demand response of fast/slow-charging electric vehicles (EVs). In this paper, the building HVAC is mathematically formulated via a R-C thermodynamic model, which coordinates with multi-energy converters and storages to form a 100% renewable building. The building management is a challenging optimization problem due to its severe constraints and strong spatio-temporal couplings. In the first layer, a day-ahead multi-energy dispatch is formulated to economically optimize the electrical, heat, gas energy carriers. In the second layer, alternating current (AC) slow charging and direct current (DC) fast charging types of EVs are considered and managed via a novel real-time supply–demand pricing mechanism. After acquiring the economical dispatch references in the first layer, the second layer implements a model predictive control (MPC)-based real-time scheduling to handle the multi-energy supply–demand fluctuations. The original two-layer optimization is further handled via mixed-integer linear program (MILP) reformulation for high-efficient solving. Comparisons have shown the advantageous performances of the proposed two-layer optimization over economics and practicability. Simulations results show that the overall system operating cost can be reduced by at most 3.01% with a higher operational flexibility in building management. [ABSTRACT FROM AUTHOR]

[Display omitted] • Morocco could achieve a 92 % RE integration rate by 2050 with an additional $32 billion total cost. • Implementing EE measures can reduce energy demand by 15 % from 2030 to 2050 compared to baseline forecasts. • The NANES scenario results in the lowest emissions rate of 0.29 MtCO2e by 2050. • A comprehensive policy framework tailored for developing countries is proposed. • Advanced planning tools and an adapted OSeMOSYS model improve energy resource management in volatile conditions. Developing countries encounter numerous challenges, such as limited access to reliable electricity and a heavy reliance on imported fossil fuels. To satisfy the rising energy demand, which is essential for economic growth, these regions are shifting towards sustainable energy solutions. Solar and wind power have emerged as key and secure energy sources. This research develops an enhanced OSeMOSYS energy system model to examine long-term energy supply strategies, using Morocco as a case study. The proposed model addresses the specific needs of decision-makers in developing countries, enabling the achievement of renewable energy targets and optimal temporal resolution. A baseline and three alternative scenarios were developed, exploring both a restructuring plan to address existing gaps and a forward-looking policy targeting nearly 100 % renewable energy. These scenarios are assessed in terms of installed capacity, generation mix, investment costs, variable and fixed costs, storage capacity utilization, and carbon emissions. The results indicate that a 92 % integration rate for renewables is feasible at an additional cost of $32 billion, thanks to new energy efficiency measures reducing demand by 15 % between 2030 and 2050 compared to baseline forecasts. Furthermore, an ambitious energy strategy by 2050 could achieve the lowest emissions rate of 0.29 Mt, paving the way for complete decarbonization. Technologically, investment in pumped-storage hydroelectric plants is the most viable backup option for a country dependent on natural gas imports. Our findings emphasize that a diversified energy mix and robust energy efficiency plans are essential for a rapid and feasible transition of the country's energy system. This paper offers an enhanced energy model to help decision-makers in developing countries set targets on the share of renewables in total installed capacity, thereby increasing their integration rate at minimal additional cost. [ABSTRACT FROM AUTHOR]

The increase of power plants’ conversion efficiencies, together with the high share of renewable energy sources in the electricity production for some countries, pushes for the use of heat pumps for space heating when aiming at reducing the associated primary energy consumption. However, the effective reduction of primary energy consumption should be supported by careful evaluations, as a number of parameters influence the heat pumps performance, including outdoor temperature, supply temperature, heat load and electricity primary energy factor. The variability of such parameters increases the complexity of the analysis, and annual or monthly average calculations might lead to incomplete evaluations and thus to sub-optimal solutions. This paper performs a hourly simulation of the operation of an air-source heat pump for space heating, relying on the available heat demand data of real buildings currently connected to a district heating network. In addition, the paper proposes the calculation of the hourly primary energy factor of the electricity supplied by the power grid, as the variability of the generation sources plays a key role in the global analysis of the energy system’s conversion efficiency. The results show that in all the considered cases the heat pumps provide potential primary energy savings compared to natural gas boilers, thanks to the combined effect of their high coefficient of performance and the low electricity primary energy factor in the analyzed context. The primary energy consumption reduction obtained in each case is in the range 10–40%, with a median value close to 30%. Moreover, the comparison between average and high-resolution calculations of primary energy factors shows the possible underestimation of the potential primary energy savings when yearly or monthly data are adopted. [ABSTRACT FROM AUTHOR]

This paper proposes a new hydraulic excavator boom driving system using novel asymmetric pump to reduce energy consumption. Due to large throttling loss and gravitational potential wasting, conventional hydraulic excavator boom driving system has very low energy efficiency. This paper aims to improve the energy efficiency of the hydraulic excavator by reducing throttling loss and regenerating potential energy directly based on a novel pump controlled system. The system under consideration utilizes a novel asymmetric pump which has three ports, of which two are connected to the hydraulic cylinder, and the other one is connected to an accumulator. Thus, this system can regenerate the potential energy directly and can basically match the unequal flow rates of the single rod cylinder. The structure and working principle of the asymmetric pump controlled single rod cylinder system are studied in depth in this paper. To better demonstrate the performance of the proposed system, the popular independent metering circuit, which has been proposed to improve the efficiency of boom system, is used as a comparison. Moreover, experimental results of the two systems have been obtained based on a real 6-ton hydraulic excavator. The boom driving system of the excavator was first modified to the independent metering circuit to conduct experiment, and afterwards was modified to the proposed system. Experimental results show that, about 82.7% of the potential energy could be regenerated and reutilized by the proposed system. Compared with the independent metering circuit, the electric power consumption of the boom system during moving-up operation can be reduced by 76.1%. Furthermore, if the energy efficiency of the power source is considered, the energy consumption during the entire boom cylinder working cycle can be reduced by 75.0%. Finally, it is worth noting that the proposed system can be applied in all kinds of heavy-duty construction machineries, though only hydraulic excavator is experimented. [ABSTRACT FROM AUTHOR]

The paper is part of the development of a novel underwater isothermal Compressed Air Energy Storage (CAES) system. Compared to conventional CAES plant, the performances of this system only depend on the electrical energy required for a round-trip cycle; performances of each sub-system of the power conversion process takes part of the overall efficiency. Consequently, this work is focused on an optimal energy management of the electrical power conversion system driving the isothermal hydro-pneumatic mechanism enabling the air compression/expansion. After examining inherent characteristics of conversion components challenging the overall conversion efficiency, we propose an efficient platform layout based on the segmentation of the energy conversion multiplying power conversion systems with different power ranges. Then, we establish control laws required by the electrical multi-machines system in order to drive pumping systems closed to their best efficiency points. However, these laws subject the conversion platform to a transient and variable operating needing the design of robust controller structures. Finally, we develop a dynamic reversible modelling of the multi-physic conversion platform along with the control scheme. The layout is modelled on Matlab® Simulink® environment and the paper closes with simulation results. We evaluate the dynamic performances of the compressed air storage system in both storage and production mode. Moreover, the effectiveness of power segmentation for the grid integration of the proposed system is discussed. [ABSTRACT FROM AUTHOR]

This paper presents a model of a diesel-combustion-engine-based variable speed generation unit driving a permanent magnet generator loaded by a power converter. Variable speed operation of the internal combustion engine facilitates fuel saving when the load profile changes, but it requires a power conditioning unit such as an electronic converter. Power converter operation is well known from wind energy conversion systems, in which variable speed operation increases their efficiency. The paper presents modeling and speed control of an exemplary diesel engine, and control of output voltage and current of the power electronics converter loading the generator. Special attention has been paid to elaboration of the methods of minimum specific fuel consumption points tracking for the given load. Incremental algorithms can find minimum specific fuel consumption in the case in which the details of fuel consumption curves are not exactly known. The incremental algorithm has been adopted from wind energy conversion systems and partly modified to avoid torque peaks during incremental step changes of reference speed. The concept has been validated in a simulation using data of a real model of an internal combustion engine through a three-dimensional approximation of fuel consumption characteristics. [ABSTRACT FROM AUTHOR]

In the present paper hydrogen production from biomass gasification using various agents is investigated and compared theoretically, from the viewpoints of the first and second thermodynamics laws. Gasification of wood and paper, as two types of common biomass feedstocks, is assessed using four gasification agents namely: air, oxygen-enriched air, oxygen and steam. Thermodynamic equilibrium model is employed to simulate the gasification process, the results of which are validated using available theoretical and experimental data in literature. The NO x and SO x emissions from the biomass gasification are also considered in the model and a sensitivity analysis is performed to determine the accuracy of the results regarding to the uncertainties of the input data. A parametric study is conducted to assess the effects of key operating parameters on the hydrogen concentration and calorific value of producer gas, energy and exergy efficiencies of the process and exergy destruction rate at different operating conditions. The results indicate that the higher values of hydrogen production is associated respectively with using steam, oxygen, oxygen-enriched air and air as the gasification agents. Also, it is concluded that for the gasification process the highest value of sensible energy efficiency is obtained for air gasification, while the highest exergy efficiency, as a rational criterion, is obtained for steam gasification for which the calorific value of the producer gas can reach to higher than 11 MJ/Nm 3 . [ABSTRACT FROM AUTHOR]

Financial issues have been always one of major priorities in scheduling of energy systems. Although these systems are able to serve several types of energy demands but generated emission by these systems is a challenging problem. Since improvement of each one of mentioned issues has negative effects on the other issue therefore a trade-off solution is necessary to be obtained between these issues. In this paper, a multi-objective model has been presented to satisfy both economic and environmental objectives of a hub energy system in the presence of demand response program. In the proposed paper, ε-constraint and max–min fuzzy satisfying methods have been employed to solve and select the trade-off solution. The main reason of implementation of demand response program is to reduce operation cost and improve environmental performance of hub energy system. In fact, demand response program transfers some percentage of load from peak periods to off-peak periods to flatten load curve which leads to reduction of cost and emission. A mixed-integer linear programming has been used to simulate the proposed model and general algebraic modeling system software has been utilized to solve it. A sample hub energy system containing renewable and non-renewable energy resources has been studied and comparison results are presented to validate efficiency of proposed techniques. [ABSTRACT FROM AUTHOR]

• TIP-EMS enhances EV energy efficiency by integrated prediction and energy management. • Significant driving economy boost; 1.6%-4.2% better than state-of-the-art PEMS. • TIP-EMS shows robust performance with varying prediction weight adjustments. To enhance the energy efficiency of electrified vehicles (EVs), developing effective energy management strategies (EMS) for hybrid storage systems is essential. Predictive EMS (PEMS) that foresee future vehicle speeds have demonstrated substantial potential in boosting EMS performance. However, traditional PEMS models, employing a sequential approach of speed prediction followed by energy allocation, are hampered by cumulative errors. These errors from the initial speed predss this issue, this paper introduces a novel solution: the trainable integrated preiction negatively impact the efficiency of subsequent energy management. To addrediction and energy management strategy (TIP-EMS). Contrasting with conventional sequential PEMS, TIP-EMS features a dual-branch, integrated neural network, which is fully trainable. This network processes driving status inputs via attention layers, with one branch dedicated to energy management objectives using a reinforcement learning (RL) algorithm, and the other to vehicle speed prediction. Both branches are trained simultaneously, but post-training, only the RL branch is activated for energy management. Implemented with a soft actor-critic RL algorithm, TIP-EMS is applied to a fuel cell EV for optimized energy management. The validation involved training TIP-EMS using 27 driving profiles, which developed its prediction and energy management capabilities, followed by tests in untrained scenarios. The results show that TIP-EMS surpasses conventional sequential PEMS by up to 4.2% in scenarios where prediction accuracies are comparable, highlighting the efficacy of the trainable integrated mechanism. In addition, TIP-EMS exhibits superior energy conservation compared to non-predictive RL strategies. Lastly, TIP-EMS exhibits robustness to adjustments in the weight given to the prediction objective, further confirming its practical applicability. [ABSTRACT FROM AUTHOR]

• Effects of structural factors on the new compressor performance are analysed. • Equivalent stroke diameter ratio is the key factor for power consumption. • Diameter ratio of pistons is the dominating factor for the mass delivered. • The optimal parameters for low specific energy consumption are obtained. • The specific energy consumption is 2328.49 kJ/kg under the optimal parameters. The ionic compressor has a prospective application potential for the conversion of mechanical energy into internal energy in high-pressure hydrogen as the ionic liquid can separate the metal piston and the hydrogen gas. The sloshing of the liquid inside is inevitable in such a liquid piston compressor, which has an impact on the specific energy consumption of the hydrogen compression. The thermofluid behaviour of this liquid sloshing can be effectively influenced by the baffle structure and piston trajectory. A novel concentric two-piston compressor is proposed in this paper, which has a unique structure that can act as a baffle inside and actively influences the fluid flow by adjusting the piston trajectory. The quantitative influence of key structural design factors on the compressor performance is investigated by mathematical modelling, based on which the optimal structural design was obtained by Taguchi and analysis of variance methods. Results indicate that the diameter ratio of Piston A to Piston B is the dominating factor for both the mass delivered and the specific energy consumption. With the optimal design in the structure, the specific energy consumption is found as 2328.49 kJ/kg, where the mass delivered and power consumption are observed as 21.42 kg/h and 13.86 kW, respectively. [ABSTRACT FROM AUTHOR]

• A Rankine-based pumped thermal energy storage concept with coordination design. • Evaluation on the potential of low-temperature heat integration is considered. • A systematic investigation into the proposed concept is conducted. • A round-trip efficiency of over 72 % is achieved under a 100 K temperature span. • Strong mutual promotion of the thermal integration is observed. Rankine-based pumped thermal energy storage (PTES) is a potential electricity storage technology for accelerating the integration of renewables. This paper provides a novel Rankine-based PTES concept based on cascade-charging, dual-expansion, and hybrid thermal storage, which enables large temperature span and the cooperative thermal matching of the heat pump, thermal storage, and heat engine. A system layout and the corresponding theoretical model for energy and exergy analysis are developed. The integration of low-temperature heat is considered, and multiple criteria are defined to evaluate the thermal energy utilization quantitatively. Afterward, a systematic investigation into its performance is conducted. The influence of key parameters is analyzed with a multiobjective optimization to unveil the trade-off relations between different performance indicators. Beyond that, the exergy loss distribution of the presented concept is revealed, and a comparison with the traditional concept is also performed. Results show the concept has promising comprehensive performance. A round-trip efficiency of over 72 % is achieved under a 100 K temperature span with the exergy efficiency of heat engine reaching about 70 %. Moreover, the strong mutual promotion of thermal integration is observed. The concept reported here can offer a meaningful reference for the coordination design of the Rankine-based PTES. [ABSTRACT FROM AUTHOR]

[Display omitted] • Solar-hydrogen hybrid system integration proposed for oil & gas industry. • Techno-economic-environmental optimization using novel Fick's Law Algorithm. • System sizing using Fick's Law Algorithm show an optimization in efficiency and cost. • Study shows 45% solar, 35% fuel cell, 20% gas turbine power contribution. • Renewable energy integration in oil & gas cuts CO2 emissions, boosts sustainability. The global demand for sustainable energy solutions in the oil and gas industry has stimulated interest in the integration of renewable energy sources. This paper investigates the techno-economic and environmental aspects of incorporating a solar-hydrogen-based hybrid renewable energy system (SHRES) into oil and gas processing facilities. The proposed SHRES, comprising Solar PV modules, hydrogen production and storage systems, and a gas turbine generator (PV-FC-EL-Tank-GT), aims to enhance energy efficiency and reduce the carbon footprint of energy-intensive operations. The study utilises a multidisciplinary approach, encompassing engineering, economics, and environmental analysis. The techno-economic evaluation employs detailed modelling and optimisation using Fick's Law Algorithm, ensuring efficient energy production and cost-effectiveness. Ecological assessments quantify potential reductions in greenhouse gas emissions and other environmental impacts. The technical and economic evaluation identifies the electrolyser system as the most significant cost contributor (57%). The optimised system balances energy sources with 45% from PV modules, 35% from fuel cells, and 20% from gas turbines, showcasing substantial reliance on renewable energy while maintaining required power generation. Addressing the urgent need for sustainable energy solutions in the oil and gas industry, the study highlights the potential of SHRES integration. By employing Fick's Law Algorithm, alongside with 80 % of renewable energy integration, the research optimises system components to optimise the annualised cost to be $57,539.85, decrease to zero the Loss of Power Supply Probability (LPSP), and mitigate CO2 emissions to a lowest value of 0.147 gCO2eq/kWh (by 80 %). The electrolyser system's pivotal role and the distribution of power generation sources are emphasised. This study presents a novel approach to integrating solar-hydrogen systems into oil and gas processing facilities, aiming for sustainability. The findings underscore the significance of the electrolyser system and the distribution of power generation sources in optimising the SHRES. Recommendations for renewable energy integration and potential reductions in CO2 emissions and costs are discussed, providing valuable insights for future energy policies. [ABSTRACT FROM AUTHOR]

• Develop an energy prediction framework - Vehicle Energy Conservation Equation (VECE) • VECE coefficients were correlated with vehicle type, speed, and acceleration. • VECE demonstrated low data classification requirements and strong data adaptability. • VECE achieved a minimum prediction error of 4.2% for cumulative vehicle energy. • VECE exhibited excellent usability, coefficient interpretability and extensibility. Predictive models for vehicle energy consumption are crucial for sustainable development in urban road traffic systems. This paper comprehensively reviews classic predictive models and develops a novel statistical-dynamical energy consumption prediction framework called Vehicle Energy Conservation Equation (VECE). VECE is constructed based on the principles of vehicle energy flow and regression analysis, employing a continuous and concise mathematical formulation. Its coefficients possess clear physical interpretations, allowing for application in various vehicle categories. To validate VECE, this study collected energy consumption data from 28 vehicles, including 9 diesel vehicles, 16 gasoline vehicles, 1 ethanol gasoline vehicle, and 2 battery electric vehicles. A rigorous data processing procedure was designed. Data analysis revealed that the VECE coefficients are correlated with vehicle type, speed, and acceleration. VECE's predictive performance is minimally impacted by the number of vehicle categories, effectively modeling energy consumption for vehicles of the same fuel type or size category. Comparative analysis with E-EcoGest, VT-Micro, PERE, and CMEM demonstrates the moderate accuracy of VECE in predicting instantaneous vehicle energy consumption while excelling in predicting cumulative energy consumption. The minimum relative percentage error for the cumulative predicted values is 4.2%. Overall, VECE demonstrates outstanding performance in computational simplicity, coefficient interpretability, adaptability, and extensibility, making it a crucial tool for achieving energy-efficient road transport systems. [ABSTRACT FROM AUTHOR]

• "Transition to sustainable multi-building energy systems can reduce greenhouse gas emissions by synergising the multiple renewable energy sources with specific structural characteristics and occupancy constraints of buildings." • "To ensuring energy flexibility and resilience, optimization strategies for multi-building energy systems vary significantly with the climatic context and potentials for integrating energy storage technologies, highlighting the necessity for adaptable designs considering future energy demands and the expansion of district-level systems." • "There is a pressing need for more user-friendly multi-building energy system simulation tools to facilitate effective long-term planning and to optimize the design and management of energy flows among multiple buildings, ensuring maximum efficiency and sustainability. The transition to clean and sustainable energy systems in the building sector is vital to reduce global greenhouse gas emissions. In this regard, shifting the focus from single buildings to clusters of buildings, such as at the district level, can provide more effective sustainable solutions. In this study, the term Multi Building Energy Systems (MBES) was introduced to represent various scales, from local communities to districts and larger urban areas. This approach reflects a more inclusive understanding of sustainability potentials for large-scale building blocks that goes beyond traditional boundaries. Such systems encompass the aggregated energy impacts of multiple buildings whether physically proximate or connected via smart grid technologies that enable two-way energy and information flows. This paper comprehensively reviewed case studies on MBES that have achieved zero-energy, nearly-zero-energy, and positive-energy performance. The literature review, facilitated by a combination of database searches and snowball search techniques, has yielded 67 relevant case studies. The findings revealed diverse pathways towards achieving optimal renewable energy production depending on the location and the climate. Integration of renewable energy sources and energy storage systems is pivotal in achieving economies of scale, reducing operational costs, and enhancing resilience and reliability of energy supply at the neighbourhood scale. Total energy use and emissions reduction could be achieved by considering the architectural features of the building stocks. The study highlighted the need for adaptive strategies in MBES implementation to address challenges such as power grid overloads and the complexities of spatial arrangement, to meet current demands, while ensuring long-term energy resilience and sustainability in evolving urban landscapes. The limited adoption of MBES simulation software suggests a need for accessible tailored software. Future research should focus on developing advanced personalised energy management and control strategies, while continuously assessing emerging technologies for improving MBES performance. [ABSTRACT FROM AUTHOR]

A single-stage 4-step pressure-vacuum swing adsorption (PVSA) process, capable of CO 2 separation from the prepared flue gas, is experimentally studied on a fresh perspective of energy-efficiency analysis. The major contribution of thermodynamic carbon pump, which includes the minimum CO 2 separation work and the second-law efficiency, is to establish the relationship between energy consumption and separation difficulty. Adsorption/desorption cycles utilizing a fixed bed of an adsorbent material made of zeolite 13X are performed. Not only the recovery target, but also the second-law efficiency is considered as the main performance criteria in this paper. Thereby, the performance analysis of experimental apparatus is conducted over a range of process parameters, namely 10–20% CO 2 concentration, 1.0–3.0 sl/min flow rate, 10–30 s time duration of pressurization with feed, 80–120 s time duration of feed and 40–80 s time duration of purge. The results show that the specific energy consumption for the 4-step PVSA experiments is varied from 2719.31 kJ/kg to 9334.21 kJ/kg, the corresponding range of second-law efficiency calculated by thermodynamic carbon pump is 1.83–4.27%. The efficiency of vacuum pump affects the specific energy consumption of CO 2 capture process. The second-law efficiency in experimental studies of this paper is strongly dependent on the mechanical work performance of vacuum pump. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present an improved way of collection and compilation of data about solid biomass consumption in households in order to improve accuracy of official energy statistics data. The accurate, timely and reliable energy data significantly contribute to the consistency in national energy statistics, energy balance, as well as for many other obligatory reporting procedures which are requested and prescribed by national and international standards. When compiling energy statistics, statistics on renewables, particularly biomass consumption, it is often the most questionable as little or no available official data exists in the country. According to the international standards and definitions, solid biomass covers organic, non-fossil material of biological origin which may be used as fuel for heat production or electricity generation. In households, the most commonly used biomass are fuelwood and wood residues. In the process of compiling national energy statistics, national institutions responsible for official energy statistics usually estimate biomass consumption based on the reports on fuelwood cuts in state forests and official biomass production, although it is known that consumption is much higher. Over the past two decades, Energy Institute Hrvoje Požar worked intensively on the energy consumption data collection and particularly on the development of the tailored-made surveying methods for different final energy consumption sectors, particularly for the household sector. The similar methods were recommended to national statistics institutes in the countries in the region when providing technical assistance in developing energy statistics. This paper describes the survey results and methods applied for the determination of energy consumption in households and particularly biomass consumption in three selected countries: Croatia, Bosnia and Herzegovina and Macedonia, and recommendations for the further improvements. [ABSTRACT FROM AUTHOR]

• A comparison method between energy-only and energy and reserve model. • Higher revenue for flexible technologies was achieved for joint model. • The down reserve proved to be more required in high RES systems. • The study showed significant difference in operation between two models. The requirements for ancillary services in energy systems are growing as the amount of renewable energy sources such as solar and wind increases. On the other hand, the system can benefit from extra sources of flexibility thanks to the increased digitalization that enables successful integration of demand response and energy storage. The majority of recent energy system analysis research did not consider the regulation markets. As a result, these investigations preclude the ability to fully evaluate the advantages of energy storage and flexible cooling loads. With the method outlined in this paper, it is possible to compare the two strategies and assess the advantages of energy storage and flexible cooling loads for each strategy. In addition to the energy storage systems, the case study in this paper focuses on flexible cooling loads as a significant consumer in the system. According to the findings, the system's operating costs increased by 19.4% when reserve limitations were placed. Furthermore, the findings demonstrated that when flexible assets were permitted to participate in the reserve market, they generated significantly higher incomes. According to the findings, mechanisms that will allow energy storage and demand response to provide reserve capacities as well as the growth of reserve markets are both necessary. [ABSTRACT FROM AUTHOR]

[Display omitted] • A new method for EROI calculation by stocks/flows-funds/services. • Case study " green hydrogen " by water electrolysis EROI = 0.97. • Energy sustainability for Energy Carrier production technologies. • Strong sustainability vs. weak sustainability the N.G. Roegen approach. • Energy embedded evaluation in Net Energy Analysis procedure. Nowadays there is a considerable interest in studying the direct and indirect energies involved in products and services. This is particularly critical when novel energy resources are exploited by complex technological chains and to determine if they can indeed guarantee an useful energy societal supply. Unfortunately, there is no universally accepted procedure for doing this. The present paper aims to suggest a new procedure to evaluate the EROI of technologies producing energy carriers based on the stocks/flows-funds/services production model of N.G. Roegen. The suggested method can uniquely identify the energy flows involved in the technology consistent with biophysical and anthropological boundaries. This analytical formulation can be used either for single technologies or combination of them in series or parallel using different energy resources. Specific recommendations in the use of the Cumulative Energy Demand and Global Energy Requirements in the Net Energy Analysis, as well as in the evaluation of both for an electrical system are reported. The approach is here applied to the analysis of electrolytic H 2 production using electricity produced by a photovoltaic panel ("green hydrogen"). The resulting EROI = 0.97 means that the technology is not sustainable, requiring 3% energy from the anthropological sphere to support it. The paper is organized as follows: providing a narrative model for EROI evaluation consistent with anthropological and biophysical spheres; covering the definition of stocks/flows - funds/services model for EROI evaluation; analysing and suggesting uses of the model for energy technologies scoring and selection based on sustainability and presenting a numerical case study. [ABSTRACT FROM AUTHOR]

[Display omitted] • A new configuration of HVAC systems for an office as zero energy building. • This model is simulated in six major climate regions in ten cities of Iran. • The evaporating cooler integrated with the ground is used as the main cooling facility. • Cooling energy demand scale in comparison with other systems' energy tends to zero. • PV cells and ground heat pump generate electricity and heating, respectively. • The LCC value for this article model system is lower than the 50 %of value in comparison with usual systems. This paper presents a new configuration of heating and cooling systems for a net zero energy building (NZEB). In this paper, one design for Net Zero Energy Building(NZEB) systems is simulated, which can provide cooling and heating needs in a wide variety of climates. This current model benefits from direct evaporating cooling (DEC) which is coupled with the ground instead of the chiller in order to reduce the consumption of energy, water usage, and humidity of indoor air. The PV cells and heat pump that are connected to the ground generate electricity and heating energy, respectively in the building besides domestic hot water is provided by solar collectors. This model is simulated in ten cities of Iran as a multi climate country with six various major climates. The Life Cycle Cost (LCC)is calculated for all of these cities and the value is compared with the usual systems. The results show the possibility of an NZEB in various dry weather in Iran, furthermore the thermal comfort situation is confirmed. The cooling energy demand proportion to other energy usage tends to be zero. The LCC value will be able to reduce to 50% of the usual systems. [ABSTRACT FROM AUTHOR]

• Low-head high specific speed Kaplan turbine for small hydropower is presented. • Unique basic, cavitation and runaway experimental characteristics were determined. • Total energy drops in turbine volumes were calculated by means of CFD. • The results facilitate safe on-site selection of a low-head Kaplan turbine. • Cavitation first induces at leading edge and blade tip on the runner suction side. In an era of growing energy demand, it is necessary to reach for lower water potentials to be used by a hydro unit. Due to low damming, a hydro unit must be designed to allow the flow of as much water as possible with maximum efficiency. This ensures optimal use of hydropower and minimization of turbine size. Therefore, this paper presents the construction of a model Kaplan turbine (runner diameter of 300 mm) with a high specific speed, designed to work under ultra-low and low heads up to 3 m. Adjustable guide vanes and runner blades were designed by means of an inverse problem method using a two-dimensional axisymmetric model. In the case of the adjustable guide vane, two shapes have been designed. The first has a classical shape and the second has a non-classical shape. The influence of both guide vanes on the turbine operation was analysed using the CFD technique. As a result, the turbine with a non-classical shape blade has a higher hydraulic efficiency and the efficiency curve is flatter. As part of these calculations, many variants of turbine settings were analysed (192 cases), namely 4 angles of classical guide vanes, 4 angles of non-classical guide vanes, and 4 angles of runner as well as 2 angles of a conical draft tube and 3 rotational speeds. The energy losses occurring in the flow elements of the turbine and their mutual contribution are presented in this paper. Model experimental tests of the turbine were carried out on the test stand with a wide range of settings of the guide vanes (the tests used a guide vane with a non-classical shape), the runner and its rotational speed. The research is aimed at determining the basic parameters of efficiency, the effect of cavitation and the runaway speed. Cavitation and runaway characteristics as well as the results of the resistance torque (friction losses) and its share in the total moment are presented. As a result of design, analytical, and experimental works the low-head high specific speed model Kaplan turbine was obtained and diagnosed. The realization of large flows, combined with the high efficiency of the machine is always a difficult task. The paper briefly describes the shapes of the designed guide vanes and runner blade obtained by the inverse problem method. However, more emphasis has been focused on the presentation of model tests that are rare for this type of machine. Therefore, the measurement uncertainty, measuring devices and the course of the conducted basic performance, cavitation and runaway tests are described in detail. Additionally, for the selected cases, a visualization of the flow with forced cavitation in the runner during cavitation tests is also presented. [ABSTRACT FROM AUTHOR]