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Reducing carbon emissions is a crucial way to achieve sustainable development. Whether the digital economy helps or makes it harder to cut emissions is a matter of debate. This paper proposes a new digital economy index based on the entropy weight method. The two-way fixed effect panel model is used to analyze the data of 30 provinces in China from 2011 to 2021. The results suggest that (1) The digital economy can significantly reduce carbon emissions. (2) Improving energy efficiency and promoting energy structure transformation are two essential mechanisms for carbon reduction in the digital economy. (3) There is heterogeneity in the impact of the digital economy on carbon emissions. The digital economy significantly reduces carbon emissions from coal but does not significantly impact carbon emissions from other sources. Moreover, the emission reduction effect of the digital economy is related to regional energy endowment, intelligent manufacturing level, and industrial agglomeration level. This paper provides new empirical evidence for clarifying the relationship between the digital economy and carbon emissions and provides policy implications for promoting the realization of carbon neutrality goals. • The digital economy can significantly reduce carbon emissions. • Energy efficiency and energy structure are two essential mechanisms. • The emission reduction effects of the digital economy vary by region. • The effect is related to intelligent manufacturing and industrial agglomeration. [ABSTRACT FROM AUTHOR]

To identify the influence of digital transformation on energy consumption, this paper introduces digitalization and energy elements into the multi-sector energy efficiency analysis model. Furthermore, this paper empirically tests the influence of digital transformation on energy efficiency from the micro level. The results show that the digital transformation indeed improves the enterprises energy efficiency, in which enterprises with higher energy efficiency are more affected. The improvement effect of digital transformation on enterprise energy efficiency continues to increase over time. In comparison, digital transformation shows more effective improvement effect on energy efficiency in enterprises that substantive transformation priority, with same group and maturity stage. Mechanism analysis shows that digital transformation can improve the energy efficiency of enterprises by reducing costs, increasing income, improving production efficiency and promoting technological innovation. In addition, the digital inclusive finance, government subsidies, intellectual property protection and service industry opening show positive regulatory effects. This paper proposes that, with the goal of peak carbon dioxide emissions and carbon neutrality, enterprises should actively increase digital investment and strengthen digital management of energy utilization. [Display omitted] • Digital transformation indeed improves the enterprises energy efficiency. • The promotion effect of digital transformation increases over time. • Digital transformation drives efficiency improvement and technological innovation. • Digital transformation contributes to cost reduction and benefit increase. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative decision support system for improving ship energy efficiency. It combines an engine optimization model and an artificial neural network (ANN). Real-time data regarding the ship and engine performance is obtained along a specific ship navigation, and an engine optimization model is built using Ricardo Wave software. This model is validated with high accuracy. Ship-specific parameters are derived, and fuel consumption is estimated using ANN models with different structures. The study identifies the most suitable ANN model with 1 hidden layer and 5 neurons based on error metric evaluation where the 0.99697 R2, 0.00035 RMSE, and 0.06470 MAPE scores are calculated. This approach offers a cost-effective solution for shipping companies to monitor critical engine parameters in real-time without investing in sensors or data collection systems. Thus, it contributes to dealing with the problem of the scarcity of analyzable data in the maritime literature, which is one of the significant issues in the papers related to energy efficiency, machine learning, and deep learning. It is an innovative approach since the parameters that are related to real-time operations rather than considering only instruction book information are aggregated, and the produced data is analyzed by an intelligent tool. • A system is proposed to control ship energy efficiency level by combining an optimization model and a neural network • A simulation model is created in the Ricardo Wave tool and the engine model is validated by actual data. • The ship fuel consumption is estimated by an artificial neural network based on the derived input parameters. • The prediction process is evaluated by error metrics to determine its success. [ABSTRACT FROM AUTHOR]

As the link between cities, the high-speed train (HST) not only effectively enhances national and regional accessibility, but also induces much energy consumption. On the other hand, passengers have a higher requirement for riding comfort of HST than before. Considering the impacts of slope gradient on energy consumption and vertical carbody acceleration, this paper optimizes the scale factor of the damper controller depending on the running condition to juggle the energy efficiency and riding comfort when HST is across slopes. Firstly, the multibody dynamics simulation model of HST is established to evaluate the energy consumed by motion resistances and carbody vibrations. Then the Skyhook control strategy is applied to the secondary vertical damper of the vehicle model. The effects of vehicle speed, slope gradient, and scale factor of the Skyhook controller on energy saving and vertical carbody acceleration of HST are investigated. Based on the simulation results, the Gaussian process regression model is established to predict the vehicle performance and describe the bi-objective optimization problem. It is demonstrated that the optimized Skyhook control system can at most save energy consumed by motion resistances by 8.52 % or reduce vertical carbody acceleration by 37.14 % without sacrificing the other target. Finally, a comprehensive feasibility and economic analysis of the proposed control system is carried out to promote its practical implementation. • Establish co-simulation platform to apply Skyhook control strategy to vehicle damper. • Reveal effects of scale factor, speed, gradient on energy saving and riding comfort. • Build Gaussian process regression model to predict indices and optimize scale factor. • Proposed strategy can improve riding comfort and energy efficiency by 37.14 %, 8.52 %. [ABSTRACT FROM AUTHOR]

Energy efficiency is crucial for the sustainable operation of industrial and urban sectors. However, practicing engineers seldom have access to open-source tools that can readily evaluate and compare scenarios. In this work, a novel web-based tool called ROSMOSE is developed and proposed for analyzing the energy efficiency of industrial and urban systems and comparing potential process integration options. This optimization framework computes and graphically represents the minimum energy requirements, the pinch temperatures, and the Grand and integrated Carnot composite curves of process systems. Results are used to design utility systems that meet energy demands, while minimizing a specified objective function, such as total cost or environmental impacts. The Quarto environment, in which ROSMOSE is built upon, allows the integration of various open-source software and tools, such as database handling software, process modeling suites, and optimization solvers, along with interactive data visualization and reporting tools. This paper discusses the application of ROSMOSE for the energy integration and total site optimization of a dairy process consisting of milk treatment, and cream and cheese production to demonstrate the tool features. Other integration options, such as the use of heat pumps or solar panels, and the production of soft drinks or biogas as value-added byproducts, are also proposed and evaluated. As a result, from 75 % to 90 % in fuel savings and up to 80 % CO 2 emissions reduction in the dairy plant are identified by optimizing the utility systems integration. Moreover, complete electrification via heat pumps eliminates any fossil fuel needs and it results in 85 % energy savings and up to 96 % CO 2 emissions reduction. The activation of renewable electricity sources, such as solar power, made plausible this fully electrified scenario. Finally, optimized waste management strategies led to in-house fuel production and net export of biogas to the grid, but they also reduce cheese yield by prioritizing the biogas production from whey upgrading process. In this way, decision-makers have access to a clear performance comparison for a list of system configurations to draw informed trade-offs. A similar approach could be adopted to aid decision-making for the design and operation of other industrial and urban energy systems using ROSMOSE. [Display omitted] • ROSMOSE is an open-source energy integration, optimization and reporting tool. • Pinch analysis and other assessments of decarbonization strategies can be performed. • The process integration and waste valorization of a dairy plant is used as case study. • Above 75 % energy saving is achieved by process integration and optimal utility selection. • 96 % reduction in CO 2 emissions and on-site biogenic energy sources are identified. [ABSTRACT FROM AUTHOR]

This paper studies the viability of energy savings in electric motors by adjusting the voltage according to load in motors that operate under significant load variations during their work cycles. The laboratory test program used a 1.1 kW electric motor to compare its measured efficiency operating without voltage control with the load-based voltage control method results. A neural network was developed, and a time series generator was used to model the motor and estimate the results of applying the method in its useful life in the load behavior of three operating regimes. The results show an energy saving potential of 2 %–5.2 % using the load-based voltage control method in motors operating with a load factor of less than 40 % during the simulated motor life cycle for the three operating regimes. Also, the economic feasibility of implementing the load-based voltage control method was evaluated on three industrial electric motors. Results indicated potential annual savings between $1227 and USD 1,549, with a projected investment payback period of less than three and a half years. • The LVCM is a good solution to save energy in motors with low load factors. • The energy savings potential of the LVCM depends on the operating time at a low load factor. • The lower the load factor, the more energy savings with the LVCM. • The LVCM does not affect the mechanical drive of the electric motor. • Neural networks and time series allow the modeling of LVCM on life cycle motors. [ABSTRACT FROM AUTHOR]

Energy performance indices are widely used methods for determining and assessing the efficiency of buildings in operation. However, methodologies for indices that compare heat consumption among buildings and at higher temporal granularity than yearly are needed. This makes it possible for consumers to compare themselves to others to encourage them to improve their energy efficiency. For a district heating system, it also provides the district heating company with an overview of consumers' energy efficiency (and consumers' efficiency must be comparable). This is critical due to the interconnectedness of district heating systems, as consumers can indirectly have negative impacts on each other's operations. Having an overview of the efficiency of consumers can provide useful information for the district heating companies to detect unusual consumption and possible faults. This paper therefore has created a framework for the comparison of heat consumption among buildings, by taking into account various contextualities to make comparisons possible. The framework has been tested on a case study, and its capabilities are showcased. • Leveraging building metadata to allow energy consumption comparison among buildings. • Creation of heating consumption performance indexes for use by end-consumers. • Enabling of higher temporal resolution performance indexes increasing usability. • Fault detection based on performance indexes. • Showcasing of methodology on real consumption data from a suburb in Denmark. [ABSTRACT FROM AUTHOR]

The average electricity consumption per capita in China still has significant room for growth. Under the current rigid residential electricity pricing, it is very important to study how factors other than price can promote electricity conservation among residents. This paper uses micro-survey data of 2018 and 2020 to analyze energy efficiency and the rebound effect through a stochastic energy demand frontier model, as well as to examine the role of news propaganda in this context. The research conclusions are as follows: (1) News propaganda promoting electricity saving can weaken the rebound effect of electricity use, which can lead to better electricity savings. (2) The energy efficiency of residential electricity has improved significantly compared to previous years, and the rebound effect has decreased. (3) Electricity prices have a negative impact on electricity consumption, while income, household size, home area, and extreme temperatures have a positive impact. Based on these conclusions, we propose policy recommendations to address the current inflexibility in residential electricity pricing and to improve the efficiency of electricity use among residents. • News propaganda promoting electricity saving can weaken the rebound effect. • The energy efficiency of residential electricity has improved. • The rebound effect of residential electricity has decreased. • News propaganda can be a complement to the inflexibility of pricing policy. [ABSTRACT FROM AUTHOR]

Using the unique micro-data of industrial enterprises' Nitrogen oxides (NOx) and Sulfur oxides (SOx) emissions covering 58,725 enterprise-year observations, this paper investigates how digitalization affect energy efficiency. The empirical results show that regional digitalization can significantly promote the improvement of energy efficiency of industrial enterprises. Specifically, the result of PSM-DID method indicates that the impact of digitalization on energy efficiency is significantly enhanced by the "National innovative pilot cities" policy, while the dynamic result validates the continuity of industrial enterprises' energy efficiency. Moreover, regional digitalization has superior impact on enterprises within eastern region enterprises, the manufacturing sector, and with elevated liquidity and profitability levels. Finally, moderating effect suggests that technological innovation expand the positive impact of digitalization on enterprises' energy efficiency. This study confirms regional digitalization can promote the energy efficiency of Chinese industrial enterprises, providing the policy suggestions to the energy transition in China. • Measure the regional digitalization level of Prefecture-level city and the energy efficiency at Industrial enterprise-level. • Findings demonstrated that digitalization increases energy efficiency. • The impact of digitalization on energy efficiency can be enhanced by the "National innovative pilot cities" policy. • Technological innovation expands the positive impact of digitalization on enterprises' energy efficiency. [ABSTRACT FROM AUTHOR]

Against the background of global warming, the low-carbon energy transition (LCET) has become one of the top concerns of governments around the world. Artificial intelligence (AI) is serving an increasingly relevant role in the energy sector by facilitating the development of cleaner energy. Thus, based on the panel data of 44 countries from 2000 to 2022, this study employs the Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) methods to explore the impact of AI technology innovation on LCET. Moreover, we explore the moderating and spatial spillover effects between AI technology innovation and LCET. The main results show that: (1) AI technology innovation significantly promotes LCET. A 1 % increase in the AI technology innovation index causes a 0.176 % increase in the level of LCET using the AMG method, and a 0.198 % increase using the CCEMG method. (2) Financial incentives and energy efficiency effectively amplify the positive influence of AI technology innovation on LCET. (3) AI technology innovation generates discernible spillover effects on LCET through bilateral trade influence, particularly in countries with closer "trade distances." This study recommends that countries adequately strengthen AI technology resources to realize new situations for the synergistic development of technology and green energy. [Display omitted] • This paper explores the impact of AI technological innovation on low-carbon energy transition (LCET) in 44 countries. • The characteristics of AI technological innovation are assessed. • AI technological innovation significantly promotes LCET. • Financial incentives and energy efficiency have positive moderating effects. • The spatial spillover effect of AI technological innovation on LCET is assessed. [ABSTRACT FROM AUTHOR]

Paper presents a comparison between a traditional district heating system with conventional boilers as a source of heat and electricity purchases from power utilities and a low temperature DH system incorporating the CHP with organic Rankine Cycle providing electricity and local heat pump raising the temperature of the DH fluid to the required temperature in the dwelling, meaning that both heat and electricity are produced within the system. Additionally, such "island" system may feature or not the heat pump. Comparisons are made based on the results obtained using a developed simple analytical model enabling calculations of the efficiency of respective systems. The analyses have a general character and can be used in studies of complex networks however presented in the paper simple examples show merely the fundamental capabilities of the developed tool. The objective of the heat pump in the system is to increase temperature of hot water to the required level locally at the dwelling and provide the heating in such way, contrary to the traditional system, where water heating is considered by the use of electric heaters to increase parameters of water for central heating purposes and preparation of utility hot water. Presence of the heat pump in the system allows for significantly lower temperatures of distributed in the network heat carrier. • Comparison between a traditional DH with conventional boilers and a LTDH system with ORC CHP and local heat pump. • Heat pump to locally raise temperature to the required values. • Simple analytical model enabling calculations of the efficiency of respective systems. • Heat pump in the system allows for significantly lower temperatures of water in DH. [ABSTRACT FROM AUTHOR]

The regenerator plays a crucial role in determining the energy efficiency of green liquid desiccant air-conditioning systems. This paper presents a novel air gap membrane distillation regenerator featuring heat recovery and portable water production. Based on a validated numerical model, performance evaluation of the regenerator combined with an external heat exchanger is conducted in terms of regeneration capacity (RC) and energy consumption (Q in). The comparison of flow patterns demonstrates that the counter-flow has a slightly higher RC , while the parallel-flow has a significantly lower Q in and is therefore preferable from the perspective of COP. The effects of key parameters including feed and coolant desiccant inlet temperatures (T f,in & T c,in), mass flow rate (m dil), membrane length (L), air gap thickness (δ ag), desiccant concentration (X dil) and solution heat exchanger effectiveness (ε she) on the performance are investigated. The results show that T f,in is the dominant factor on performance compared to T c,in and m dil , and increasing L leads to a marked growth in both RC and COP regardless of the raised Q in. Additionally, it is found that narrowing the air gap from 3 mm to 1 mm can improve RC and COP by 69.9 % and 50.1 % respectively. As for ε she , it has no influence on RC but remarkable impacts on Q in and COP. Moreover, the heat recovery by the coolant channel is proved to save nearly 8 % of energy input under the involved conditions. Finally, the NSGA-Ⅱ based multi-objective optimization is performed to obtain the Pareto front for maximizing RC and minimizing Q in. And the optimal solution through TOPSIS decision-making offers a RC = 975.8 g/h and a Q in = 1938 W. The findings provide a basis for design and application of the novel regenerator. • A novel air gap membrane distillation liquid desiccant regenerator is investigated. • Parallel-flow pattern is superior to counter-flow pattern in terms of energy efficiency. • Heat recovery by the regenerator can achieve about 8 % energy savings. • Effects of various design and operation parameters on the performance are explored. • Trade-off between regeneration capacity and energy consumption is realized by NSGA-Ⅱ. [ABSTRACT FROM AUTHOR]

Industry poses one of the biggest challenges in the renewable energy transition. In this paper, fossil fuels in the European industrial sector are replaced by renewable energy using a novel tool, IndustryPLAN, a planning tool for the assessment of national industrial sectors. In a bottom-up approach, each industry sub-sector is addressed with energy efficiency and fossil fuel replacement measures based on best available and innovative technologies, and in a top-down approach, the fuel and electricity consumption per country is analysed and decarbonised. The results indicate that: 1. Known technologies can decarbonise most of the industrial sector; 2. Costs and efficiencies are improved by energy savings and electrification; 3. Limiting bioenergy consumption is a critical challenge, emphasising the key role of energy savings and electrification, and the alternative of using hydrogen or hydrogen-based electrofuels will make the transition more expensive and induce energy losses. A full transition to renewable energy and a decarbonised industry sector may be possible before 2050, however, this requires that all investments are sustainable from 2030 onwards and that grid electricity is fully decarbonised. This paper presents several pathways toward 100% renewable energy supply in the European industrial sector and discusses the implications of the outlined scenarios. • Four tangible 100% renewable energy scenarios for industry in EU27 + UK are established. • 100% renewable energy in industry is feasible before 2050. • Energy efficiency improvements are essential to limit biomass consumption. • Industry energy transition needs to be prioritised in short- and long-term planning. [ABSTRACT FROM AUTHOR]

The landscape of Demand-Side Energy Management (DSM) research is rapidly evolving, shaped by technological innovations and policy developments. This paper presents an exhaustive bibliometric analysis and methodological framework to explore the research trends within the DSM domain. By synthesizing data from Scopus and OpenAlex, we compile a comprehensive dataset of DSM publications that serve as the basis for our analysis. Through rigorous data acquisition and cleaning, we ensure the reliability and relevance of our dataset. We employ state-of-the-art Large Language Models (LLMs) and topic modeling techniques, including GPT and BERTopic, to perform semantic analysis and uncover thematic structures within the literature. Statistical analysis of the literature dataset reveals a steady increase in DSM publications, with significant contributions from prestigious journals and institutions worldwide. We observe that articles are the predominant publication type, while reviews often cite more references and receive higher citation counts. The distribution of publications over time indicates a growing interest in DSM, particularly since 2014. Geographical mapping of institutions highlights key regions contributing to DSM research, with notable outputs from Europe, North America, and East Asia. Coupled with citation network analysis, our approach reveals the influential works and emerging trends that define the scientific progression of DSM research. Our unsupervised topic modeling, powered by BERTopic, clusters the publications into distinct themes, while our advanced visualization techniques using UMAP and t-SNE provide insights into the semantic space of DSM literature. The resulting thematic classification is presented in a hierarchical structure, offering a comprehensive understanding of the field's focus areas. Our citation network analysis, utilizing force-directed graph computation and edge-bundling algorithms, maps the interconnectivity and impact of research contributions, providing a dynamic view of the field's evolution. This study not only charts the landscape of DSM research but also offers a methodological blueprint for future bibliometric analyses. The insights gained from this multi-faceted exploration serve as a valuable resource for researchers, policymakers, and industry practitioners looking to navigate the complexities of DSM and contribute to its scientific advancement. • Reviews energy demand-side management literature using bibliometric methods. • Uses citation network to reveal research clusters and interdisciplinary connections. • Uses GPT embedding and BERTopic model to cluster literature into ten themes. • Develops software tool for bibliometric analysis. [ABSTRACT FROM AUTHOR]

With the facilitation of agricultural modernization, China's agricultural energy consumption continues to rise. This paper empirically tests the agricultural energy rebound effect and its influencing factors in China during 1999–2020. It is believed that the improvement of energy efficiency has not led to the expected energy-saving effect in agriculture due to the "Jevons paradox" of energy efficiency and energy consumption. The average energy efficiency of China's agricultural energy consumption was 0.446, and the average energy rebound effect was 68.9 %. The level of agricultural mechanization, the effective irrigated area of farmland and agricultural investment have a positive impact on the rebound effect of agricultural energy, and the direct effects are 0.062, 0.008 and 0.064, respectively, while agricultural labor force and energy price have a negative impact on the rebound effect of agricultural energy. In particular, technology spillover and scale spillover led by agricultural technology progress have strong negative space spillover effect. As it is argued, 1 % of agricultural technology progress can reduce 3.5 % of agricultural energy rebound effect in surrounding areas. In order to reduce the energy rebound effect, it is suggested to increase the subsidies to agricultural labors and rationally formulate regional differentiated energy regulation policies. • The internal mechanism of rebound effect is expounded from the view of producers and consumers. • The average energy efficiency of China's agricultural energy consumption was 68.9 % during 1999–2020. • The determinants of the agricultural energy rebound effect were further discussed by considering the spatial spillover effect. [ABSTRACT FROM AUTHOR]

—This paper proposes two real-time energy-oriented driving strategies to minimize the energy consumption for electric vehicles on highways with varying slopes. First, a novel strategy, called normalized-energy consumption minimization strategy (NCMS), adopts a designed kinetic energy conversion factor to convert the vehicle kinetic energy change into the equivalent battery energy consumption. By minimizing the total normalized energy consumption, the energy-orientated vehicle control sequence is calculated. In addition, a logic car-following algorithm is developed to enhance NCMS for avoiding collisions with the potential preceding vehicle on the journey. Second, an improved model predictive control (MPC) is developed with a hierarchical framework, which achieves a balance between optimization and computational efficiency. In the upper level, a global, coarse-grained, iterative dynamic programming is employed to penalize the MPC terminal state, while the lower level performs online rolling optimization of the vehicle within a moderate time step. Thirdly, the performance of the proposed driving strategies is verified through a traffic simulation to evaluate the energy efficiency improvement and processor computation time compared to dynamic programming and constant speed strategy. Finally, a vehicle-in-the-loop test is carried out to validate the feasibility of the proposed two novel driving strategies. • A normalized energy consumption model is presented, combining two energy usage. • A novel eco-driving strategy is developed based on the proposed energy consumption. • The algorithm suits both free traffic and car-following scenarios with safety. • The characteristics of the four eco-driving strategies are compared. • The proposed strategy is verified by both simulation and vehicle-in-the-loop tests. [ABSTRACT FROM AUTHOR]

This paper delves into the potential impact of a changing climate on the energy performance of European buildings. Research aims to provide a comprehensive evaluation of current energy requirements focusing on the envelope, considering existing regulations in national policies. Energy simulations are conducted at 94 locations across the European Union to cover the climatic variability and Koppen climate classification. The research analyzes future climate scenarios for the years 2030, 2050, and 2070, using three different Representative Concentration Pathways (RCP 2.6, 4.5, 8.5). According to a comprehensive analysis of heating, cooling, and overall energy performance, climate plays a significant role in buildings' energy balance. In moderately cool climate countries, the demand for air conditioning is projected to decrease in the years ahead. Conversely, in countries with a warm climate, there is a projected increase in the overall energy demand. Consequently, a revision of current energy regulations should be a priority. Providing insights into the relation between building design, energy efficiency, and climate change, the research identifies policy adjustments to ensure buildings can effectively respond to changing climatic conditions. A holistic and dynamic approach can support building design accounting for long-term impacts of climate change to create resilient and energy-efficient structures. • National building energy regulations of European Member States do not tackle climate change. • Over next decades, a decrease in heating demand is forecasted across all climate zones. • There is potential for a future considerable increase of cooling demand in Europe. • A reduction in total building energy demand in colder climates and an increase in warmer climates can be expected. • Revise national energy regulations, especially in warmer zones, to curb the expected rise in Europe's total energy demand. [ABSTRACT FROM AUTHOR]

In this paper, a methanol production process with high thermodynamic efficiency and a low production cost is presented. The proposed process is based on steam methane reforming, in which carbon dioxide (CO 2) captured from a power plant flue gas is employed to improve the stoichiometric number, methanol efficiency, and carbon efficiency and increase CO 2 conversion. In addition to the sensitivity analysis, comprehensive technical, economic, and environmental analyses are performed. Furthermore, the obtained results of this paper are compared to those of previous studies. A parametric study showed that the optimum steam-to-methane ratio is 3.75, and the optimum flow rate for CO 2 utilization is 140 kmol/h. From the economic point of view, it is demonstrated that the total annual cost is 11,799,484 USD, and the total production cost rate is 0.1 $/kg. The environmental analysis showed that the total net CO 2 emission in this process is 6580.64 kg/h, and for producing 1 kg of methanol, 0.41 kg of CO 2 is emitted. • Proposal of a methanol production cycle based on steam-methane reforming. • Improving stoichiometric number, methanol efficiency, carbon efficiency, and CO 2 conversion using the proposed system. • According to the results, the optimum value of the steam to methane is obtained 3.75. • The total annual cost and production cost rate are estimated 1,179,948 $ and 0.1 $/kg. [ABSTRACT FROM AUTHOR]

The paper evaluates the potential energy efficiency benefits for dynamic sliding exterior shades suitable for windows of both new and existing buildings. In particular, the analysis outlined in the paper summarizes the energy performance of dynamic sliding shades when applied to windows for apartment units located in various US climates. A series of sensitivity analyses is performed using a detailed whole-building simulation coupled with modeling techniques of dynamic envelope systems to determine the optimal positions for the dynamic sliding shades to minimize the annual demand for US housing units. Several operation strategies are evaluated using continuous and stepped settings of the positions for the dynamic sliding shades using monthly, daily, and hourly adjustment frequencies. The results of the analyses indicate that the dynamic shades have significant energy efficiency potential for all US climates and design conditions with annual savings in HVAC energy end-use of over 50% especially in hot and mild climates. The performance of the dynamic shades is even higher for large and single-pane windows indicating that these systems can serve as retrofit alternatives to window replacements. • New and low-cost dynamic and insulated shading systems are introduced. • Energy benefits of the dynamic shades are assessed for residential buildings. • Optimal controls for the dynamic shades are determined for US climates. • Dynamic shades achieve over 50% reduction in heating and cooling energy use. [ABSTRACT FROM AUTHOR]

Due to the high dehumidification performance realized by removing adsorption heat by inner cooing, desiccant coated heat exchanger (DCHE) has been proposed and widely studied. The heat pump is usually used as the cooling and heat sources of the dehumidification system composed of DCHE because the cooling and heat capacity could be provided by the heat pump at the same time. Moreover, considering the advantage of low-grade thermal energy utilization, solar thermal energy can be used to further enhance the regeneration of DCHE to improve dehumidification performance and energy efficiency. In this paper, the solar-enhanced fresh air dehumidification system using DCHE driven by heat pump was proposed and a series of experiments were conducted under typical Shanghai summer high humidity conditions. The typical moisture removal of the system can be increased by about 15% to 10.14 g/kgDA and the COP could be further increased by over 25% to 5.39. In addition, the influence of different regeneration temperatures enhanced by solar thermal energy on the system has also been studied. Considering the dehumidification performance improvement and energy utilization efficiency, the optimal regeneration temperature is between 60 °C and 65 °C for the system proposed in this paper. • Moisture removal and COP can be increased by 6%–28% by solar enhanced. • Performance enhanced is more obvious when regeneration temperature is below 65 °C. • Solar enhanced dehumidification 1.43 (g·kgDA−1)/kW and 1.12 kg/kWh can be achieved. • Higher efficiency solar collectors will achieve higher solar enhanced performance. [ABSTRACT FROM AUTHOR]

Energy efficiency is a critical issue in data centre management, which is the foundation for cloud computing. The VM placement has a considerable impact on a data centre's energy efficiency and resource utilisation. The assignment of VMs to PMs is an NP-hard problem without an easy way to find an optimal solution, particularly in large-scale data centres. In this study, the VM placement problem is formulated as a constrained optimisation problem. The Genetic Algorithm (GA) is a suitable method for solving this problem in terms of the quality of the solution. However, GA is time-consuming to obtain an optimal solution in the large scale optimisation problem. Therefore, this paper focuses on accelerated GA for energy-efficient VM placement. As the most time-consuming element of the GA is the calculation of its fitness function, this paper simplifies this calculation through a new fitness function in GA. Simulation results of small-, medium-, and large-scale data centres demonstrate that our accelerated GA is faster than the standard GA and gives better quality of solution than the First Fit Decreasing (FFD) algorithm, respectively. The findings of our GA with the new fitness function reveal an 8% energy saving for our GA compared to FFD and a 66% reduction in our GA execution time compared to the standard GA with standard energy formula as a fitness function. The number of generations in our GA is reduced by about 50% in comparison with the standard GA. Moreover, we started with 3000 PMs in the large-scale dataset, and only 1086 PMs were actually used after running our GA. Therefore, we may switch off far more PMs for energy savings from our GA results than those from the standard GA. • Virtual machine placement problem formulated as a constrained optimisation problem. •It focuses on accelerated genetic algorithm for virtual machine placement. •Our algorithm can minimise residual resources using Taylor extension. •Our solution quality is better than FFD and standard genetic algorithm. •It reduces execution time and energy in large scale data centres. [ABSTRACT FROM AUTHOR]

Energy efficiency investments are essential to transition to a carbon-neutral economy. Nevertheless, despite being financially viable, many energy efficiency investment opportunities do not materialise. The existing literature attributes this situation to financial and non-financial factors. Research suggests that many firms focus only on direct energy savings and neglect non-energy benefits that include increased labour productivity. Up to date, due to the lack of high-quality data, few studies attempted to quantify how the energy efficiency investments affect firm-level outcomes other than the reductions in energy consumption. This paper overcomes this barrier by using novel data from a firm-level survey conducted by the European Investment Bank. The survey covers more than 15,000 firms in 27 European Union member states and the United Kingdom during 2018–2019. This study investigates the relationship between the energy efficiency investments and the labour productivity of the European firms and uses instrumental variables methodology to account for potential endogeneity. The results show a positive and causal relationship between energy efficiency investments and labour productivity. The findings of the paper suggest that firms can benefit much more from the energy efficiency investment than what is often assumed, and highlight a need for government policies that would increase firms' awareness of the non-energy benefits. • This paper investigates the link between energy efficiency investments and the labour productivity. • We apply IV models to 15,000 firms in 28 European countries during 2018–2019. • We find positive causal relationship between energy efficiency investments and productivity. • Governments should implement policies to increase firms' awareness of the non-energy benefits. [ABSTRACT FROM AUTHOR]

Thermal grids will play a key role in the development of local energy communities and the achievement of 100% renewable societies. Such systems allow excess heat produced by distributed producers through renewable energy sources (also referred to as "thermal prosumers") to be shared among other consumers characterized by high heat demand or who still depend on fossil fuels. However, to achieve more reliable results when performing energy analyses, it is of utmost importance to develop models of prosumers' substations, where technical details (e.g., type of connections, heat exchangers, valves, etc.) and controllers are accounted for. Starting from the layout of a bidirectional substation for a thermal energy network proposed in the literature, this paper proposes a dynamic model that replicates the experimental setup in the TRNSYS environment. Validation results show a good matching between simulation and experiments in terms of dynamic behavior and energy balance. To show the capabilities of the proposed model, a prosumer with heat available from 205 m2 solar thermal collectors is considered as a case study. The analysis is performed by assuming two locations characterized by different irradiation values, i.e., Palermo (Italy) and Berlin (Germany). The results show that exchanging the excess heat produced on-site with a heating network allows the solar collectors to reach peak heat production, which is 130 kW and 110 kW for Palermo and Berlin, respectively. The surplus heat sold to the network is equal to 66% and 29% of the total energy exchange within the substation for Palermo and Berlin, respectively. Conversely, the self-consumption of the produced heat accounts for 21.2% and 30.6%, respectively. The model prospectively represents a valuable tool to develop feasibility studies in Thermal Energy Communities and assess the potential of innovative energy- and cost-effective operation strategies. • A model of a thermal prosumer substation exchanging with a District Heating Network (DHN) was created in TRNSYS • The virtual model was validated through experimental data by showing a good matching between simulation and experiments • To show the capabilities of the model, a prosumer equipped with 205 m2 solar thermal collectors is considered as a case study • Results showed that the prosumer substation allowed for optimal exploitation of the heat produced by the solar collectors • The proposed model represents a viable tool to perform analyses applied to renewable energy systems in prosumers networks [ABSTRACT FROM AUTHOR]

Multistage centrifugal pumps are widely used, and improving their efficiency is an indispensable part of energy conservation. A multi-objective optimization method combining experimental design, surrogate model, and optimization algorithm is proposed to re-design impellers and diffusers for improving pump performance. In the paper, nine variables were selected by the Plackett–Burman design with the head and minimum efficiency index (MEI) as the optimization objectives. The Gaussian process regression (GPR) was used to establish the surrogate model, and multi-objective optimization of the impeller and diffuser was carried out by non-dominated sorting genetic algorithm II (NSGA-II). The optimization results show that head and efficiency at the designed point 1.0 Q d increased by 8.8% and 2.8% respectively, and C MEI decreased by 1.34%. Meanwhile, the energy loss and flow characteristics of the original and optimization models were analyzed with the entropy production theory. Compared with the original model, the energy loss was reduced, and the flow in the interaction area between the impeller and diffuser becomes more stable for the optimized model. Moreover, the influencing mechanism of the pump geometrical parameters on the hydraulic performance and flow characteristics were discussed and analyzed. • A PB-GRP-GA multi-objective optimization method is proposed. • Internal energy losses were identified by Entropy Production Rate. • Influence mechanism of geometry on performance was revealed. • Higher MEI of pump model was achieved and verified by experiments. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to propose the blowdown heat recovery system using a steam dryer. A flash tank is used to reduce blowdown water pressure and generate flash steam. Flash steam is supplied to the steam dryer to decrease fuel moisture content. Exhaust vapor vented from the steam dryer is also used to increase air temperature in an air heater. Furthermore, due to decreased fuel moisture content and increased air temperature, the exhaust flue gas temperature may be decreased by increasing the air heater surface area in the boiler. This method of blowdown heat recovery has never been proposed before. Therefore, it may be considered as knowledge gap that is worth an investigation. The use of blowdown heat for steam drying is compared with the use of blowdown heat for feed water heating. Simulation results show that using blowdown heat for steam drying results in a significantly larger net power output. Furthermore, the integration of this heat recovery system is economically feasible. • An alternative blowdown heat recovery system using steam dryer is presented. • Dryer exhaust is used to increase air temperature in air preheater. • Additional air heater area is installed to lower exhaust flue gas temperature. • The proposed system results in larger power output than the conventional system. [ABSTRACT FROM AUTHOR]

Environmental degradation has become one of the major challenges facing the global community. This paper aims to explore the more effective options to combat environmental degradation by investigating the linearity and nonlinearity (trade openness set as a threshold variable) of energy efficiency, natural gas, renewable energy and ecological footprint. To this end, linear and non-linear panel models were constructed using panel data from 60 countries. The results of the linear analysis show that improving energy efficiency, and increasing the consumption of natural gas and renewable energy are conducive to inhibiting environmental degradation. Energy efficiency has the most significant negative correlation with ecological footprint, followed by renewable energy, and then natural gas, implying that improving energy efficiency and developing renewable energy is a more effective strategy to combat environmental degradation. The results of the nonlinear analysis show that there are threshold effects of trade openness between energy efficiency and ecological footprint, and between renewable energy and ecological footprint. The negative impact of both renewable energy and energy efficiency on the ecological footprint increases when trade openness exceeds the threshold. This suggests that, in terms of curbing environmental degradation, enhancing trade openness may further increase the negative impacts of energy efficiency and renewable energy on ecological footprint. At the same time, this confirms the positive role of trade openness in environmental protection. [Display omitted] • Exploring more effective option to combat environmental degradation. • Energy efficiency, renewable energy, natural gas can reduce ecological footprint. • Trade openness help energy efficiency, renewables lower ecological footprint. • The most effective strategy is energy efficiency, followed by renewables and natural gas. [ABSTRACT FROM AUTHOR]

Current oceanic hydrate research mainly focuses on its exploitation, but the subsequent storage and transportation of recovered gas is also necessary. To accelerate its commercial application and clarify the potential of liquefaction after hydrate exploitation, a rigorous simulation modelling was firstly conducted on the depressurization exploitation of hydrate coupled with recovered gas liquefaction in this paper. The energy performance was evaluated by energy consumption and efficiency analysis. The energy efficiency of the gas and liquid production process, liquefaction process, and the key influence factors of the whole process were studied separately. Results show that the energy efficiency ratio for depressurization exploitation reaches between 4.9 and 19.4, while that for the whole system of hydrate exploitation and liquefaction is only between 1.3 and 2.7 considering recovered gas combustion for power generation. The energy efficiency ratio of the whole system increases to between 2.6 and 4.3 powered by offshore wind farm. The largest energy efficiency reduction is up to 77.8% after recovered gas liquefaction compared with exploitation process. Therefore the storage process with lower energy consumption should be prioritized or the energy consumption should be optimized for the storage and transportation process after hydrate exploitation. [Display omitted] • A coupled system of natural gas hydrate exploitation and recovered gas liquefaction is proposed. • Rigorous process modelling is established and key influence factors are investigated. • Energy supply for the coupled system driven by ocean wind power is analyzed. • Exergy analysis results show energy efficiency ratio is 2.6–4.3. [ABSTRACT FROM AUTHOR]

This paper conducts a systematic study to address the problems of high flow loss and low energy efficiency of centrifugal pumps caused by the development of secondary flow within the impeller. Based on the forces balance in the direction perpendicular to the streamline, theoretical calculations are drawn to redesign blade thickness for a 5-blade centrifugal impeller to suppress the secondary flow. The correlations between the development of internal secondary flow within the impeller and energy efficiency of centrifugal pump under full flow rate conditions are illustrated by numerical simulations validated by experimental tests. Secondary flow coefficient and entropy production rate (EPR) are introduced and extracted to quantitative analysis the secondary flow level and energy loss inside the impeller. Results indicate that the blade redesign methods proposed here can efficiently inhibit the development of secondary flow and improve the energy efficiency. Moreover, the secondary flow coefficient introduced in this paper can quantitatively reflect the intensity of secondary flow under various flow rates of different impellers. Combining with the entropy production analysis of impeller, the consistent change trend of total secondary flow coefficient and entropy production reveals that the improvement of pump energy efficiency benefits from the reduction of turbulence EPR which results from the suppression of internal secondary flow. • Theoretical calculations of blade thickness for low specific speed centrifugal pump. • Blade redesign based on secondary flow suppression to improve energy efficiency. • Quantitative analysis of secondary flow and energy losses in the impeller. • Improvement of energy efficiency attributes to the reduction of turbulence EPR. [ABSTRACT FROM AUTHOR]

To reduce the conventional energy utilization in the pulp and paper mill, exploitation of renewable energy may provide a significant energy saving mostly in energy intensive subunits such as Multiple Stage Evaporator (MSE). MSE is used to concentrate the weak black liquor, a reach source of bio energy. Hence, this work explores the performance analysis of MSE with various proposed Energy Reduction Schemes (ERSs): Thermo-Vapor Compressor, Steam Split, Feed Split, Feed Preheater, and Flash Tanks. This analysis has been intended to develop the steady-state nonlinear energy models for proposed ERSs integrated MSE that translated it into a single objective unconstraint nonlinear optimization problem. Further, different optimization approaches (nonlinear programing and metaheuristics) have been employed to search the optimum process parameters and hence, maximize the energy efficiency. Moreover, to utilize the waste heat of condensate, feed, and product, flash tanks have been integrated with MSE which further improves the energy efficiency by 3.9% and 83% than that of base case model. Finally, the LFR solar field has been integrated to reduce the load of conventional energy utilization and ensures the self-sustainability of the paper mill by supplying the required amount of heat (3,399 kW) for the proposed hybrid MSE configuration. [Display omitted] • Incorporation of different ERSs and TVC with Multiple Stage Evaporator. • Implementation of optimization approaches to maximize the energy efficiency. • Waste heat reutilization by using flash tanks. • Integration of LFR solar field to reduce conventional fuel utilization. • Validation of result by comparing with other reported literatures. [ABSTRACT FROM AUTHOR]

Based on macro and micro matched data, this paper uses a fixed effects model, subsamples regression and the instrumental variable method to analyze the degree to which Internet development influences energy efficiency, the mechanism for that influence, and the spillover effect of Internet development. The findings show that for every 1 % increase in the Internet development index, the energy efficiency of firms increases by approximately 0.38 %. Robustness analysis and endogeneity analysis also verify that Internet development is conducive to improving the energy efficiency of firms. The internal mechanism analysis shows that Internet development can improve the energy efficiency of Chinese firms and realize an energy-saving effect by correcting the misallocation of resources and promoting technological innovation. In addition, this paper finds that for every 1 % increase in the Internet development index in other cities and leading cities in the province, the energy efficiency of local firms increases by approximately 0.10 % and 0.026 %, respectively, which supports the spillover effect of Internet development in China. The findings of the paper can help promote the deep integration of the Internet and manufacturing technology in China, facilitating manufacturing industry development in an intelligent and energy-saving direction. • The impact and mechanism of Internet on the energy efficiency is analysed. • The spillover effect of Internet development is explored. • Internet development is conducive to improving the energy efficiency in China. • Misallocation correction and innovation are internal mechanisms of Internet. • Energy efficiency of local firms can be promoted by Internet in other cities. [ABSTRACT FROM AUTHOR]

The deployment of electric vehicles (EVs) is rapidly progressing worldwide, and energy efficiency is an important indicator for both the economy and the environment. It is necessary to verify whether EVs are more energy efficient than internal combustion engine (ICE) vehicles. However, studies have yet to evaluate the energy efficiency of EVs using the data envelopment analysis (DEA) approach. To fill this research gap, this paper evaluated the energy efficiency of EVs for road passenger transportation using a slacks-based measure (SBM) approach in six European countries from 2012 to 2018. EVs have been separated from the entire transport sector and compared to ICE vehicles. In the case of EVs that use electricity as fuel, the primary energy supply must be used as energy input to reflect conversion loss during power generation. The primary energy supply was calculated by applying the power generation efficiency of each country for use as an energy input to reflect conversion loss. EVs were more energy efficient than ICE vehicles in four out of six countries but less energy efficient in two countries. Based on the measured slack results, the potential energy savings were quantified, and the main factors in reducing energy efficiency were identified. • The energy efficiency of EVs for road passenger transportation was analyzed. • A SBM model based on DEA was used for this analysis for the first time. • Primary energy supply was used as an input to reflect the energy conversion loss. • EVs were more efficient than ICE vehicles in Belgium, Germany, Norway, and the UK. • Large labor force (Greece) and energy consumption (Italy) led to low EV efficiency. [ABSTRACT FROM AUTHOR]

Optimal design of building envelopes/HVAC systems and free cooling strategies are today necessary to reduce energy, economic and environmental impact of telecommunication, electricity distribution, or electric transportations infrastructures. To this aim, designers and operators require advanced techniques and tools. Target of this paper is to present the development of a simulation model for assessing and optimizing cooling performance of new/existing infrastructures to be designed/refurbished from the energy point of view. The model is implemented in a computer tool to assess the related potential benefits of different energy saving technologies/strategies and optimize different objective functions. By the presented approach new design and operating criteria are developed by varying all the occurring boundary conditions (weather, temperature limitations, electricity tariffs, etc.). To show the capability and suitability of the proposed approach, a case study concerning the equipment cooling of a railway substation is developed. The analysis is conducted for different Italian climates, obtaining remarkable energy savings. Specifically, by optimizing free cooling operation and thermal insulation the cooling energy consumption can be decreased up to 80% and 10%, respectively. By an energy refurbishment of all the Italian railway substations an annual electricity cost reduction due to equipment conditioning of about 0.5 M€ can be achieved, 47% lower. • Distributed building infrastructures have great potential of reducing cooling energy consumption. • Dynamic simulation is a paramount tool to design enhanced energy management strategies. • Free cooling contributes to 50% reduction of energy demand for equipment cooling. • Operational energy and use of material can be reduced with optimal envelope design. • The study proposes design criteria aimed at increasing energy efficiency at the infrastructure level. [ABSTRACT FROM AUTHOR]

The PV/T hybrid system has irreplaceable advantages in the comprehensive utilization of energy because of its capability to simultaneously generate heat and power. A heat pipe PV/T system is often used in cold area duo to its high energy efficiency and anti-frost properties. While most of existing systems only focus on the hot water supply, rarely involving in the function of space heating. In this paper, a novel dual-condensers heat pipe system is proposed to extend its energy supply functions and application areas. This study aims to establish a mathematical model of the proposed system, and analyze the performance of the system in different climatic region cities. Three cities in different climate zones were selected as boundary conditions for the analysis. The numerical result shows that in the hot water mode the system's electrical efficiency is 13.6%, 13.3% and 13.5%, and the total efficiency is 56.1%, 59.7% and 60.6%, respectively. In space heating mode, the system's electrical efficiency is 14.7%, 14.8% and 14.8%, and the total efficiency is 55.4%, 55.4% and 51.1%, respectively. The results confirm that the performance of the novel PV/T is steady and suitable for the cities with different environmental conditions. • A novel multi-functional heat pipe PV/T system was designed and constructed. • A dynamic model of the novel dual condensers heat pipe PV/T was presented. • The model accuracy was validated by experiment giving less than 10% in error. • The typical day's energy efficiencies in different climatic regions are similar. • The total efficiency of the in summer and winter is about 60% and 55%, respectively. [ABSTRACT FROM AUTHOR]

In Italy, the economic support scheme for high-efficiency cogeneration annually provides tradable White Certificates to new constructed or refurbished high-efficiency cogeneration plants over a period of 10 years, proportionally to their annual primary energy saving. In contrast to the legislation currently in force, which assumes the power grid efficiency constant, this paper aims at assessing the adoption of a time-dependent approach, based on the use of the thermoelectric-based power grid efficiency, for evaluating the primary energy saving ensured by high-efficiency cogeneration as well as the relating economic incentives. The case study being analysed includes two 5.5 kW el micro-cogenerators installed in Naples (South Italy). Beyond the conventional, three scenarios have been outlined, depending on the time accuracy adopted (yearly, monthly and hourly basis). Starting from 2016, the scenarios have been replicated over the ten-year incentive period. In particular, the annual average thermoelectric-based power grid efficiency has been forecasted from 2021 to 2025. Following the innovative approach proposed in this study, the White Certificates would have increased by 9.2% in 2016, by 6.1% in 2017 and by 6.1% in 2018 too, thus fostering the achievement of the targets about high-efficiency cogeneration at national level. • In Italy, White Certificates are recognized to high-efficiency cogeneration. • The power grid efficiency affects the primary energy saving of cogeneration. • Hourly thermoelectric-based power grid efficiency indicators vary over time. • Increased time-accuracy means improved meaningfulness of results. [ABSTRACT FROM AUTHOR]

This paper develops a thermodynamic model for the regenerative Brayton cycle that uses monochlorobiphenyl waste as fuel in a combustion chamber to power a gas turbine. The regenerator increases the air temperature entering the combustion chamber to react with monochlorobiphenyl wastes to produce a higher turbine inlet temperature. The pressure ratio and turbine inlet temperature can negatively or positively affect power plants' thermal efficiency. Thus, different pressure ratios and turbine inlet temperatures are used to calculate the overall thermal efficiency. A stoichiometric reaction-based gas composition model is used to determine the combustion gas composition at the combustion chamber exit and to calculate the heat capacity of air and combustion gases as a function of temperature. The exergy analysis of the proposed power plant is presented to determine the effect of the pressure ratio on the exergy efficiency of the turbine, compressor, and regenerator. According to the results, an increase in pressure ratio increases cycle thermal efficiency and turbine inlet temperature when using a regenerator, whereas the temperatures decrease when not using a regenerator. The Brayton cycle with a regenerator increases thermal efficiency from 30% to 100% for a pressure ratio of 6–30. This contrasts with the Brayton cycle without a regenerator. In addition, for the regenerative Brayton cycle, the turbine inlet temperature rises from 1050 K to 1200 K as the pressure ratio rises from 1 to 30. In the absence of the regenerator, however, this variation's trend is in the opposite direction. Furthermore, the results show that an increase in pressure ratio will increase the exergy efficiency of the compressor and regenerator, while a decrease will occur in the exergy efficiency of the turbine. Findings indicate that the regenerator has the highest exergy efficiency at a pressure ratio higher than five, followed by turbine and compressor exergy efficiency. [Display omitted] • Increase in pressure ratio, improves regenerator and compressor exergy efficiency. • Turbine efficiency increases system efficiency in "with regenerative" mode. • In "no regeneration" mode, boosting the pressure ratio improves thermal efficiency. • In "with regeneration" mode, turbine intake temperature decrease with pressure ratio. [ABSTRACT FROM AUTHOR]

Improving energy efficiency helps achieve energy conservation and emission reduction. Examining whether China's SO2 trading emission system (TES) reform can enhance energy efficiency will provide empirical evidence for the institutional benefit of market-oriented environmental regulation in environmental governance. This paper employs the difference-in-differences (DID) method to examine the effect of SO2 TES on energy efficiency using panel data from 285 Chinese cities from 2003 to 2018. The empirical results indicate that: (1) SO2 TES significantly promoted green total factor energy efficiency and reduced energy intensity. This conclusion is still valid after the prerequisite assumption test and robustness test. (2) SO2 TES significantly promotes local energy efficiency and has significant spatial spillover effects on surrounding cities. (3) Promoting green technological progress, resource allocation, and curbing energy consumption, are the primary mechanisms for SO2 TES to improve energy efficiency. (4) SO2 TES's improvement in energy efficiency comes more from eastern, developed, small, resource-based, and non-old industrial cities. • SO2 trading emissions system (TES) improves energy efficiency. • TES has a spatial spillover effect on nearby cities. • Green innovation, resource allocation and energy saving effects are the channels. • The effect of the TES on energy efficiency is heterogeneous. [ABSTRACT FROM AUTHOR]

This paper presents the performance evaluation of several combinations of working fluids for a new heat recovery cogeneration system which combines an Organic Rankine Cycle (ORC), a Vapor Absorption Cycle (VAC) and a Vapor Compression Cycle (VCC). NH 3 –NaSCN is chosen as the working fluid in the VAC. Seven different refrigerants in the ORC-VCC were studied to identify the fluid that would allow the overall system to achieve a high efficiency in the tropical region. These fluids were chosen because of their low Global Warming Potential and Ozone Depletion Potential. A thermodynamic simulation allowed to set the appropriate operating conditions of the VAC. Subsequently, energy and exergy analyses showed that R717 is the appropriate working fluid for system operation in the tropical region. For this fluid, the highest values of cooling capacity, net power output, thermal efficiency, exergy efficiency and exergy destruction of the system were respectively 1205 kW, 158.3 kW, 64.32%, 39.39% and 690.4 kW for VCC evaporation temperature of 15 °C, for ORC-VCC condensation temperature of 40 °C and for ORC steam generator outlet temperature of 219.7 °C. The most exergy-destroying components are the steam generator and the ORC/VCC condenser with 57.29% and 22.58%, respectively. • Vapor recovery at the turbine outlet improves overall system performance. • Electricity produced is not influenced by the operation of the VAC cycle. • For R717, cold production slightly increases with ORC/VCC condensation temperature. • Cold is produced by the VAC by recovering the waste heat at the turbine outlet. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is crucial for reducing energy consumption and carbon emissions. Energy efficiency is thought to be greatly improved by digital technology. Investigating the connection between digitalization and energy efficiency can offer a valuable reference for the worldwide achievement of the carbon neutrality goal. To analyze this relationship, this paper constructed a digital evaluation index system and collected data from 90 countries between 2000 and 2020. The findings of the two-way fixed effect panel model indicate that there is an inverted U-shaped relationship between digitization and energy intensity. The conclusion is still valid after using the two-stage least square method, the generalized method of moments, and a series of robustness tests. When the digitization level reaches 0.4324, digitization can improve energy efficiency and play an energy-saving role. According to the results of the heterogeneity analysis, developed countries have already reached the stage where digitalization can improve energy efficiency while developing countries have not yet reached this stage. Moreover, no heterogeneity effect caused by the energy mix and electrification level was observed. This study clarifies the causal relationship between digitalization and energy efficiency and provides factual support for digital and decarbonization transitions. • There is an inverted U-shaped relationship between digitization and energy intensity. • Digitization can improve energy efficiency when the digitization level reaches 0.4324 • Digitalization can significantly reduce energy intensity in developed countries. • No heterogeneity was discovered regarding energy endowment and electrification level. [ABSTRACT FROM AUTHOR]

The state of energy (SOE) of the lithium-ion battery indicates the driving range of electric vehicles, which is affected by its maximum available energy (MAEgy). Meanwhile, the energy efficiency is of great significance to improve the estimation accuracy. In this paper, a collaborative estimation method of the SOE and MAEgy with optimized time windows considering energy efficiency is proposed. Firstly, based on the Thevenin model of the battery, the forgetting factor recursive least squares is used to identify its parameters. The state space equations of the SOE and MAEgy are established respectively and two extended Kalman filters are leveraged to estimate them with different time windows. To reduce calculations and improve estimation accuracy, the multi-objective genetic algorithm is applied to optimize the time windows for the transient scheme and steady scheme, respectively. Then the optimal time windows of the initial and convergence phase are derived from these two schemes by the entropy weight method. Finally, the instantaneous energy efficiency is deduced, and the influences of four different calculation methods on the estimation performances are discussed. The results show that the proposed method has better transient performances and steady-state accuracy under dynamic driving condition and is robust against incorrect initial values. [Display omitted] • The SOE and MAEgy are collaboratively estimated with multi-scale time windows. • The time windows are optimized by MOGA and determined by entropy weight method. • Four instantaneous energy efficiencies for the lithium-ion battery are discussed and applied in the collaborative estimation. [ABSTRACT FROM AUTHOR]

Most of existing photovoltaic (PV)-Trombe wall systems use a single coolant which has the drawbacks of low utilization efficiency and unreasonable heat distribution of space heating. In order to address these problems, a novel micro-channel heat pipe PV-Trombe wall system is proposed in this paper. The system uses heat pipe and Trombe wall to cool the PV collector decreasing its operating temperature and thus improving the overall efficiency. Moreover, an air-cooled condenser is used to control the thermal energy transfer in the room to improve the thermal comfort. The mathematical model of the system under different operation modes is verified to investigate the performance of the system in Lhasa, Beijing and Nanjing. The results show that: (ⅰ) during the space heating mode, the average room temperature of 20.36 °C, 19.80 °C and 20.18 °C can be reached while the daily total power generation of 0.86 kWh, 0.81 kWh, 0.72 kWh can be achieved in Lhasa, Beijing and Nanjing, respectively; (ⅱ) during the hot water mode, the water temperature in the tanks increases only by 8.08°C–12.76 °C and the total power generation is around 0.20 kWh-0.23 kWh in the three cities while the indoor temperature increases by less than 0.1 °C due to the lowest facade solar radiation in summer. • Proposing a novel micro-channel heat pipe photovoltaic-Trombe wall system. • The system can realize multiple functions under different running modes without power equipment. • Establishing a dynamic mathematical model. • Investigating the performance of the system in representative cities in China. [ABSTRACT FROM AUTHOR]

As an important driving force for energy efficiency, the digital economy plays an irreplaceable role in achieving the goal of energy conservation. Entrepreneurship, as an endogenous force driving economic growth, also has an important impact on energy efficiency. Therefore, this paper incorporates entrepreneurship into the analysis framework of industrial development, and discusses the main paths and theoretical mechanisms of digital economy affecting energy efficiency from the two dimensions of entrepreneurship's innovation spirit and entrepreneurial spirit. The current work has yielded the following results: (1) The digital economy has significantly improved energy efficiency, and after a series of robust tests, this conclusion is reliable. (2) The nonlinear regression results show that with the improvement of economic development level, the role of digital economy in promoting energy efficiency gradually increases. 3) The heterogeneity test found that the digital economy had a significant role in promoting energy efficiency in the sample of resource-based cities and central region, but this effect was not significant in the samples of eastern and western regions and non-resource-based cities. (4) Mechanism testing shows that entrepreneurship's innovation spirit is an important mechanism for promoting energy efficiency in the digital economy, while entrepreneurial spirit is not. (5) From the convergence model test, it can be seen that the regional convergence of energy efficiency objectively exists, and the digital economy has become a booster to promote its regional convergence. • The digital economy has significantly improved energy efficiency. • The effects of entrepreneurship's innovation spirit are crucial channels. • The regional convergence of energy efficiency objectively exists. [ABSTRACT FROM AUTHOR]

An analysis of the end use of energy in the EU reveals that industry is one of the three dominant categories, which accounts for 26.1% of the final end use of energy. In the case of the aluminium industry, approximately 70% of energy consumption is due to heat and thermal processes, highlighting a vast potential for waste heat recovery technologies. Within the aluminium die casting industry, liquid aluminium is cast, formed, cooled, and further processed within a thermal heat process, which includes three sub-processes: solubilising, quenching, and ageing. In the case presented, a thermal heat process is the second most energy intensive process within the factory, and the ageing heat treatment furnace accounts for 15% of the thermal heat process. The thermal heat treatment generates a significant amount of waste heat. The recovery of that waste heat, with minimal risk of cross contamination between streams and reduced chance of equipment failure, has been achieved via the use of a heat pipe heat exchanger (HPHE). The HPHE has been designed, manufactured, and installed in the solution furnace exhaust stack. The HPHE was designed to recover up to 88.6 kW in steady state operating conditions at 400 °C. The return on investment has been evaluated at 35 months with an expected CO 2 emissions reduction of 86 tCO 2 /year when best engineering practices are applied. Furthermore, a theoretical modelling tool to predict the thermal performance of the HPHE was developed and validated within a ±20% deviation from the experimental results. This paper further presents the development of the theoretical model to allow a characterisation of HPHE technology and will act as a guideline for the design of HPHEs within the aluminium industry. • A HPHE for waste heat recovery (WHR) in the aluminium industry was demonstrated. • The HPHE was designed to recovery 88.6 kW. • The HPHE performance was monitored and assessed over 6 months period. • The HPHE has a payback period of 35 months and CO 2 reduction of 86 tCO 2 /year. • The presented HPHE represents a reference for future industrial WHR applications. [ABSTRACT FROM AUTHOR]

This paper investigates an integrated energy management strategy (IMS) to improve energy efficiency of proton exchange membrane fuel cell (FC) system in intelligent fuel cell/battery hybrid vehicles (FCHVs). Unlike other similar works which solely control output current from the FC system, stack temperature regulation is added in this research due to its impact on FC output power performance. For liquid-cooled FC systems, joint management of FC current and stack temperature is more difficult than air-cooled FC systems due to complicated thermal management systems. To address this, firstly, a control-oriented integrated model is established to provide the foundation for controller design. For the purpose of decreasing the strong nonlinearity of integrated model, the heat generation term is parameterized with a polynomial function. Secondly, in order to determine reference trajectories for controller, a data set consisting of nearly optimal operation points (FC current and stack temperature) is constructed offline, which provides reference trajectories based on simple rules in real time. Finally, a contraction-based control (CBC) approach is utilized to regulate FC current and stack temperature jointly. The bounded convergence between system states and reference trajectories is guaranteed by contraction theory. The effectiveness of the proposed IMS is validated via MATLAB simulation. • An integrated management strategy is proposed to enhance FC system energy efficiency. • A data set is constructed to provide the nearly optimal operation points of FC system. • The online ascertainment of reference FC operation points is achieved with simple rules. • The bounded convergence to reference trajectories is ensured by a contraction-based control. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is one of the most effective ways to reduce energy waste and achieve carbon neutrality, but it may also bring the energy rebound effect and thus fail to achieve the desired energy conservations. In this paper, we examine the energy rebound effect of Beijing at the level of overall economy, industry and sector based on the Cobb-Douglas production function and the idea of Solow residual, so as to clarify the true impact of technological progress on energy-saving target. Results suggest that: (1) The overall economy of Beijing shows partial rebound effect in most years and appears backfire effect in some years, but the degree of the rebound effect has been gradually mitigated; (2) The energy rebound degree of the tertiary industry is higher than that of the secondary industry on the whole, but the rebound effect of the secondary industry fluctuates more obviously; (3) Energy savings at the sector level is also not ideal, and in most cases, sectors with low energy efficiency have a higher rebound effect than sectors with high energy efficiency. Based on these results, suggestions are provided to alleviate the energy rebound effect of Beijing. • The energy rebound effect of Beijing are quantified at the level of overall economy, industry and sector. • The overall economy of Beijing appears backfire effect and partial rebound effect. • The energy rebound effect of the tertiary industry is higher than that of the secondary industry in most years. • Sectors with low energy efficiency may have higher rebound effects. [ABSTRACT FROM AUTHOR]

Energy drives national economies with a positive correlation. Global environmental concerns, growth of the world population, and emerging of developing economies with more need for energy resources, would change the future of energy markets and human lives. To manage energy shortage and energy-related environmental threats, decision-makers have to decide between three potential solutions [1], to develop supply value [2], to suppress energy (all types) demands, or [3] to adopt a hybrid strategy. This paper is aimed to uncover potential saving capacities to fill the supply-demand gap based on efficiency improvements for the case of Iran as a developing economy with increasing energy needs. The methodology has been designed based on energy balance calculations which have been evaluated and validated through 47 expert panels under 9 major themes. Then, policy sets have been determined and to map how defined policies were interacting in the living energy, a system interpretive structural model was performed to determine direct and indirect relationships among policies. As a result, policymakers can prioritize and set a roadmap to approach the desired future. Findings showed for the case of supply-side Iranian energy management [1] maximizing electricity transmission and distribution efficiency [2], upgrading the consumption standard in equipment and processes (in the terms of energy production, conversion, and transmission), and [3] online monitoring of distribution networks are most basic and top priority policies. While for the case of demand-side "targeting energy subsidies" is the most crucial policy to support the Iranian energy efficiency improvement targets. • Iran's potential saving capacities to fill the supply-demand gap based on efficiency improvements are studied. • Policy sets have been proposed through 47 expert panels containing 9 main themes. • An interpretive structural model was performed to map policy relationships and dedicate a macro-level action plan. [ABSTRACT FROM AUTHOR]

In the paper presented is analysis of the influence of reduced pressure on efficiency and heat transfer area of vapor generator of Organic Rankine Cycle (ORC) in case of subcritical and supercritical parameters of operation. Compared are two cases of subcritical and supercritical ORC featuring a similar arrangement of heat source supply and heat removal, that is featuring the same temperatures of working fluid before the turbine, and the same condensation temperature in the respective cycles. The analysis is helpful in selection of the appropriate pressure in the vapor generator. In accomplished analyses a selection of wet ORC working fluids are scrutinized for a given range of heat source temperatures with respect to influence on efficiency of thermodynamic cycle and vapor generator area of heat transfer on installation and operation costs to illustrate the issue. Investment cost of a vapor generator in the ORC cycle accounts for a main share of expenditure alongside the cost of the expanding machine. Results of calculations show that from the point of view of cycle efficiency and size of vapor generator the pressures close to critical fluid pressure are usually optimal. Some working fluids feature even an optimal pressure. For the region close to critical point authors elaborated own method for heat transfer coefficients elaboration, which is useful in more exact estimations of heat transfer process in vapor generator. In case of a heat source with a relatively high temperature, it is better to consider a thermodynamic cycle with supercritical parameters even if as a result the vapor generator is slightly larger than for the case of a subcritical cycle. There will always be a more pronounced gain in efficiency compared to the expense induced by the heat transfer surface area of vapor generator. • Effect of reduced pressure on efficiency and heat transfer area of vapor generator is analysed. • An analytical model for determination of heat transfer area of vapor generator is formulated. • Own method for estimating heat transfer coefficient for subcritical and supercritical pressures is applied. • The effect of reduced pressure on efficiency and heat transfer area is shown. [ABSTRACT FROM AUTHOR]

The article presents problems related to the assessment of local energy efficiency of energy systems. In practice, local energy efficiency is commonly used to evaluate these systems, which is not a correct criterion to compare different energy technologies, especially non-renewable and renewable energy systems. For the correct assessment of efficiency, a system analysis in the global balance boundary should be used. In the paper system analysis algorithm is discussed - Thermo-Ecological Cost (TEC), which is a correct tool to compare energy and ecological efficiency of different energy systems. Problems with the correct application of the energy and environmental efficiency assessment are illustrated with examples of results of local and system (TEC) evaluation of non-renewable and renewable energy systems efficiency. • Results confirming that local energy efficiency is not proper tool to compare different energy technologies. • Presentation of advanced system analysis tool – Thermo-Ecological Cost (TEC) – for proper comparison efficiency of energy technology. • Comparison of local and system assessment of efficiency of non-renewable, renewable, renewable integrated with accumulation energy systems. • Results confirming that local and system evaluation of energy systems can lead to opposite conclusions. [ABSTRACT FROM AUTHOR]

Employment of renewable energy instead of fossil fuels in the textile factory reduces the problems caused by fossil fuels. This paper conducts detailed modeling of a novel integrated textile factory and power system using geothermal energy. Energy and exergy analysis are done, and the effects of changes in critical parameters on the energy and exergy performance of the proposed system have been evaluated. In addition to find the best performance condition of the suggested system, a multi-criteria optimization is done. A creative waste heat recovery system (WHRS) is designed to recover the waste heat of the proposed cycle. Results obtained from the thermodynamic modeling are analyzed to find effects on energetic and exergetic performances of the proposed combined system with varying time. The results show that the drop in temperature of the water entering the reinjection well occurred when hot water was in demand for the textile factory. The temperature range of 90 °C –96 °C are selected as temperature intervals for using WHRS. The maximum energy efficiency is about 6.2%, which is related to the time intervals when there is no demand for hot water in the textile factory. In the first three-time intervals that the WHRS is active, the energy efficiency increases from 3.38% to 4.6% and the exergy efficiency increases from 17.59% to 21.06%. According to the multi-objective optimization of Kalina cycle in the selected optimum condition the system energy efficiency and exergy destruction rate are 9.39% and 152.36 kW. • Propose a new integrated system based on textile factory and geothermal source. • Determine the effect of main variables of Kalina cycle on the overall performance. • Application of multi-objective optimization to determine the best suggested system. • The KCS optimization leads to decrease the system exergy destruction substantially. [ABSTRACT FROM AUTHOR]

This paper presents the energy efficiency potentials from Diesel generator operations on bulk carrier, chemical tanker, ro-ro, and container vessels. The electrical energy usage that may occur if the generators are operated in the range of 40%–90% capacity was examined in terms of annual average fuel consumption, fuel cost, and emissions. In this study, the type and size of vessels, generator specifications, electrical energy demand, and time spent at berth, maneuvering, and at sea were considered. Thus, the annual energy savings obtained from various load sharing practices of generators were analyzed. The results showed that although annual savings vary according to the type of vessel, a minimum of 7% reduction in fuel consumption, fuel costs, CO 2 , and NO x emissions can be achieved if generators are operated at 90% instead of 40% capacity. The minimum reduction in SO x is also around 5%. In addition, it is possible to achieve savings of up to 17% in all parameters. Therefore, marine generators should be set to their optimum capacity to help reduce energy use and emissions from shipping. In this context, some predictive methods or alternative energy sources can be integrated into the main switchboard to keep the generators at their optimum capacity. • The efficient use of electrical energy for various vessel types is being evaluated. • The efficient operation of generator sets on conventional vessels is examined. • Various load sharing practices of generator sets are compared. • The annual energy savings potential from generator sets is estimated. [ABSTRACT FROM AUTHOR]