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A liquid nitrogen wash based novel system is proposed for electricity generation and LNG production. This system utilizes cold energy of methane rectification for power generation, and realizes the LNG production through methane recovery from exhaust gas. Effects of operational parameters on net generation capacity (NEG) and energy efficiency are studied. Exergy destruction/efficiency and exergy cost are obtained. Advanced exergy/exergo-economic analyses are conducted to clarify the improvement potential and improvement strategy. Finally, the optimal solutions are obtained in multi-objective optimization. Results show that propane could be used as the organic working medium and the maximum NEG is 675.95 kW and the energy efficiency is 19.34 %. As 88.8 % of the system investment cost is for the equipment, reduction on exergy destruction cost of equipment should be considered. Advanced analysis indicates that 27.27 % of the exergy destruction, 30.02 % of the exergy cost and 7.20 % of the investment cost can be avoided. The thermodynamic optimization shows that the highest energy efficiency is 67.26 %, the highest exergy efficiency is 76.95 % and the lowest exergy cost per unit is 28.45 $/GJ. The economic optimization shows that exergy efficiency is improved by 2.83 % and NEG is improved by 47.95 % when increasing the investment cost for 6.13 %. • A liquid nitrogen wash based system is proposed for electricity and LNG production. • Advanced exergy/exergo-economic analyses are conducted for the system evaluation. • 27.27 % of exergy loss, 30.02 % of exergy cost and 7.20 % of investment can be avoided. • The highest energy efficiency and exergy efficiency are obtained as 67.26 % and 76.95 %. • Optimal operation of this cogeneration system is achieved using the genetic algorithm. [ABSTRACT FROM AUTHOR]

To achieve efficient utilization of renewable energy and facilitate the development of a more equitable and harmonious power market, an optimization study is conducted focusing on peer-to-peer (P2P) power sharing within multiple low-carbon microgrids (LCMGs). Firstly, the coordinated operation mechanism of a LCMG is proposed involving a step-type carbon trading scheme as well as flexible supply and demand. Then, an optimization model of multi-LCMG cooperative operation is formulated based on the Nash bargaining theory. The original Nash bargaining problem is equivalently transformed into a subproblem of maximizing alliance benefits and a subproblem of maximizing the benefits of power trading. In the first subproblem, a combination of opportunity constraints and robust optimization method is employed to address these multiple uncertainties from renewable generation and electricity prices. The second subproblem addresses the issue of gaming fraud among LCMGs with a third-party intermediary model applied to achieve a fraud equilibrium. Further, to solve these problems efficiently, an improved adaptive parametric alternating direction method of multipliers (AP-ADMM) algorithm is used to protect the privacy of each party. Finally, a case study was conducted to validate the efficacy of the proposed method in enhancing the stability and cost-effectiveness of cooperative optimization within multi-LCMG systems. • Constructing a low-carbon microgrid with a flexible dual response while considering multiple uncertainties. • Developing a cooperative operation model for multiple low-carbon microgrids based on Nash bargaining theory. • Introducing an intermediary transaction model, thereby reducing game-fraudulent negotiations among the participants. • Enhancing the adaptive parameter ADMM algorithm to solve the cooperative game model. [ABSTRACT FROM AUTHOR]

In the process of vaporizing water within the biogas-driven CCHP system based on chemical recuperation, a significant temperature disparity in heat transfer exists, leading to increased irreversible loss, and the methane conversion rate is low because the gas turbine exhaust gas is difficult to drive efficient methane conversion. This paper proposed a novel biogas-driven CCHP system based on chemical reinjection. Through the reinjection of a portion of the exhaust gas into the reactor, a self-thermal reforming reaction process is engineered, leading to a substantial enhancement in methane conversion rate. The heat matching of the heat exchange unit is optimized by the reheat air, and the power generation and cooling capacity of the system are improved. Notably, the electricity and cooling generation of the new system increased by 55.52 kW (6.20 %) and 542.49 kW (101.49 %), respectively, while the exergy efficiency increased by 8.31 %. The study delves into the influence of key parameters on the system thermal performance. During the reforming process, the exhaust gas split ratio has a significant impact on carbon deposition and methane conversion. When the methane is nearly completely converted, there is no significant change in electricity generation of the system. Excessive turbine inlet temperature is found to be unfavorable for improving the exergy efficiency of the new system from a holistic system perspective. Finally, a comprehensive comparison of the thermal performance between the new system and the reference system is conducted under various ambient temperatures. This study offer a new design scheme for the efficient utilization of biogas. • A novel biogas-driven CCHP system based on chemical reinjection is proposed. • Partial exhaust gas reinjection for self-heating of biogas reforming reaction. • The thermal efficiency and exergy efficiency increased by 28.39 % and 8.31 % in the new system. • The system is subjected to parameter analysis in combination with carbon deposition analysis. [ABSTRACT FROM AUTHOR]

This paper focuses on the determination of the optimal operating scenario of an Externally-Fired Micro-Gas turbine utilizing syngas produced by biomass gasification. Biomass exploitation can contribute to the achievement of the net-zero emissions target in 2050. This can be boosted by the advancement of externally-fired technology. In this study, a dual-objective optimization process, including a validated thermodynamic model, is combined with preliminary cost insights to assist the decision-making process. The resulting performance is compared with the actual data-based performance of a reference natural-gas-fired Micro-Gas Turbine. The performance comparison is performed through an exergetic analysis, identifying the main losses contributors. The optimization results in an externally-fired performance of 77.9 kW el electrical power and 20.3% efficiency, improved by 31.5% compared to the average current externally-fired demonstrated efficiencies. Yet, there is still room for improvement to reach natural-gas-fired Micro-Gas Turbine efficiency. The study highlights an unavoidable efficiency decrease of at least 4.0 percentage points due to the use of syngas itself instead of natural gas, which conversely increases heat recovery potential. However, compared to the state-of-the-art demonstrations, the proposed analysis is a significant step towards efficiency improvement, which can be exploited for future biomass demonstrations, attractive for electricity generation as well. • Performance of an externally-fired microturbine using biomass syngas is optimized. • Design point is determined through an optimization with preliminary cost insights. • Performance is compared with the validated data from a natural gas microturbine. • Electrical efficiency improved by 31.5% compared to average current demonstrations. • Syngas use results in an unavoidable efficiency decrease of 4.0 percentage points. [ABSTRACT FROM AUTHOR]

Deck photovoltaic (PV) system has been widely investigated on ocean-going ships to reduce oil consumption. However, its adoption on smaller ship encounters obstacles such as limited deck space, reduced energy efficiency, and cumbersome support structures. This paper explores the application of vertical PV windows on small ships as an alternative solution. By retrofitting standard glass with PV windows, the electricity generation area is expanded without occupying valuable deck space or requiring heavy brackets. Unlike deck PV system that solely generate electricity, PV windows also have the added benefit of reducing cooling load inside cabin, enhancing the overall energy-saving effect. Solar energy received by vertical surface is related to heading angles during navigation, a factor that has received scant attention in previous studies. Therefore, hybrid energy saving performance of PV window system is investigated under sailing condition by experiment and simulation methods. The electricity performance of PV window exhibits periodic fluctuations in closed-route trails, with sailing resulting in better electricity performance than mooring. Annual simulation research indicates that PV window system can generate 300.0 kWh of electricity actively, decrease 374.4 kWh of air conditioning load passively and reduce 472.0 kg of CO 2 emission. The optimal transmittance of PV window is 0.4%. • Hybrid energy saving performances of ship PV window system are researched by experiment and simulation. • The periodical changes of received solar radiation and electricity performances are observed from experiment. • The electricity generation and air conditioning load reduction are 300.0 kWh and 374.4 kWh, respectively. • The recommended transmittance of PV window is 40%. • Sailing can promote the electricity efficiency and power generation. [ABSTRACT FROM AUTHOR]

The wave energy potential in the Adriatic Sea is investigated at seven offshore locations, and the mean annual energy, average electric power production, operating hours, as well as the coefficient of variation of the monthly power production are determined for three wave energy converters. Since wave energy converters are commonly designed and optimized to extract energy from ocean waves, they have low capacity factors in low-energy seas or bays such as the Adriatic Sea, where the sea states are slight to moderate. The scaling of the wave energy converters is performed on the basis of the Froude scaling law for AquaBuoy and Pelamis devices. The results of WECs at eleven scales are compared with those obtained for a Lysekil WEC. The obtained results show that the capacity factors of the downscaled WECs increase significantly at their optimum scales, reaching about 29 % and 42 % for the AquaBuoy and Pelamis, respectively, depending on the location. By comparing the results obtained for the AquaBuoy and Pelamis at a scale of 0.7 with the results of a full-scale Lysekil WEC, it may be concluded that the downscaled WECs may be more suitable for the considered locations in the Adriatic Sea while keeping their economic viability. • The wave energy potential of seven locations in the Adriatic Sea is investigated. • The performance of full-scale and downscaled WECs is evaluated. • The capacity factors and operating hours of WECs in eleven scales are quantified. • By reducing the WEC size, a significant increase in the capacity factor is obtained. • The variability in monthly power production is assessed. [ABSTRACT FROM AUTHOR]

This paper investigates the challenges isolated islands face in transitioning from fossil fuel-based electricity generation to renewable energy sources. The Canary Islands serve as a case study, where photovoltaic and wind power are the primary renewables, but their variability requires a deep techno-economic analysis. The island's energy demand is predicted to rise by 100% due to economic growth, electrification and electric vehicles. However, implementing renewable systems encounters obstacles, such as limited suitable sites and protected areas. The study uses Wilks' methodology and Monte Carlo sampling to explore 59 combinations of randomly selected inputs of the uncertain variables, aiming for a 95/95% coverage and confidence level in the results. In most cases, they experience energy shortages, failing to meet electric demand. Even though a new generation mix appears to cover demand under all circumstances, the uncertainty unveils a different reality, leading to an approximate 25% increase in system costs. Surpluses in energy generation, while seemingly positive, can pose challenges. The new system's Levelized Cost of Energy increases from around 14 to 17c€/kWh. These cost increases are contingent upon future performance and the variability of uncertain parameters, leading to excesses ranging from slightly below 25% to over 40%. • Demand coverage scenario designed to meet electric demand through renewable sources. • Uncertainty analysis of a scenario for the complete electrification of the economy. • Best Estimate Plus Uncertainty analysis implementing the Wilks' methodology. • Resizing the system to cover the demand with 95% coverage and confidence levels. • Differences in using deterministic and stochastic methods for electric demand coverage. [ABSTRACT FROM AUTHOR]

Coal-based Allam cycle is an advanced low-carbon and efficient power cycle that uses syngas produced by coal gasification to drive the semi-closed supercritical CO 2 cycle for electric power generation. To improve the thermodynamic and economic performance, a novel coal-based Allam cycle coupled to CO 2 gasification is proposed. Compared to the reference system, the steam for gasification is eliminated and the mole fraction of H 2 within the raw syngas is reduced, which could effectively decrease the moisture fraction of the combustion flue gas and give enough margin to intensify heat integration. Thereby, more process heat has been saved to drive the efficient supercritical CO 2 cycle and the raw syngas cooling heat is further recovered by the main recuperator. Results show that the net efficiency of the novel system soars to 43.99%, which is enhanced by 0.67% points. Moreover, the exergy efficiency increases by 0.65% points with the total exergy destruction and loss reduced by 1.23%. In addition, the total plant investment (TPI) and the cost of electricity (COE) are reduced by 1.42% and 1.39%, respectively, which proves that the novel system is also superior for commercial application. • CO 2 gasification of coal is coupled to a semi-closed supercritical CO 2 cycle. • Heat integration is improved with the elimination of steam for gasification. • Energy/exergy efficiency is enhanced by 0.67/0.65% points. • Superior economic performance is obtained with COE decreased by 1.39%. [ABSTRACT FROM AUTHOR]

Closed-Brayton-cycle (CBC) has considerable potential for power generation on hypersonic vehicles, but its power level is limited by the cold source onboard, commonly the hydrocarbon fuel. To achieve power enhancement of CBC with finite cold source, this study assessed and compared the power output and thermal efficiency of supercritical carbon dioxide (S–CO 2) and helium-xenon mixture (He–Xe) CBCs at ultra-high turbine inlet temperature (TIT), taking into account the thermal cracking of hydrocarbon fuel. Results indicate that raising TIT can significantly increase the electric power output for both CBC working fluids. The electric power under per unit mass flowrate of fuel is as high as 1600 kJ/kg at the TIT of 2000 K, making it easy to achieve megawatt-level power generation. The power enhancement of He–Xe CBC is more significant than S–CO 2 CBC when the TIT exceeds 2000 K. Moreover, the compressor inlet temperatures and cycle pressure of S–CO 2 CBCs are much higher than those of He–Xe CBC, causing additional challenges in the aerodynamic design and component manufacture. Therefore, He–Xe CBC operating at ultra-high TITs may be more suitable than S–CO 2 CBCs for high-power electricity generation mission on hypersonic vehicles. • Improving TIT is dramatically effective for power enhancement with finite cold source. • Electric power per unit mass flowrate of fuel is 1600 kJ/kg at TIT of 2000 K. • At ultra-high TITs, T 1 of S–CO 2 CBC is much higher than that of He–Xe CBC. • He–Xe closed-Brayton-cycle may be more suitable than S–CO 2 CBC. [ABSTRACT FROM AUTHOR]

The utilization of geothermal resources for electricity generation relies heavily on appropriate power plant technology, which is linked to the resource's enthalpy potential. Moderate and high-enthalpy resources often find application in binary (Organic Rankine Cycle) plants, flashing-type plants, or even hybrid configurations. Among the crucial elements determining plant efficiency is the cooling system. By maintaining low turbine exhaust pressure, an effective cooling system facilitates enhanced power output. Traditional options include wet-type and dry-type cooling systems, both with established roles in geothermal applications. This study focuses on mitigating the detrimental impact of high ambient temperatures during summer months on geothermal power plant performance. Specifically, we propose the first-ever implementation of ground source cooling for a combined geothermal power plant in Western Anatolia, Turkiye. This innovative approach aims to counteract the decline in electricity generation observed during summer and maintain stable output throughout the year. The TOUGH + RealGasBrine V1.5 was employed to model the heat transfer dynamics between the buried pipes of the ground source cooling system and the surrounding ground. The simulated system underwent a three-month injection phase followed by a nine-month shutdown period to allow for a return to initial temperature conditions. This comprehensive modeling approach provided valuable insights into system behavior and performance. The simulations revealed a highly encouraging outcome: ground source cooling has the potential to enhance the power generation performance of the geothermal plant by over 10% during summer conditions. This significant improvement underlines the feasibility and effectiveness of the proposed approach. Furthermore, a sensitivity analysis was conducted to assess the influence of pipe diameter on temperature transient behavior and overall system feasibility. This analysis provides valuable information for optimizing the design and implementation of ground source cooling in future geothermal projects. • The study investigates the use of ground-source cooling to increase electricity generation from power plants. • Heat transfer simulations between PEX pipes and the ground by using TOUGH2. • Feasibility assessment of ground source cooling for power generation. [ABSTRACT FROM AUTHOR]

Solar-driven thermoelectric generator is an enticing avenue for sustainable global electricity generation. Nevertheless, its broad adoption is impeded by two significant challenges: low efficiency and reliability. To address these challenges, a novel hybrid system that integrates angle-independent evacuated U-tube solar collector (EUSC) with inhomogeneous thermoelectric generator (ITEG) is first proposed in this paper. The power density of the hybrid system is predicted to be 26.1 W m−2 with an efficiency of 2.61% under AM 1.5, signaling considerable potential for performance enhancement. Extensive parametric studies demonstrate that raising the inlet water temperature for EUSC and the spatial inhomogeneity coefficient of ITEG, reducing external environmental temperatures and fluid flow rate within the EUSC, and optimizing the number and geometric characteristics of ITEG can improve the output performance. By optimizing the number of thermocouples in ITEG, the power density could reach 39 W m−2 when the spatial inhomogeneity coefficient of ITEG is 0.83. Gradient-based local sensitivity analyses further identify that the geometrical characteristics of ITEG and inlet water temperature of EUSC are, respectively, the most and least sensitive variables. These findings offer valuable insights into the intricate integration and operational mechanisms pivotal for achieving efficiency and stability in solar-driven thermoelectric generator power systems. • A novel photo-thermal-electric hybrid system is conceptualized and formulated. • Power density and efficiency can reach 26.1 W m−2 and 2.61%, respectively. • Influential laws of key design parameters and operation conditions are revealed. • The most and least sensitive factors are identified by local sensitivity analyses. [ABSTRACT FROM AUTHOR]

During the operation of alkaline fuel cells (AFCs), a significant amount of waste heat is generated, which has negative impacts on energy utilization and the environment. To improve energy efficiency, cost savings, environmental sustainability, and industrial practices, an effective approach is proposed to employ thermogalvanic cells (TGCs) for electric power generation by harvesting low-grade exhaust heat produced in AFCs. A mathematical model of the AFC-TGC hybrid system is established, taking into account the three overpotential losses in AFCs and the irreversible heat losses in TGCs. Based on this thermal-electric coupled model, we investigate the hybrid system's output performance characteristics and optimal parameter design. The calculated results indicate that the hybrid system achieves a considerable increase of 19.72% in maximum power density from 247.07 W m−2 to 295.80 W m−2 and 5.71% in conversion efficiency from 10.16% to 10.74% compared to a single AFC, respectively. In addition, the output performance of the hybrid system can be further improved by adjusting system parameters such as the AFC's operating temperature, the length of each TGC cell, the heat sink temperature, and the thermal convection coefficient. More importantly, a comparative study of the maximum power density of AFC-based cogeneration systems reveals that the TGC demonstrates a remarkable ability to economically recover waste heat from the AFC, surpassing previously reported thermal energy utilization devices. This study provides important theoretical guidance for the optimal design and parametric analysis of AFC-TGC hybrid systems, thereby facilitating the development of high-performance energy cascade utilization systems based on AFC devices. • An AFC-TGC hybrid system is proposed for waste heat recovery and cogeneration. • The total power density and overall efficiency are increased by 19.72% and 5.71%. • Parametric selection criteria for achieving better output performance are determined. • Potential advantages of the output electrical performance and cost are demonstrated. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach that addresses the intricate challenges associated with energy hubs, focusing on diverse issues in the transmission and production of energy, particularly within the realms of gas and electricity networks. A key emphasis is placed on the profitability of energy hubs, navigating through uncertainties heightened by the presence of varied energy carriers. The proposed model features an energy hub with electrical inputs and outputs encompassing natural gas, electricity, and thermal energy. Diverse sources contribute to electricity supply, including bilateral contracts, power basin purchases, and generation via a cogeneration unit. Thermal heat is provided by a heating furnace, alongside a simultaneous cooling, heating, and power production unit. Addressing market price uncertainties, the model incorporates probabilistic considerations for the next day's electricity prices. Notably, the model encompasses the intricacies of electric vehicle rechargeable modes, treating them as a bidirectional source for both energy production and consumption, contributing to effective demand-side management. To tackle the complexity inherent in these dynamics, a novel optimization method based on crow search is proposed, enhancing local and global search capabilities. The efficacy of the proposed method is demonstrated through a comprehensive application on a micro-energy grid, considering four distinct cases on a typical summer day. The analysis reveals that Case 2, incorporating PV and WT, significantly outperforms Case 1, with a 10.8 % surplus in electricity generation. Furthermore, the proposed Crow Search Optimization algorithm exhibits a 50 % improvement over alternative methods, showcasing its efficacy in achieving optimal solutions for microgrid performance. [Display omitted] • Model explores gas-electricity networks in an energy hub. • Addresses energy hub profitability amidst uncertainties. • Introduces crow search optimization for complex models. • Models EVs as two-way energy sources. • Applies proposed method to micro-energy grid scenarios. [ABSTRACT FROM AUTHOR]

The non-renewable nature of conventional power plants and the challenges associated with fuel costs and environmental impact highlight the need for innovative solutions. This research proposes a biomass-based combined system designed to produce multiple products, including electric power, coolant, and heat, addressing the drawbacks associated with conventional power generation. The proposed system integrates a biomass gasification unit with a helium gas turbine and a Kalina power unit. Additionally, a domestic water heater is incorporated into the Kalina cycle for heat generation, and the heat loss from the helium gas turbine is utilized in a modified Kalina cycle with a refrigeration unit. To further enhance efficiency, a dual-loop organic flash cycle is employed to recycle waste heat from the modified Kalina cycle. The analysis of this framework encompasses technical aspects, including energy, exergy, and economic considerations. The system is optimized using the multiple-objective particle swarm optimization method. Two scenarios are explored based on the desired product capacities: heat-electric power and coolant-electric power. In the first scenario, the system demonstrates an optimal electric power generation capacity of 6239.56 kW, along with favorable exergetic and economic outcomes. The optimal exergetic efficiency, net present value, and payback period are determined as 35.57 %, 15.07 M$, and 3.97 years, respectively. This research presents a comprehensive approach to biomass-based power generation, considering both technical and economic aspects, and provides valuable insights for sustainable energy solutions. • Renewable CCHP system using biomass feedstock and suitable waste management. • Use of helium gas turbine, Kalina cycles, and organic flash cycle for a CCHP model. • Technical energetic, exergetic, and economic analyses and multi-criteria optimization. • Heat-electric power scenario leads to the highest optimal electric power at 6239.56 kW. • Optimal exergetic efficiency and payback period are found at 35.57 % and 3.97 years. [ABSTRACT FROM AUTHOR]

This article presents a study of the electricity generation potential using ORC systems of the most important geothermal sites in northeastern Algeria, combining geological, thermodynamic and economic analysis. The results highlight that geothermal electricity is technically feasible with the selected indirect heat ORC geothermal plant. Such production can present an interesting economic profitability when considering the international electricity price. The best economic performance was obtained for the geothermal site of Meskhoutine leading to a depreciated payback period of 10.8 years. The electricity production cost was evaluated at 0.21$/kWh for an electricity production capacity of 498 kW. Such performance is completely breakdown when considering Algerian subsidised electricity prices. These subsidies must be revised. Otherwise, it will harm the profitability of renewable energy systems, limit their development, and constrain seriously the Algerian energy transition road map. In addition, this study highlights that the selected indirect ORC configuration presents an important internal auxiliary consumption, especially for the Air Condenser (AC) unit, and was not suitable for geothermal temperatures below 117 °C. Other configurations, especially hybridisation and combined heating and power production are prioritized for future investigation. • Combining geological and thermo-economic analysis for an indirect heat ORC geothermal plant. • The North-East region of Algeria highlights the most important potential for geothermal electricity production. • The maximum power scenario points out capacities of more than 1MW with a higher DPP greater than the ORC life span. • International electricity standard price leads to lower capacities but attractive economic profitability, DPP≈10.8 years. • The partial revision of electricity subsidies is strongly recommended to faster the Algerian energy transition program. [ABSTRACT FROM AUTHOR]

To expand the functions of building window and enhance its thermal performance, a novel CdTe multi-layer PV ventilated window system integrated with phase change material (PCM) was proposed. The novel window system was fabricated, constructed and installed on the south façade of a building room and several groups of seasonal experiments were conducted under different operating modes. Electrical, thermal and daylighting performance of the system were investigated. Main conclusions are: (1) For the heating season mode experiment, daily total electricity generation (E P V ) and average electrical efficiency (η e) were 0.383 kWh and 7.39 %. Room air temperature difference ( Δ T r o o m ) between the experimental room and reference room was in the range of 0.88 °C–7.04 °C. Effective functions of space heating and heat preservations were achieved; (2) For the cooling season mode, daily E P V and average η e were 0.159 kWh and 6.33 %. Δ T r o o m was in the range of −4.26 °C to −1.26 °C. Effective functions of passive ventilation cooling was realized; (3) The novel window system can provide useful daylight illuminance (UDI) for most time during the working time; (4) Based on the experiment results on transition season, other alternative operating strategies were recommended for specific different ambient condition days. • A novel CdTe based PV ventilated window system integrated with PCM was proposed and constructed. • Several groups of full-day experiments were conducted under different operating modes. • Electrical, thermal and indoor lighting performance were analyzed. • Other alternative operating strategies in transition season were recommended and discussed. [ABSTRACT FROM AUTHOR]

Spatially-disaggregated projections of new solar photovoltaic (PV) installations are essential for planning electricity grids and managing the electricity system at large scale. Such projections at sub-national level can be obtained by statistical models or by electricity system optimization models, but there is barely any study that compares the performances of these approaches. This study aims to compare methods for projecting PV installations at a level of 143 districts in Switzerland, using a simple extrapolation method (as a benchmark of the common practice today), a multiple linear regression model, two spatial regression models, and a spatially-explicit optimization model (EXPANSE) with various features to account for policy. The performance of different approaches is evaluated retrospectively for 2012–2020, using multiple accuracy indicators. The evaluation results show that statistical regression models, which account for socio-demographic and techno-economic characteristics as predictors of future PV growth, overall perform better than simple extrapolation or optimization. Although commonly used, extrapolation has the highest variability in accuracy, indicating the least robust performance. The optimization model tends to underestimate PV installations in its least-cost scenarios, if the role of policy is not considered. Incorporating solar PV policies and renewable electricity generation targets increases the overall accuracy of the optimization model at a national level, but not necessarily at a spatially-explicit level. We thus conclude that statistical models are preferred over extrapolation or optimization models for projecting future PV installations at a sub-national scale. • Statistical and optimization models for projecting spatial PV growth are compared. • Out-of-sample testing in 143 Swiss districts in 2012–2020 is used. • Statistical and optimization models perform better than simple extrapolation. • Optimization with policy is more accurate at a national, but not sub-national level. • Statistical models are preferred for projecting PV installations at a sub-national scale. [ABSTRACT FROM AUTHOR]

With the diversification of marine monitoring buoy functions, limited onboard batteries have been unable to meet the energy demand of multifarious carrying sensors. Finding a self-sustained power supply for marine monitoring buoys is an urgent problem, while wave energy is an ideal and promising option to address that problem. In this study, two wave-excited vibration energy harvesters (WVEHs) are proposed, which can be installed inside large buoys to provide a sustainable power supply. A full-coupled wave-to-wire model is developed to investigate the influence of blocks' mass, geometric size of buoys, mooring system and WVEH's quantity on the electric power performance of harvesters in realistic sea states. Parametric studies based on the Taguchi method imply that the sea state and the WVEH's quantity have a significant effect on the device's electric power performance. Numerical results indicate that the optimized two harvesters can produce a mean electric power of 777.50 W and 747.43 W , respectively, under a sea state with a peak wave period of 7 s and a significant wave height of 1.6 m. A high wave-to-wire efficiency of 2. 60 % is obtained for a specific system parameter combination. Furthermore, more electric power generation can be achieved by installing multiple harvesting units. • Two wave-excited vibration energy harvesters are proposed for large marine buoys. • A full-coupled wave-to-wire model is developed. • Harvesters are optimized based on the Taguchi method in realistic sea states. • A mean electric power of 777.50 W is achieved under a peak wave period of 7 s. [ABSTRACT FROM AUTHOR]

Islands must reach sustainable lifestyles by improving resources management and by getting accustomed to renewable energy sources. Culatra, a small Portuguese island, is actively increasing renewable energy penetration into local processes in order to be the first 100% sustainable Portuguese territory by 2030. Based on the electric consumption of Culatra, the objective of the present study is to project a photovoltaic unit composed of several sub-fields, each with a distinct orientation, in order to increase the self-consumption ratio while at the same time reducing the surplus of energy production, assessed by the self-sufficiency ratio criteria, resulting in a lower levelised cost of energy of the power system. To achieve this, MATLAB's implementation of a genetic algorithm was used to find the optimised set of orientations for a given load profile. The results indicate that it is possible to optimise the photovoltaic plant to reach a more continuous electricity generation through daytime, reducing the storage needs and increasing the value of photovoltaic systems. The method can be extended to other locations or demand curves, assisting on comparing different energy management strategies, and their respective advantages and disadvantages. [Display omitted] • Including different orientations to design a photovoltaic plant can shape its generation curve. • Doing so, the generation can better fit a given consumption. • Genetic algorithms are versatile and can be applied to solve complex global optimisation problems. • The principal component analysis helps understanding the links between the different PV performance indexes. • Extreme orientations favour optimised self-sufficiency and self-consumption. [ABSTRACT FROM AUTHOR]

As the proportion of renewable energy in electricity generation continues to increase, the uncertainty of renewable energy has brought significant challenges to power system security. Traditional renewable energy dispatching methods have less research on power system failure risk analysis due to economic considerations. In this paper, a renewable energy time series regulation strategy considering N-1 faults is proposed to improve the power system economy and security. In this strategy, by researching flexible load aggregation models, the time-series regulation model of aggregation loads is determined. Then the network N-1 security analysis divided into generator detection and branch detection is conducted. Determining possible N-1 faults of the system, the scheme minimizes the operating cost and grid risk. Adopting the methods above, the most desired renewable energy time-series regulation results are obtained. The results have shown that after adopting the proposed strategy in the improved system, the solar and wind curtailment volume is reduced by 38.10%, and the operating cost is reduced by 24.60%. In a daily cycle, the maximum power of all branch power overruns at the most risky moment is reduced by 20.36%, and the sum of the total power of all branch power overruns is reduced by 40.30%. • A renewable energy time-series regulation strategy is proposed. • A time-series regulation model of aggregation loads is established. • The grid failure scenario is considered in the new energy time series forecast. • The influence of N-1 faults during power system operation is considered. • The time series regulation strategy improves system benefit and security. [ABSTRACT FROM AUTHOR]

The hybridization of solar and biomass energy systems is a promising technology for mitigating the issues of energy generation-related greenhouse gas emissions and high energy prices. The global warming potential and economic feasibility of a hybrid solar-bioenergy system, comprised of a concentrated solar tower, biomass gasifier, thermal storage, and combined cycle gas turbine, have been evaluated by using life cycle assessment and cost benefit analysis, respectively. Sensitivity analysis is carried out to identify the hotspots of costs and emissions. The net present worth of the proposed system at the 30th year was calculated to be about €–0.7 billion. There are two suggestions to enhance the economic viability of the system, allowing for a payback period of less than 10 years. The first suggestion involves reducing the O&M cost of the system by 19% at 43.9 €/MWh, and the second suggestion entails increasing the overall efficiency of the system by 20%. This system can save 787.7 kg of CO 2 -eq/ton waste-wood and generate a total of about 0.8 million MWh of electricity each year. The findings provide scientific evidence for the design and deployment of the hybrid technology to enhance energy security, while reducing carbon emissions. Overall, this study highlights the potential benefits of hybrid solar-bioenergy systems and encourages the adoption of sustainable energy practices for a greener future. • Carbon footprint and economics of CSTGB-based electricity generation was explored • The CSTGB system generated 0.8 million MWh electricity annually • The CSTGB system saved 787.7 kgCO 2 -eq/ton waste-wood • CCS had the most significant impact on the carbon footprint • Operation and maintenance cost significantly affected economic viability [ABSTRACT FROM AUTHOR]

The concept of integrating cooling systems with photovoltaic-thermal (PVT) collectors is not new, although it has yet to be widely commercialized. Such systems have the potential to reduce building energy consumption since they can provide combined power and heat generation. Thus, the current work proposes an innovative water-based PVT system coupled with phase change material (PCM) capsules (PVT-PCM panel) and operating in both active and passive cooling modes to maximize the performance of photovoltaic panels in terms of power generation and thermal utilization. Unlike prior PVT systems, the current one achieves a higher electricity generation and heat storage capacity with a lower frictional power to meet the requirements for practical applications. Several sets of experiments were conducted in Cairo, Egypt, under real outdoor climatic conditions, to assess the overall performance of the PVT-PCM panel under various operating scenarios, with the results compared to those of a naturally air-cooled reference PV panel. According to the results, at 3 L/min cooling water flow rate, the actively cooled PVT-PCM panel achieved the highest electrical and thermal energy gain, translating to a maximum cumulative overall efficiency of 74.1%, compared to 34.6% and 12% for the passively cooled PVT-PCM panel and the reference PV panel, respectively. • PVT-PCM collector has been tested experimentally in both active and passive modes. • Water flow rates in the PVT-PCM with and without backside insulation were varied. • For Active PVT with and without insulation, cell temperature dropped to 7.45 and 6.3 °C. • The overall efficiency of active PVT can reach 74.1% at 3 L/min water flow rates. • The passive PVT lowers cell temperature by 3.76 °C and has 34.6% overall efficiency. [ABSTRACT FROM AUTHOR]

Coal power plants are crucial in both the power sector and central heating sector and also emit large amount of carbon dioxide. Existing research on coal power plants transformation mainly focused on their role in the power sector, with insufficient attention paid to their heat and power cogeneration capabilities. To address this gap, this paper proposes a long-term expansion joint optimization model for power sector and central heating sector incorporating the competitive technologies in both sectors, which is used to obtain the optimal low-carbon transition pathway of power sector and central heating sector, and analyse the pathway of coal power plants. China is selected for a case study for its largest scale of existing coal power plants in the world and urgent need of decarbonization. Compared to the scenario only considering electricity generation function from coal power plants to power sector, another scenario also considering the heating production to central heating sectors brings less than 5% increase in their remaining capacity, whilst results in significant changes in their regional distribution. Proportion of heat and power cogeneration of coal power plants in the heat generation structure is expected to increase first to 80% in 2030 and decrease to 58% in 2055. • A long-term optimization model for sectors of power and central heating is built. • Impacts of considering heating sector on coal power plants paths are quantified. • Proportion of coal power plants in total heat production increases to 80% in 2030. • Electric heat pumps are developed rapidly for negative carbon emission constraint. [ABSTRACT FROM AUTHOR]

The solution of an optimization-type power generation expansion planning model that endogenizes technology costs through the application of experience curves is highly dependent on the assumed values of the learning rate. Practical numerical models of this type derive a solution in which early diffusion of emerging technology, such as solar photovoltaic systems, leads to an intertemporal minimization of total electricity generation costs if the technology's assumed learning rate is above a particular boundary value; however, the principle behind this derivation is not well understood. This study aims to clarify the principle using a simple analytical model represented as an optimal control problem in addition to a numerical model. It identifies the factors influencing the solution as the discount rate and deployment rate at an initial time relative to the potential market share of the emerging technology. Analysis shows: (1) the higher the values of these two factors, the stricter the condition of learning rate required for the early diffusion of the technology to be optimal, holding other conditions constant; (2) the two factors have interaction effects on the optimal diffusion condition. Also, the study verifies the consistency of the results obtained from the analytical and numerical models. • Experience curves are endogenized in an optimal power expansion planning model. • Learning rate conditions are analyzed for deployment of solar/wind-power generation. • Dependence of the power technology choice on learning-rate assumptions is clarified. • Effects of the technology's initial market share and discount rate are identified. • Results consistency between numerical and simplified analytical models is confirmed. [ABSTRACT FROM AUTHOR]

Ethiopia's electric grid relies mostly on hydropower for electricity generation. Compared to metropolitan regions, rural areas have only 5% access to power, and 83% of remote areas rely on traditional biomass energy for lighting and cooking. Close to 60% of the land area in Ethiopia is pastoral, and electrifying from the main grid is a major challenge due to economic, technical, and nomadic reasons. This paper explores the feasibility analysis, design, and simulation of an off-grid solar Photovoltaic system in addition to discussing the complete engagement of national energy policy and a strategic plan for electrifying a pastoral Communities' in Borena. Using solar radiation base data from the National Aeronautics and Space Administration, a case study is performed at Moyale, Yabelo, and Dire, which have 454 households, 367 households, and 379 households, respectively. Through the HOMER software simulation, the optimization determines the inverter, battery size and number, and solar array's capacity. The daily energy usage and peak power demand in the pastoral communities of Moyale, Yabelo, and Dire were 498.102 kWh/day, 447.114 kWh/day, and 454.02 kWh/day, or 36.89 kW, 35.41 kW, and 35.68 kW, respectively. Due to the country's subsidizing of all clean energy costs, off-grid solar Photovoltaic systems are more economically feasible than diesel generators, which have a level cost of electricity of 0.4 US$/kWh. National energy strategic plans and policies ultimately support the full involvement of off-grid solar Photovoltaic electrification at remote sites. • The design, simulation, and feasibility study of an off-grid solar PV system are investigated. • The inverter, battery size, number of batteries, and solar array's capacity are determined by optimization using HOMER software. • The three locations, Moyale, Yabelo, and Dire, have significant solar resource potential. • The nation subsidizing electricity prices, solar PV systems are preferred, especially for pastorals living in remote places. • Off-grid solar PV electrification for selected sites was fully supported and viable by a national strategic plan and policy. [ABSTRACT FROM AUTHOR]

With its European Green Deal, the European Union (EU) aims to substantially increase renewable electricity generation and decrease greenhouse gas emissions in the electricity sector by 2035. European countries independently set these targets, but might not account for cross-border infrastructure interdependencies that may facilitate or impede their implementation. This study quantifies regional interdependencies among 36 European countries aggregated to eight regions by applying electricity sector modeling, Modeling to Generate Alternatives, tree-based ensemble method, and scenario discovery. Cost-effectively reaching EU targets in 2035 allows for flexibility in uptake of electricity system infrastructure across European regions, with few exceptions. Reaching EU targets with low costs requires high renewable capacities in Central and Nordic Europe and France, steep reductions of fossil fuel capacities in Central and Eastern Europe, keeping existing nuclear capacities in France, and high storage capacities in Alpine and Central Europe. Regional targets are most influential for increasing renewable capacities, while EU targets are most influential for decreasing greenhouse gas emissions. If EU targets are met, reaching regional targets of Central Europe and keeping nuclear capacities in France substantially reduce infrastructure requirements in Eastern Europe, highlighting the importance of regional cooperation for electricity system planning and policy. • EU targets allows for flexibility in new electricity infrastructure in Europe • Renewables in Central and Nordic Europe are cost-effective to reach EU targets • Regional interdependencies highlight the importance of cooperation across Europe [ABSTRACT FROM AUTHOR]

The current research is motivated to arrange an innovative hybrid solar-geothermal system, where the geothermal-driven subsystem is used to give out a sustainable framework for the upstream subsystems. Thus, an integrated geothermal flash cycle combined with organic Rankine cycle 1 (ORC1) is utilized to supply the input electricity of the compressed air energy storage system (CAES) at charging periods. The stored stream is exposed to electricity generation by the use of parabolic trough solar collectors (PTSCs). In addition, ORC2 recovers the waste heat of air turbines. A multi-aspect study is considered from the thermodynamical and economical standpoints. In addition, the sensitivity analysis is carried out to evaluate the effect of different parameters on the performance of the system. Moreover, four optimization scenarios are defined and scrutinized using a multi-objective particle swarm optimization (MOPSO) algorithm. The present study exhibits that the most appropriate optimum solution from the thermodynamic facet is a consequence of a framework in which the energy efficiency of flash-ORC1 and its output electricity is the objective functions. In this situation, the optimum energetic and exergetic efficiencies of the flash-ORC1 unit are equal to 20.43% and 67.63%. Furthermore, the lower optimum payback period equals 3.07 years corresponding to the scenario in which objective functions are the exergy efficiency of flash-ORC1 and the payback period. • Design of a novel hybrid solar-geothermal combined power plant utilizing CAES. • Conduct a coherent parametric study at charging and discharging periods. • Investigation of the proposed system from thermodynamic and economic viewpoints. • Considering four different optimization methods using MOPSO/TOPSIS/LINMAP. • Obtaining The best optimum exergy efficiency and payback period of 67.63% and 3.07 years. [ABSTRACT FROM AUTHOR]

An innovative valorization process for biomass waste treatment has been developed in this study. The basic simulation process developed considering experimental studies, and it has been optimized by application of a pattern search algorithm to obtain the optimum output of energy efficiency, economic performance, and process safety index (PSI). Mainly, three different scenarios have been analyzed based on the sustainability index (SI). These SI has been determined through energy, economy, safety, and electric power potential. According to the results of the SI, the optimized processes are more sustainable (SI = 0.517 to 0.563) in all scenarios as compared to the basic process (SI = 0.503). Similarly, the economic analysis in terms of internal rate of return (%) of the basic process varies from 37 to 2% when the process efficiency dropped from 100 to 80%, and it varies from 44 to 6% for the optimized process without any subsidy. The optimized process has a potential of 2788–4044 kW of electric power generation from thermal energy of the process while it is only 2302 kW for basic scenario. Therefore, the optimized process has better energy, economic, electric power, and safety performances, thus it is more sustainable as compared with the basic process. [Display omitted] • Integration of pyrolysis and gasification for biomass valorization. • Pattern search algorithm application for valorization process optimization. • A novel sustainability index has been proposed. • Electricity potential from optimized process thermal energy is 2788–4044 kW. • Energy efficiency of the processes varies from 46% to 66%. [ABSTRACT FROM AUTHOR]

Solar thermal devices with large installation areas represent technical, economic, and environmental challenges to design, construct, and operate them. Heat pump assisted with a solar thermal installation (STI) guarantee heat load supply at target temperature of a process, minimizing STI occupied area, environment impacts and associated costs. This paper deals with the design of two heat pumps, each one assisted with a STI. For designing solar network (which together the storage tank makes up the STI), lower irradiance levels than winter period are considered, guaranteeing continuous process operation. For designing each heat pump, two refrigerants with Ozone Depletion Potential of zero and Global Warming Potential of 7 (in one of them) are evaluated. This designing methodology is applied to a second-generation production of bioethanol case study. When heat is generated through a heat pump assisted with STI, the solar network absorber area is reduced by 85%, comparing with required area if only a STI produces heating. The same thing happens to generate electric power. Solar fraction value is one, 81,360 tons/year of not burned bagasse avoids 63,142 tons/year of greenhouse gases emissions. Still always guaranteeing the supply of energy to process, the impacts on environment and soil are minimized. [Display omitted] • Significant reduction of large solar thermal installation and storage system areas. • The cost of solar thermal energy is below the cost of fossil fuels. • Operation of the solar collector network under adverse irradiance conditions. • Profitable heat and power production from solar thermal energy plus heat pumps. [ABSTRACT FROM AUTHOR]

The Philippines is aiming to significantly reduce its carbon footprint by 75% by 2030 as part of its Nationally Determined Contribution. One way the country is focusing on achieving this goal is by making its domestic ferries emit zero emissions. To this end, the use of electrified and battery-powered vessels is being explored, especially for short sea shipping. A life cycle analysis of diesel-powered ships and battery-powered ships for five different energy sources for electricity generation was carried out using the GABI 2020 software. The results showed that the environmental friendliness of a vessel depends on the primary source of electricity generation. While electrified ships can be environmentally friendly, they are not necessarily better than diesel-powered ships, particularly if the source of electricity is coal or heavy fuel oil. Based on the data obtained from the Philippines, transitioning to battery-powered ships necessitates the expansion of the national grid and the utilization of natural gas as an interim solution, while focusing on renewable energy sources for the medium and long term. Sustainable infrastructures such as shore power and smart grids in ports are crucial during this transition. To expedite the process, implementing effective policies like pay-for-pollution principles and providing incentives such as carbon levies, low-risk loans, and state contributions are essential. • The analysis focused on evaluating the life cycle environmental impacts of hybrid vessels in the Philippines. • Underlying parameters for battery-powered vessels in the Philippines were identified. • The role of energy sources for power generation in reducing carbon emissions in shipping was investigated. • Policies and measures for the deployment of battery-powered vessels in the Philippines were proposed. [ABSTRACT FROM AUTHOR]

An adaptive proportional-integral control method (APCM) of a direct expansion photovoltaic-thermal heat pump (DX-PVTHP) system is proposed. First, the APCM was adopted and the proportional and integral factors were determined by experiments. Then, a universal engineering model combined the 10-factor model and temperature prediction model is built. The initial electronic expansion valve (EEV) opening during start-up under different working conditions is predicted and the EEV opening under dramatic irradiance changes is corrected under the APCM. Multiple experiments were conducted to evaluate the effectiveness of the APCM and test the performance of DX-PVTHP system under the APCM. The results reveal that the stability of superheat improved under typical cloudy skies and the maximum overshoot value was 3.2 °C. The overshoot time percentage of superheat was 27.54% with a decrease of 36.12% relative to the conventional control method. Moreover, the average coefficient of performance and photoelectric conversion efficiency were 3.51 and 13.25% in household mode, and 3.16 and 13.78% in commercial mode. Furthermore, the comprehensive coefficient of heating and electricity generation (CHE) is proposed to evaluate the comprehensive coefficient of the DX-PVTHP system. The CHE of the system was obtained 34.92% in household mode and 32.83% in commercial mode. • An adaptive control method for photovoltaic-thermal heat pump was proposed. • Engineering model was used to predict the opening of electronic expansion valve. • Comprehensive coefficient of thermal and electricity generation was defined. • Overshoot of superheat was determined less than 3.2 °C under typical cloudy skies. • CHE of system was obtained 34.92% in household and 32.83% in commercial modes. [ABSTRACT FROM AUTHOR]

In the Republic of Djibouti, due to increasing electricity demands, the government has planned to increase power supply by using renewable resources such as geothermal, solar and wind energy. This work presents the first wind resource assessment in the Republic of Djibouti using measured wind speed data for the period of three years by meteorological stations at eight locations. The results confirmed that three of the eight locations (i.e. GaliMa-aba, Ghoubbet and Bada Wein) have the best resource, with mean annual wind speeds of more than 6.0 m/s. Wind simulations using NCEP-CFSR and ERA5 models reanalysis shows that the seasonal variations are stable between different years and are broadly consistent with the observed wind speed. The feasibility of three wind farms with total capacity of 275 MW at GaliMa-aba, Ghoubbet and Bada Wein is examined. Using the WindPRO program and two commercial wind turbines in according to IEC 61400-1 design criteria, the electricity generation were technically assessed. These wind farms can produce 1073 GWh of electricity per year, approximately equal to Djibouti's expected average annual electrical demand in 2030. The economic evaluation using the present value cost (PVC) method estimate that the generation cost per kWh at these locations varies from 7.03 US.$ cent/kWh to 9.67 US.$ cent/kWh. • Wind energy potential in eight locations in the Republic of Djibouti is assessed. • CFSR and ERA5 models are used to investigate the interannual variability of wind. • Using WindPRO program the feasibility of three wind farms of 275 MW is examined. • The proposed wind farms will generate 1073 GWh/year of electricity. • The expected cost varies in the range of 7.03 US.$ cent/kWh to 9.67 US.$ cent/kWh. [ABSTRACT FROM AUTHOR]

In order to optimize the economic dispatching of the electric power system, this paper has proposed a new Hybrid Intelligent Algorithm based on the Particle Swarm Optimization (PSO) and Artificial Fish Swarm Algorithm (AFSA). Basing on a comprehensive dispatching optimization model with the goal of minimizing coal consumption, pollution emission and purchasing cost, we have utilized this Hybrid Intelligent Algorithms to solve the integrated weighted dispatching optimization model for five units and ten units respectively, considering the node flow balance of the power system, as well as the system's active power balance, positive and negative reserve constraints, transmission capacity constraints, unit output constraints, node voltage constraints, unit output power rise rate constraints, unit minimum runtime and downtime constraints, etc. The calculation results in the case study of five units are that coal consumption is 10,074.17 hundred-yuan, carbon emission is 11,280.75 kg, and electric power cost is 12,827.54 hundred-yuan. The calculation results in the case study of ten units, given a population size of 200, are that coal consumption is 31,305.45 hundred-yuan, carbon emission is 13,982.06 kg, and electric power cost is 16,754.79 hundred-yuan; while given a population size of 30, coal consumption is 29,221.16 hundred-yuan, carbon emission is 10,921.21 kg, and electric power cost is 16,521.56 hundred-yuan. Moreover, we have obtained the above results with an improvement of 35.56% in calculation efficiency. • An optimization model minimizing coal input, emission and cost was constructed. • A Hybrid Intelligent Algorithm based on the PSO and AFSA Algorithm was designed. • The calculation efficiency of two cases was improved 35.56% by the new algorithm. • The suitable range of population size for this new algorithm was determined. [ABSTRACT FROM AUTHOR]

This work presents a mathematical framework for optimizing water-energy nexus during shale gas production, processing, distribution, usage in power generation, and transmission of produced power. The framework entails a superstructure-based mathematical formulation. Regeneration is achieved using membrane distillation (MD), whereby the treated water can be reused at the next fracturing operation. The developed model incorporates a detailed design model of MD to account for the design specifications and energy requirements of the water regenerator. Hence, water, energy, operating and/or capital cost are optimized simultaneously. The study considers natural gas as fuel for commercial, industrial and residential customers, as well as for electric power generation, with the goal of maximizing the overall profit. The resultant model is applied to a case study, which is a representative of Marcellus shale play. The approach results in 23.2% reduction in freshwater utilization, 18.6% reduction in the freshwater cost and 42.7% reduction in the energy requirement of the regenerator. The energy requirement for regeneration is 160 × 103 kJ/m3 of water. The results indicate that the cost incurred in the network involving wet gas is 41.76% higher than the network involving dry gas due to the processing requirement of wet gas. • Tightness in schedule encouraged effective flowback water reuse. • Steady supply of gas to meet market demand due to tightness in fracturing schedule. • Significant reduction in the energy required by the regenerator using the approach. • The cost of shale gas production is the primal cost in the overall network. • The type of gas produced in a region has effect on the infrastructure development. [ABSTRACT FROM AUTHOR]

This article analyzes how productivity in the electric power industries (electricity, gas, steam and air condition supply) is affected through investments in R&D for OECD countries between 1995 and 2014. The accumulated R&D expenditures represent the current stock of knowledge or technology. Using a detailed input-output matrix for country-industry combinations allows us to distinguish between four types of spillovers: domestic own sector, foreign own sector as well as domestic and foreign other sector spillovers. The foreign spillovers we capture thus occur through the use of (imported) inputs from the electric power industries or from other sectors. Our estimates show that the productivity of the electric power industries is much more influenced by the transfer of embodied technology from other industries than by investments of these industries themselves. Countries with the highest stock of R&D are mainly responsible for these international technology spillovers. • We estimate productivity spillovers in the electric power industries through investments in R&D. • Spillovers from others sectors are more important that those from electric power industries. • Especially spillovers through imported technology raise productivity. [ABSTRACT FROM AUTHOR]

Wind power is one of the leading source of renewable energy in terms of installed capacity, power generation and technology maturity in the world today. It is promoted through financial support such as Feed-In Tariffs (FIT), renewable certificates, investment grants and tax incentives almost everywhere in the world. Attractive power pricing and a general global thrust for renewables have resulted in increasing the wind power capacity from 17 GW in 2000 to 514 GW in 2017. This paper analyses the relationship between financial mechanisms and wind capacity and wind power generation across 15 countries and 10 US states over 2006–2017. These countries/states contribute to 88% of total wind generation capacity in 2017, and contribution of their individual wind capacities to overall electricity generation rose from 0.15 to 24.2% (2006) to 1.2–38.5% (2017). Our analysis indicates that the trend of financial support reverses beyond an inflection point vis-à-vis the share of wind power in total power generated. The inflection point exists for all countries but the value varies across countries. The relationships are statistically significant. This has important policy implications with regard to the governments' approach towards promoting wind power as share of wind generation increases. • Correlation of financial support with wind generation and capacity. • Econometric model on financial support for wind across countries is dynamic in nature. • Existence of inflection point for financial support vis-à-vis share of wind generation. • The inflection point of wind share varies across countries. [ABSTRACT FROM AUTHOR]

In this study, an interval-credibility-chance constrained programming (ICCCP) method which is capable of handling uncertainties presented as interval and interval-fuzzy-random values existed in the energy-water nexus (EWN) system is developed. An ICCCP-EWN model is formulated for planning energy-water nexus system of Xiamen that is heavily relies on fossil fuels (e.g., coal is a main energy source). A set of probability and credibility levels related to energy-water availabilities, energy-water demands, and pollutant-emission mitigations are examined. Results discover that uncertainties have significant effects on the system planning strategies. System cost, heat generation, imported energy, and water supply would decrease with the raised probability level and increase with the raised credibility level. Coal-fired would be the main contributor to electricity generation; however, its proportion would reduce from [59.4, 59.9]% to [40.5, 41.8]%. Gas-fired would increase from [27.4, 27.6]% to [41.5, 43.9]% of the total electricity generation. Surface water would be the main water source, sharing more than 65% of the total amount. One of the major water users would be gas-fired electricity generation, increasing from [32.1, 32.6]% to [42.1, 44.6]% in future. These findings can provide useful information for the study city to adjust the existing energy and water planning strategies to achieve the goal of sustainable development. • An interval-credibility-chance constrained programming model is proposed. • Energy-water nexus system planning model is formulated for Xiamen, China. • Interval-fuzzy-random uncertainties can affect the planning policies. • The system transforms from coal-dominated to gas-dominated (over 40%). • Surface water would be main water source (over 65%) and gas would be main consumer. [ABSTRACT FROM AUTHOR]

Seasonal climate variations affect electricity demand, which in turn affects month-to-month electricity planning and operations. Electricity system planning at the monthly timescale can be improved by adapting climate forecasts to estimate electricity demand and utilizing energy models to estimate monthly electricity generation and associated operational costs. The objective of this paper is to develop and test a computationally efficient model that can support seasonal planning while preserving key aspects of system operation over hourly and daily timeframes. To do so, an energy system optimization model is repurposed for seasonal planning using features drawn from a unit commitment model. Different scenarios utilizing a well-known test system are used to evaluate the errors associated with both the repurposed energy system model and an imperfect load forecast. The results show that the energy system optimization model using an imperfect load forecast produces differences in monthly cost and generation levels that are less than 2% compared with a unit commitment model using a perfect load forecast. The enhanced energy system optimization model can be solved approximately 100 times faster than the unit commitment model, making it a suitable tool for future work aimed at evaluating seasonal electricity generation and demand under uncertainty. • An energy system optimization model is repurposed for seasonal planning. • Results are compared with a unit commitment model under two demand forecasts. • The enhanced energy system model can generate results nearly 100 times faster. • This model performance makes it possible to do seasonal planning under uncertainty. [ABSTRACT FROM AUTHOR]

Transition to low carbon energy system requires number of metals that are required in other sectors, have limited availability, produced mainly as byproducts in limited countries, and classified critical, which may shift energy system traditional geopolitics. China is main producer of several metals and one of their main consumers, which may have implications on their use in other sectors and in low carbon technologies in other countries. We aim at analyzing electricity generation technologies (EGT) in China, their metals requirements, and their global implications. Metals included are Ag, Te, In, Ge, Se, Ga, Cd, Nd, Dy, Pr, Tb, Pb, Cu, Ni, Al, Fe, Cr, and Zn. Dynamic material flow-stock model and seven energy scenarios are used, combined with material scenarios. Results indicates that most critical metals for energy system are Te, Cr, Ag, Ni, In, Ge, Tb, and Dy, however, technology advancements are expected to reduce risks associated with Ag, In, Dy, and Tb. Energy scenarios are difficult to realize without adequate supply of metals from primary sources, combined with increasing resources efficiency, recycling, and careful selection of technologies. Energy models used to produce these scenarios should include energy-material nexus. Biggest global implications expected for Ge, Te, Tb, and Dy. • Electricity technologies and their metals requirements in China are analyzed. • A dynamic material flow-stock model and seven energy scenarios are used in the analysis. • Te, Cr, Ag, Ni, In, Ge, Tb, and Dy are the most critical metals for Chinese energy system. • China high metals demands in energy sector may constrain their use in other countries and sectors. • Metals availability should be included in energy models due to their impacts on scenarios realization. [ABSTRACT FROM AUTHOR]

Growth of electricity generation from variable renewable resources like wind and solar has raised questions about future grid stability. This paper used several renewable energy penetration scenarios to determine when an electric grid might be more vulnerable to frequency contingencies, such as a generator outage. Unit commitment and dispatch modeling was used to quantify system inertia, an established proxy for grid stability. A case study of the Electric Reliability Council of Texas grid was used to illustrate the method. Results from the modeled scenarios showed that the Texas grid is resilient to major grid changes, even with relatively high penetrations (∼ 30% of annual energy generation compared to 18% in 2017) of renewable energy. However, retiring nuclear power plants and private-use networks in the model led to unstable inertia levels in our results. When the system inertia was constrained to meet a minimum threshold in our model, multiple coal and natural gas combined-cycle plants were dispatched at part-load or at their minimum operating level to maintain stable system inertia levels. This behavior is expected to expand with higher renewable energy penetrations and could occur on other electric grids that are reliant on synchronous generators for inertia support. [ABSTRACT FROM AUTHOR]

Our world's future is strongly connected to energy consumption trends. There are bi-directional relations between energy consumption and the average temperature of Earth, leading to positive causal loops. Increasing temperatures cause activity of more cooling systems most of which are electrified by burning hydrocarbons that consequently yield more carbon dioxide concentration and warmer climates. This paper is a trial to estimate the loop gain by employing a bottom-up regional model. The model is a spreadsheet containing sets of parameters and variables to estimate electricity used for cooling buildings in the residential and commercial sectors of 12 regions all around the world. The share of fossil-fuel based power plants determines each region's contribution to CO 2 emissions. Then, by processing data on the global emission trend and land temperature anomaly, a linear ARMAX relationship is estimated to compute the loop gain. The results show that, even in the optimistic scenario of IPCC (A1B), emission from cooling electricity will double up by the end of the century. With the estimated 1 + 1.4 × 10-6 loop gain, even if fossil-fuel electricity generation is gradually reduced to 40%, after a short fall, it will start growing again in the mid-century. • Electricity need for cooling buildings in summers is estimated for 12 world regions. • Carbon emitted by fossil-fuel power plants for the cooling electricity is estimated. • A linear model is used to relate emissions to the land temperature anomaly. • Loop-gain is estimated then by multiplying the two estimated coefficients. • The positive loop will bring up acceleration again even in optimistic scenarios. [ABSTRACT FROM AUTHOR]

Long term time series of variable renewable energy (VRE) generation and electricity demand (load) provide important insights into the feasibility of fully renewable power systems. The coverage of energy statistics is usually too short or the temporal resolution too low to study effects related to interannual variability or the impact of climatic extreme events. We use time series simulated from climate data to assess the frequency, duration, and magnitude of extreme residual load events of two fully renewable power scenarios with a share of VRE generation (wind and solar PV) of about 50% for the case of Sweden. We define residual load as load – wind – PV – nuclear generation. Extreme residual load events are events that exceed the balancing or ramping capacities of the current power system. For our analysis, we use 29 years of simulated river runoff and wind and PV generation. Hourly load is derived from MERRA reanalysis temperature data by applying statistical models. Those time series are used along with historic capacity and ramping restrictions of hydro and thermal power plants in an optimization model to minimize extreme residual load events. Our analysis shows that even highly flexible power systems, as the Swedish one, are affected by climatic extreme events if they increase their VRE shares. Replacing current nuclear power capacities by wind power results on average in three extreme residual load events per year that exceed the current power system's flexibility. Additional PV generation capacities instead of wind increase the number of extreme residual load events by about 4%, as most events occur during the winter month when solar generation is close to zero and thus not able to counterbalance low wind events. Contrarily, overproduction and the need to curtail VRE generation become more pressing with higher shares of PV. In the discussion we highlight measures that could provide additional balancing capabilities to cope with the more frequent and severe residual load events in a fully renewable power system with high shares of VRE generation. • Load during winter is negatively correlated with wind power and natural river runoff. • Annual residual loads vary between 51 and 72 TWh in a fully renewable power system. • Two out of three years exceed the balancing capacities of the current power system. • The longest extreme residual load event lasts 18 h with a maximum lack of capacity of 4 GW. • Additional flexibility measures can avoid loss of load events in fully renewable power systems. [ABSTRACT FROM AUTHOR]

This work demonstrated the possibility of bioelectricity generation using microbial fuel cell technologies from sugarcane molasses by a bacterial strain isolated from molasses. The strain identified according to 16S rRNA as Brevibacillus borstelensis STRI1. Sugarcane molasses could be used as a substrate in MFC, because of its high sugar content. When the bacterial strain was used as biocatalyst and sugarcane molasses as a substrate in MFC. The voltage increased rapidly over time recording 990 ± 5 mV in open circuit voltage (OCV), and 453 ± 6 mV in closed circuit voltage (1000 Ω) after 10 days of operation. The power density (P max) determined from the polarization curve, and it was 188.5 mW/m2 with an initial concentration of sugarcane molasses 1 ml (1632 mg/L as COD). While the coulombic efficiencies (CEs) ranged from 59.8 to 28.03%, related to initial concentrations of 0.3 ± 0.05 to 2.0 ± 0.15 g/L. The COD removal was determined and it was 11.7% after 5 days and reached to 81.7% by the end of the operation (30 days). These results suggested that bioelectricity could be generated from sugarcane molasses by Brevibacillus borstelensis STRI1. • Electricity can be produced from sugarcane as a substrate. • Brevibacillus borstelensis STRI1 could be used as a catalyst in MFC. • The power density increased by increasing sugarcane concentration. • Sugarcane degradation were elucidated through COD removal & electricity generation. [ABSTRACT FROM AUTHOR]

In this study, a M W -scale fuel-cell-based multi-energy hub system is simulated to maximize microgrid flexibility. The system was designed to deliver electricity, heat, and H 2 with a high energy efficiency, which can be realized through the integration of the exothermic phosphoric acid fuel cell and endothermic turboexpander generator modules. To extract additional useful work during the depressurization process in the natural gas supply chain, this multi-energy system is currently under construction on a pilot basis in South Korea. Based on a natural gas flow rate of 28,000 k g / h , we analyze the performance of the system and its economic effects under different load demands and operating conditions. The system simulation results show that the total electrical power generated by the turboexpander generator and phosphoric acid fuel cell modules is approximately 3.395 – 3.539 M W e , while the H 2 yield is 19.94 – 40.00 k g / h. In addition, an economic assessment of the multi-energy hub system is conducted based on the current natural gas, electricity, and H 2 prices in South Korea. Assuming a life span of 20 years for the turboexpander generator and phosphoric acid fuel cell modules, the payback period is estimated to be between 7.09 and 10.05 years. • MW-scale fuel-cell-based MEH system is modeled and simulated. • MEH system exhibits flexible hydrogen production and electricity generation. • Energy efficiency of the PAFC system has a tradeoff with hydrogen production. • Economic assessment is made based on current NG, electricity, and hydrogen prices in Korea. [ABSTRACT FROM AUTHOR]

Developing carbon-neutral bioenergy sources and bioproducts is an extraordinary opportunity for achieving an environmentally friendly economy. However, the overconsumption of resources in bioenergy and bioproduct production causes severe environmental concerns. The green biorefinery concept is one of the most attractive solutions for sustainably producing bioenergy sources and bioproducts. Seaweed is well-known as a promising green resource for biorefineries. Biorefineries based on seaweed not only produce various products but can also help solve macroalgal bloom issues. Nevertheless, a comprehensive environmental investigation should be performed before implementing seaweed-based biorefineries. Thus, using an environmental life cycle assessment, the current study examines three seaweed-based biorefineries. These scenarios include biogas production and waste valorization (Sc-1), bioethanol production and waste valorization (Sc-2), and biogas + bioethanol production and waste valorization (Sc-3). The results indicate that all the proposed scenarios offer environmentally friendly solutions for utilizing seaweed as a source of bioenergy and bioproducts. Sc-1 demonstrates the best environmental performance compared to the other two scenarios. Specifically, Sc-1 achieves a 99% and 97% reduction in total weighted environmental impact compared to Sc-2 and Sc-3, respectively. This finding is attributed to the avoidance of mineral fertilizers in Sc-1, resulting in a significant reduction in environmental impact. The electricity generation based on Sc-1 results in 1.91E-08 DALY/MJ of damage to human health and 1.65E-03 PDF.m2.yr/MJ of damage to ecosystem quality. Furthermore, the net weighted environmental impact of electricity generation based on Sc-1 results in 1.65E-03 EUR2003/MJ of damage, compared to 1.07E-01 EUR2003/MJ for grid electricity in the region. Therefore, replacing grid electricity with electricity generated from biogas in Sc-1 can reduce 98% of environmental damage. [Display omitted] • Seaweed-based biorefineries are environmentally scrutinized by life cycle assessment. • Waste valorization under the biorefinery has a key role in lowering environmental impacts. • Avoiding mineral fertilizers due to seaweed valorization reduces environmental impacts. • Biogas production under the biorefinery significantly reduces damage to the environment. • Seaweed-based biogas for electricity can reduce up to 98% of environmental impacts. [ABSTRACT FROM AUTHOR]

In spite of the fact that the solar power tower system is considered as one of the most valuable power generation facilities, it still faces challenges such as insufficient utilization of the solar salt temperature range and the dependence on high solar radiation intensity. To address this issue, an integrated recompression Brayton cycle and trans -critical regenerative organic Rankine cycle in parallel layout is proposed. The comparison with other literature shows that the specific work of the integrated system (147.8 kW/kg) outperforms the partial cooling Brayton cycle (130.1 kW/kg) under the same solar salt temperature range. In order to forecast future electricity generation and serve as a reference for plant operation, a power prediction strategy using neural networks is developed. Findings indicate that the integrated system can increase power production and maximize solar salt temperature utilization by adjusting the physical constraint strategy based on the changing temperature interval. Its equivalent work and thermal efficiency reach 12.7 MW and 38.36%, respectively, and it can recover the cost in 8 years. These results suggest that the proposed integrated system is a promising solution to enhance the performance of solar power tower systems with significant economic benefits. [Display omitted] • A two-stage power cycle to fully utilize SPT solar salt temperature range is offered. • Proposed system increases power production by adopting physical constraints. • The power cycle adopts low GWP and zero ODP working fluid. • The total specific work of the combined system surpasses the partial cooling cycle. • A BI-LSTM-based power generation prediction strategy of the system is developed. [ABSTRACT FROM AUTHOR]

The generation forecast helps to develop the scheduling plan of power sources, build a power balance system and ensure the adequacy of power supply to the power system at the macro level. Therefore, a novel structurally adaptive discrete grey Bernoulli model, called DHGBM(1,1), is proposed in this paper for the prediction of power generation. Firstly, the Hausdorff fractional order cumulative generation operation makes it possible to achieve new information prioritisation. As for the structure of the model, we have extended the nonlinear grey Bernoulli model with the introduction of a nonlinear dynamic structure term, which allows the model to simulate variable generation data and improves the adaptability of the model. In a comparative test of the algorithms, the well-performing differential evolution algorithm was used for hyperparameter optimisation of the model to obtain better predictive performance. Monte Carlo simulations and probability density analysis verified the excellent robustness of the model. In addition, through the simulation tests, we obtained a reasonable range of parameters for the structural terms, thus limiting the complexity of the model, and the phenomenon of model overfitting was effectively prevented. Finally, five actual cases of China's hydro, China's thermal, China's nuclear, China's wind power generation and China's electricity exports are predicted. • A novel nonlinear dynamic structural term is proposed. • A novel structural adaptive discrete grey Bernoulli model is developed. • The robustness analysis of the novel model is established. • Comparative study shows that the novel model is superior to other six models. [ABSTRACT FROM AUTHOR]

Coke oven gas is a by-product of the process of producing coke from coal and contains valuable compounds such as hydrogen and methane. In this study, an improved process was proposed for co-generation of power and LNG from COG with low CO 2 emissions and high energy and exergy efficiency. This proposed process includes: LNG Recovery Unit, Organic Rankin Cycle, and the power plant. The results of simulation showed that the exergy and energy efficiencies for this proposed process are 77.9% and 70.29%, respectively, which are considerably higher than other studies. It is found that the total exergy destruction of the proposed process is 4272.95 kW, and the power plant with 3118.1 kW exergy destruction has the largest share in total exergy destruction. Additionally, outcomes showed that ORC recovered 1205 kW of waste heat from compressor exhaust gases and produced 167.4 kW of power. Environmental analysis shows indirect carbon emissions for the proposed process is zero. The CO 2 emissions for the total energy and electric power generation were 0.0034 k g C O 2 / M J and 406 g C O 2 / k W h e l , respectively which are lower than coal or natural gas power plants. • A novel structure was proposed to produce power and LNG from Coke oven gas. • This proposed process includes LNG Recovery Unit, Organic Rankin Cycle and the power plant. • Using ORC made cooling utility consumption reach its minimum value. • The proposed process has low carbon dioxide emission. • The energy and exergy efficiencies are 70.29% and 77.9%. [ABSTRACT FROM AUTHOR]

The dynamic performance (or flexibility) of the combined heating and power (CHP) unit operating in a heat-led mode is restricted by the strong interdependence between electricity generation and thermal generation. This paper proposes a method that balances the flexibility and the heating quality using a coupled two-timescale model predictive control (MPC) scheme. The indoor temperatures of thermal users are regulated in a comfort region by a slow timescale MPC using zone control; a fast MPC is used as the coordinated control system (CCS). The two controllers are coupled in that both controllers use the extraction steams as their controlled variable. In this way, the dynamic flexibility of the CHP unit is improved by utilizing energy buffers from district heating systems and buildings. The proposed scheme is verified using a simulation study on a real heating system with 2 CHP units, 28 thermal nodes, and 58 pipelines. The result shows that the dynamic performance of the system is improved considerably while the temperatures of thermal users remain in their comfort regions. [Display omitted] • An MPC scheme is proposed to optimize the dynamic flexibility of CHP systems. • Two coordinated MPC controllers are used to solve the problem. • Zone control is used in order to give more room for electrical power control. • The method is verified using simulations of a CHP system. [ABSTRACT FROM AUTHOR]

Owing to slowly lessening of fossil fuel, economical use of obtainable fuel for electric power and heat generation has turn out to be an important worry of utility industries. In this manuscript, fuel constrained combined heat and power unit commitment incorporating renewable energy sources and electric vehicle parking lot is undertaken for addressing the optimum generation scheduling of the committed units. Here thermal generating units (TGUs), cogeneration units (CGUs), heat only units (HOUs), cascaded hydro power plants (CHPPs) and solar PV plants (SPVPs) and wind turbine generators (WTGs) are considered. A number of plug-in electric vehicles (PEVs) with charging and discharging behaviours is also considered. The problem is solved with and without fuel constraints. The UC problem is solved by using binary differential evolution (BDE) along with priority list (PL). Numerical results of the test systems are included to provide valued minutiae for operational and planning problems. [Display omitted] • Fuel constrained combined heat and power commitment scheduling has been studied. • Cascaded hydro power plants, solar PV plants, wind turbine generators are considered. • 50 000 PEVs have been incorporated with both G2V mode and G2V/V2G modes. [ABSTRACT FROM AUTHOR]