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This paper studies the production decisions of a power plant with two different risk attitudes, in which the power plant faces the risks of uncertainty in renewable energy production, and two types of risk attitudes are considered, namely, risk neutrality and risk aversion. First, we construct the optimization models of a power plant with two different risk attitudes under the Feed-in-Tariffs (FIT) policy, and obtain the optimal outcomes by solving the models, including the optimal output and the expected profit. Then, by comparing the optimal outcomes under the two risk attitudes, we reveal the impacts of the different risk attitudes of power plants on their power production decisions. In addition, we also give an extended study to analyze the change from the FIT policy to the market-oriented Tradable Green Certificates (TGC) policy. The results show that the expected profit of the power plant decreases if it switches from risk-neutral to risk-averse, and the fossil energy output of the risk-neutral power plant is higher than that of the risk-averse power plant if the difference between the levelized costs of renewable energy and fossil energy exceeds a certain threshold. [ABSTRACT FROM AUTHOR]

The accuracy of models to capture the uncertainty of renewables significantly affects the planning and operation of renewable energy-based stand-alone (REB-SA) microgrids. This paper aims to first study different stochastic and deterministic models for renewables, then evaluate the performance of an REB-SA microgrid planning problem and provide qualitative and quantitative comparisons. A modified Metropolis-coupled Markov chain Monte Carlo simulation is considered for the first time in the planning of an REB-SA microgrid to predict the behavior of renewables with minimum iterations. The modified model is benchmarked against two prevalent models including the retrospective model with worst-case scenarios and the Monte Carlo simulation. The operations of three designed microgrids (by these three methods) are evaluated using the last three-year historical data of a city in northern Sweden including solar radiation, wind speed, the water flow of a river, and load consumption. The impacts of the considered methods on using PV panels and hydrogen systems are investigated. The results verify that the modified model decreases the risk of planning and operation of an REB-SA microgrid from the energy and power shortage viewpoints. Moreover, the designed microgrid with the modified model can cope with all possible scenarios from economic, technical, and environmental viewpoints. • Uncertainties of renewable energy are major concerns for replacing fossil-fuel energy. • A modified Metropolis-coupled MCMCS is applied to the microgrid planning problem. • Uncertainty modeling methods on microgrid planning and operation are benchmarked. • Microgrid planning is highly affected by different uncertainty modeling methods. • The planning results besides the benchmarks show economic and reliability improvement. [ABSTRACT FROM AUTHOR]

Nowadays, the local distribution grids have been facing technical, economic, and regulatory challenges, because of the increased integration of renewable energy sources (RESs) and electrification of vehicles. The traditional solutions to the grid expansion, e.g., to build an additional power line, are utility-centered solutions, i.e., the distribution grid operators (DSOs) are the only party involved to tackle grid issues. The DSOs have to engage grid users with technology providers to develop innovative solutions that tackle one problem and overcome several cost-effectively. This paper presents a holistic solution to optimally control cross-sectoral energy flow between interconnected microgrids (MGs) consisting of different RESs, hydroelectric power plant (HPP) and wind turbines (WTs) to meet electric vehicles (EVs), residential, commercial and industrial demands with the main grid contribution. This issue will provide the advantages of community-based MGs for local energy trading which causes for an active and engaged system, however, an adequate control strategy for proper operation is required. The proposed solution is based on a new interconnection line between two MGs through a multiport converter (MPC) with the techno-economic consideration of newly installed components such as MPC, cables and the required battery energy storage system (BESS). The proposed case study is evaluated under three different conditions e.g., load increment, demand response (DR) and N-1 criterion in separate, interconnect and island modes. The CPLEX solver of GAMS software is employed to solve the mixed-integer linear programming model. The results show that the applied interconnection line for MGs compared to the separated operation mode can decrease the system's total costs, reduce the applied peak to the upstream grid, and enhance the system's reliability under different conditions. Furthermore, the applied solution provides the ability for MGs operation even in island mode under different conditions for a full day (24 h). • Minimizing OPEX and CAPEX costs under load variations, N-1 criterion, and DR. • Optimal BESS sizing for separate, interconnect and island conditions in MGs. • Optimal MV cables cross-section size for new interconnection line between MGs. • MPC Sizing for more functionality to Host EVs and BESS in interconnected MGs. [ABSTRACT FROM AUTHOR]

Hybrid platforms composed of a floating offshore wind turbine (FOWT) and wave energy converters (WECs) may possibly reduce the levelised cost of energy of both energy harvesting devices and improve the platform dynamics. This paper investigates the dynamics of a hybrid platform composed of a semi-submersible FOWT combined with three spherical heaving point absorbers (PAs), either floating or submerged, under turbulent wind and irregular waves conditions. Since the WECs are attached to the floating structure, complex hydrodynamic couplings occur between the floating bodies. In this regard, a parametric investigation of the power-take-off system is performed to understand the wave power absorption and motion characteristics, which are compared against their respective stand-alone configurations. At sea states with short wave peak period, both hybrid platforms (with floating or submerged PAs) were able to operate under maximum wave power absorption condition and extract nearly the same amount of wave energy as the PAs attached to the ground (stand-alone), while providing the additional benefit of reducing the horizontal nacelle accelerations of the FOWT. On the other hand, when operating at sea states with long wave periods, the hybrid platforms may need to restrict the wave power absorption capability to prevent additional nacelle horizontal acceleration. • Analyses the dynamics of two hybrid platforms under random wind and wave loads. • Provides insights on the performance and nacelle acceleration of hybrid platforms. • Presents a critical comparison of power and motion compared to standalone platforms. • Presents a sensitive analysis of the power take-off coefficients of hybrid platforms. [ABSTRACT FROM AUTHOR]

Hydroelectric power plants have been losing competitiveness to renewable resources in Brazil, specifically wind and solar power resources, given the current water crisis in the country, which has left main reservoirs in the Brazilian hydroelectric power system depleted. However, other renewable energy resources show disadvantages in terms of intermittence and energy storage. Pumped Hydropower Storage (PHS) can help mitigate this problem, supplying energy with fewer variations. This paper studied using PHS concepts together with solar and/or wind renewable resources to recover water levels at the Furnas reservoir in terms of energy and economic performance. The energy studies were developed by sizing the PHS and identifying solar and wind resource potential for supplying energy for pumps in the hydropower plant. The economic analyses considered three different scenarios (I; II and III), and used the NPV (Net Present Value), and LCOE (Levelized Cost of Electricity) methods for a period of 30 years. Energy calculations showed that 1692 MWh/day of energy could be generated using PHS. However, 2729 MWh/day of energy would be needed to store generated energy, and a 1037 MWh negative energy balance will be compensated for by using daily wind and/or solar photovoltaic power production. This would allow the Furnas reservoir to regain 0.45 m of its water level per year. The economic studies showed economic viability for PHS scenarios I and III, with estimated NPV at 151.5 million dollars, and 64.5 million dollars for the last year of the project, respectively. Scenario II was unviable, giving rise to several strong discussions on this application within Brazil. • Wind and solar sources were considered for the pump energy supply. • The proposed system can recover 0.45 m/year of the level in the Furnas reservoir. • The energy production of the reversible power plant was estimated as 1,692MWh/day. • Economic feasibility was evaluated in many scenarios using NPV and LCOEmethods. • Market regulation is required for the diffusion of this technology in Brazil. [ABSTRACT FROM AUTHOR]

The energy communities based on the integration of microgrids make it possible to gain economic, environmental, technical, and social benefits. The paper aims to propose a unified multi-criteria approach covering both the planning stage and the stage of managing the energy community, in the context of various interests of its participants. Planning stage should take into account the long-term goals of the community and possible changes in external conditions. Therefore, we suggest an approach relying on the multi-attribute value theory considering the uncertainty of decision makers' preferences. Interval estimators used to express preferences enable a choice of community configuration with robust performance under changing conditions within some limits. In the operation stage, the new multi-criteria model of an intelligent "energy community operator" is proposed. It is based on bi-level programming and reinforcement learning, implementing the structure of a fair local market for sustainable development of the community. To optimize the operation of individual microgrids within the community, the multi-objective Monte-Carlo Tree Search (MCTS) algorithm is used, which helps to improve the convergence in the Stackelberg game. The multi-criteria version of the MCTS algorithm allows implementing an adaptive local automation model to solve a multi-objective lower-level problem: minimize operating costs, risk of power shortage, and CO2 emissions; smooth load peaks, and optimize power exchange between microgrids. At the top level, a management strategy that will be beneficial to all members of the community is chosen to guarantee their long-term aggregation. The effectiveness of the proposed approach is demonstrated by the example of an energy community created for three remote villages located on the coast of the Sea of Japan. The natural and climatic conditions of the area allow the efficient use of wind, solar, and biomass resources. Building the community involves the consideration of three scenarios, in which priority is given to economic efficiency, environmental efficiency, or balanced development. • The practical multi-criteria approach for development a sustainable energy community. • Energy community sizing under uncertainty of decision makers' preferences. • Bi-level programming for a "fair" community operator model. • Monte-Carlo Tree Search algorithm for multi-criteria community management. [ABSTRACT FROM AUTHOR]

Distributed energy systems are becoming increasingly popular worldwide. The 100% renewable energy system can be an important energy supply alternative to reduce the carbon emissions and address energy shortage, especially for remote areas. However, the performance of 100% renewable energy system (RES) at community level needs further detailed analysis, which is affected by the climates, availability of renewable energy and local energy markets. This paper proposes a design optimization framework of 100% renewable energy systems for low-density communities and investigates the system performance. To investigate the integration and performance of 100% RES, thirty typical cities located in different regions of China were chosen considering different climates, geographical features, and renewable energy distributions. By taking the economic performance as the optimization objective, the optimal design for the 100% RES is obtained, and the energy and economic performance is analyzed. Results show that, under the current energy market conditions, the 100% RES is feasible for low-density communities in most regions of China. The payback periods of the systems in most cities are less than six years. When the cost of PV is reduced by half considering future technological developments, the payback period of a 100% RES can be reduced by 30%–60%. This paper would provide design suggestions and application recommendations in regard to promoting 100% RES in China. • Application of 100% renewable energy system at community level is studied. • 30 zones are selected considering climates, renewable energy sources and markets. • Solar energy and biomass can contribute to over 90% of the total energy supply. • Investment of 100% RES can be paid back in 6 years for most regions. • Payback periods can be reduced by 30%–60% when PV technology is further developed. [ABSTRACT FROM AUTHOR]

The paper proposes an innovative power-sharing model, i.e., a power-system architecture for aggregation of users able to share the power produced by common generators and energy services. The model is suitable for both multi-tenant buildings and groups of multiple buildings and it is applicable for both existing and new buildings. It is scalable for larger systems and suitable for an easier integration with storage systems. The novel principle of the model is that the energy produced by common generators can be shared among the end-users in a unidirectional way, so that each user remains passive towards the distributor, except a single active user that assumes the role of balance node. This key feature allows for easily implementing the model in all the residential and tertiary multi-units buildings in full compliance with national regulations, with the adoption of power sharing contracts as well. This paper discusses the feasibility of the model through a dynamic Matlab/Simulink model, which is used to show its effectiveness in several case studies. The significance of this work consists of approaching the energy sharing in buildings with a completely new strategy, based on an innovative system architecture that can be effectively implemented. • Innovative democratic power-sharing model for building and energy communities. • It allows for aggregation of users. • It allows to share the power produced by common generators. • Each user remains passive towards the distributor. • The model can be implemented in all multi-units buildings. [ABSTRACT FROM AUTHOR]

Tremendous development and integration of intermittent renewable energy resources have forced the hydraulic turbines to experience transient processes more frequently and thus endangered the stability of the machine. The principal objective of this paper is to present the numerical investigation into load rejection towards a high-head model Francis turbine based on the structured overset mesh, which provides greater flexibility over the standard mesh techniques and adequate mesh quality during the movement of the guide vanes. The numerical results show good agreement with experimental measurements. The formation and evolution process of the vortex rope in the draft tube are elaborated by the velocity invariant Q and the swirl number S reaching its maximum value due to the formation of precessing vortex rope. Evidence is presented which shows that significant influence of the rotor-stator interaction is captured, and the pressure fluctuation amplitudes caused by the changing of angular position of guide vane are also powerful. Furthermore, the velocity profiles in axial and radial imply that an increasing recirculating flow region is developed at the center of the draft tube during the transient process. The findings presented in this paper enhance the insight into transient features of load rejection process. - Load rejection process was simulated through the structured overset mesh technology. - Dynamic characteristics during load rejection was analyzed. - Formation of processing vortex rope was presented. [ABSTRACT FROM AUTHOR]

At present, energy represents a key element in the social and economic development of a territory. This is particularly true for fragile territories that are not interconnected, such as small island states. As is true for many of the Small Island Developing States (SIDS) worldwide, the energy situation of the Comoros is substantially based on fossil fuel imports. The socioeconomic development of this archipelago is overwhelmingly dependent on energy security from sustainability, availability and affordability perspectives. As a forward-looking response to energy vulnerability, the deployment of renewables to diversify the generation of electricity appears to be an essential prerequisite for guaranteeing a sustainable future. Nevertheless, despite a high potential for renewable energy, only 3.8% of the electricity supply in the Comoros is provided by hydropower. This paper provides a comprehensive overview of the energy situation throughout the Comoros and focuses on renewable energy opportunities to facilitate the supply of green power. This study ultimately shows that renewable energies are rarely exploited despite the powerful potential of different resources. Finally, this paper attempts to provide recommendations for the Comoros to pursue a more sustainable future. • Analysis of the current energy situation of Comoros. • Defining renewable potential and ongoing actions. • Analysis of the specific barriers and policy to the development of RES in the Comoros. [ABSTRACT FROM AUTHOR]

The deployment of intermittent renewables in distributed energy systems has to be managed so as to maximise local energy self-consumption. This paper deals with the application of sector coupling strategies to increase energy self-consumption and decarbonise urban energy districts. The aim of this work is to investigate the combined implementation of Power-to-Gas and Power-to-Heat strategies in Renewable Energy Communities. Power-to-Power, Power-to-Heat and Power-to-Gas systems, along with their combined adoption, have been implemented in a residential community under different renewable excess conditions. For each strategy, the storage system's size has been optimised and the configurations have been compared in energy, environmental and economic terms. The Power-to-Heat strategy is the most cost-effective solution, although it presents intrinsic limitations. The Power-to-Gas configuration involves the hydrogen injection into the gas grid, thus exploiting the local network as a free storage system. Higher self-consumption can be achieved; nevertheless, energy and emissions savings are lower due to the electrolyser poor efficiency. The combined application of the two sector coupling strategies allows the strategies individual advantages to be exploited and the limitations of both to be overcome. Furthermore, this solution leads to higher self-consumption and lower annual costs than conventional electric batteries. • Sector coupling strategies for improving self-consumption in energy communities. • Combined implementation of Power-to-Heat and Power-to-Gas systems. • Analysis of energy storage systems in two renewable excess conditions. • Assessment of energy, environmental and economic impacts. • Self-consumption based tariffs in accordance with the Italian incentive scheme. [ABSTRACT FROM AUTHOR]

The exploitation and utilisation of solar energy is challenging because of both diurnal and seasonal variation. Seasonal thermal energy storage is a prominent solution to solve the problem of seasonal variation of solar production. This paper investigates both the optimal design and energy management of a renewable energy plant with seasonal thermal energy storage. As a case study, the thermal, cooling and electrical energy demands of a university campus during one year are considered. Three scenarios, characterized by a different available area (20,555 m2, area covered at present; 50,000 m2, potentially available area by exploiting the entire rooftop and parking area; unlimited area) for solar thermal collectors and photovoltaic panels are investigated. In the first two scenarios, the exploitation of solar energy allows a primary energy saving of 31% and 57%, respectively compared to the use of a conventional plant. The seasonal storage reaches an overall efficiency (thus considering both charging and discharging) up to 84%. Finally, the analysis of the third scenario shows that the feasibility of meeting the energy demands by only exploiting solar energy is technically challenging because a large area equal to about 100,293 m2 is needed for solar thermal collectors and photovoltaic panels. [ABSTRACT FROM AUTHOR]

In order to mitigate the influence of global warming and greenhouse gasses emission, different proceedings are suggested such as utilizing renewable energies and demand response programs. This paper investigates the expansion of renewable resources and electrical energy storage units in distribution systems towards reducing investment costs and environmental pollution. Since the development of components is not possible in a single-stage due to the limitation of staff and funds, a multi-stage programming is applied to consider various restrictions. According to the penetration of crypto-currency miners in recent years, their impact is evaluated on the problem as the high-rate energy consumers. Moreover, the demand side management strategy and risk-averse scenario-based approach are implemented to analyze the role of responsive loads and model the renewable resources uncertainty, respectively. The results approve that simultaneous expansion of wind turbines, photovoltaics and electrical storage systems decreases the total pollution and cost by 100% and 99.98% after the third year, respectively. The simulations also validate that crypto-currency miners reduce the total revenue by 4.16%, whereas the responsive loads increase it by 9.89%. As well, the fluctuations of wind and solar power decrease the total revenue by 13.27%, in return, the robustness notably improves. [ABSTRACT FROM AUTHOR]

The sustainability of economic growth has recently become a major objective for the global economy. Innovation is a newly emerged key factor for an efficient energy market and sustainable development. It can reduce pollution by increasing production efficiency (the first effect of CO 2 e reduction) and direct involvement in renewable energy development (the second effect of CO 2 e reduction) by replacing fossil fuel instruments with their counterparts that rely on renewable energy. The main question of this research is: Will the impact of innovation on per capita CO2e be the same on a threshold with different levels of renewable energy consumption? This paper explores the impact of innovation on CO 2 emissions in a panel of 29 selected EU countries from 2000 to 2019 using the fixed-effect panel threshold model. The results indicated that innovation had a significantly negative effect on per capita CO 2 e. In the early levels of the use of renewable energy, innovations have been directed more towards clean energy (the second effect on CO 2 e). Innovations were directed more towards clean energy in using renewable energy at early levels. It can be concluded that this policy has led to more innovation in clean energy production and more use of renewable energy, thus reducing CO2e considerably (the second effect). [ABSTRACT FROM AUTHOR]

Globally, renewable energy technologies, such as solar photovoltaic (PV) contribute significantly to sustainable development. However, adoption of solar PV is limited in many developing countries. Governments have rolled out policy strategies like financial inclusion to stimulate deployment of modern energy technologies. Notwithstanding, little is known about financial inclusion and household solar PV adoption. Using two waves of Uganda National Household Survey data covering 28,913 households, this paper examines the effect of financial inclusion on adoption of solar PV. The study employed logit model and pooled ordinary least squares for estimation. Taking endogeneity into account, we find that financial inclusion has a strong positive effect on solar PV adoption. The estimates show that unit increase in financial inclusion increases the likelihood of residential solar PV adoption by 3.6% (p < 0.01). This finding is consistent across all robustness checks. The findings further suggest that use of mobile money is more important for solar PV adoption. The study identified household income and education as possible pathways through which financial inclusion influences solar PV adoption. Thus, policy makers and renewable energy practitioners should continue prioritizing financial inclusion particularly use of mobile money and financial remittances so as stimulate adoption of solar PV. • The link between financial inclusion and adoption of solar PV in Uganda is examined. • The National Household Survey data for Uganda and logit regression model were used. • We found that financial inclusion increases adoption of solar PV in households. • Income and education are pathways by which financial inclusion affects PV adoption. • Policy on financial inclusion should prioritize use of mobile money and remittances. [ABSTRACT FROM AUTHOR]

— Seasonal and location dependence of renewable energy resources have limited their applications in power generation. Energy storage systems are promising solutions to the intermittence of renewable energy resources. Rural electricity grids are faced with economic sustainability challenges due to low power demand and poverty. A rural grid design around economic drivers like agriculture and micro industries can mitigate poverty and improve economic sustainability of rural grids. This paper presents an integrated design for photovoltaic power generation with a pumped hydro storage system for irrigation and community utilization. The design explored the natural availability of water body in an elevated settlement area that offers a natural storage height for hydro energy storage. A photovoltaic generation plant was designed to power a pump as a turbine system for water storage and generation. HOMER® energy simulation software was deployed in the simulation. The result shows a satisfactory net present cost for the possible integration of a pumped hydro storage system in a photovoltaic generation plant as the most viable option to provide power at a power supply probability of 99.9% and water for irrigation. The benefits from the irrigation and water supply will enhance the community's socio-economic development and sustain the investment. [Display omitted] • We proposed a strategy to help an African community to have access to electricity. • The scheme will provide irrigation facilities and water supply to the community. • Photovoltaic Generation System was deployed as the primary energy source. • Intermittence of renewable energy was addressed through pumped hydro storage. • The result shows a satisfactory net present cost and 99.9% power supply probability. [ABSTRACT FROM AUTHOR]

This paper introduces a flexibility concept in development of a novel multigeneration energy system driven by a renewable energy heat source. Nevertheless, the energy system can be upgraded to a highly productive system by incorporating other subsystems for achieving more production such as domestic hot water and freshwater. A novel design is proposed for a system comprising organic Rankine cycle, absorption compression heat pump, liquid natural gas to natural gas converting system, domestic water heater, and humidifier-dehumidifier desalination to exploit the Sabalan geothermal source for multigeneration purposes. Due to its high-efficient and environmentally friendly characteristics, n-pentane is utilized in the organic Rankine cycle. Also, the Ammonia-water is employed in the absorption compression heat pump subsystem. Energy, exergy, and thermoeconomic analysis is conducted on the plant along with multi-objective optimization based on the parametric study of key variants. According to the results, the novel step-by-step flexibility analysis can give a wide viewpoint to the designers to make the best multiple plant. The results of multi-objective optimization indicate that the freshwater production increases from 0.803 kg/s to 0.834 kg/s, the capacity of the domestic water heater rises from 1254 kW to 1265 kW, and the net output power surges up by 137.96 kW. However, the heating production falls from 1276 to 1088 kW. Furthermore, the total energy and exergy efficiencies increase by 6.43% and 4.47% with a 2.08 $/GJ reduction in the unit cost of the product. [ABSTRACT FROM AUTHOR]

In the context of sustainable development, the renewable energy technology innovation (RETI) may have a potential impact upon the industrial structure upgrading, while green finance will play a moderating part. This paper studies the role of green finance and renewable energy technological innovation on industrial structure in China. We found that RETI has contributed significantly to the adjustment of industrial structure. The research results of PVAR (Panel Vector Autoregressive) model further prove this dynamic and continuous positive promotion. The threshold regression results indicate that with the improvement of green finance, there is a non-linear relationship between RETI and industrial structure. In areas where green finance is relatively low, RETI can inhibit the upgrading of industrial structure. When the degree of green finance development is relatively high, the influence of RETI on industrial structure is remarkably positive. Heterogeneity analysis shows that in eastern China, renewable energy technological innovation has significantly promoted the industrial structure upgrading. Therefore, policy makers should take various measures to expedite the green finance development and strengthen the green finance support to renewable energy technology innovations. Chinese government has the need to continue to implement related green credit policies and expand the source of green funds. • Study the impact of renewable energy technology innovation on industrial structure. • Green finance is a moderating variable. • Threshold regression model is used to study nonlinear relationship. • Renewable energy technology innovation positively impacts industrial structure. • Green finance has a positive moderating effect. [ABSTRACT FROM AUTHOR]

To fully exploit the use of water/nanofluids in the photovoltaic thermal (PVT) unit condenser and further increase renewable energy resources in energy mix, the current paper numerically studies the effect of operating water/PVT unit, Al 3 O 2 -water/PVT unit and Ag-water/PVT unit on the overall performance. In the ANSYS Fluent 18, the mathematical equations related to these models were discretized by the second order upwind scheme and solved at steady state, considering the fluid inside pipe as laminar flow. The results were obtained and discussed in terms of coefficient of performance (COP), Nusselt number (Nu), specific exergy (E in,out) and outlet flow temperature (T out), at different nanoparticle fractions and operating conditions of both flow and weather. A higher inlet mass flow rate of nanofluids (Ag-water and Al 3 O 2 -water) was recommended both for better COP and handling nanoparticles deposition problem. In addition, due to thermal conductivity difference, the maximum COP of about 3 was achieved from PVT unit condenser with Ag-water as fluid medium. The optimum conditions of flow and weather were proposed for the operation of three considered PVT units condenser. [ABSTRACT FROM AUTHOR]

In 2020 the European Commission approved the GND (Green New Deal), a strategic plan aimed at the decarbonization of the EU by 2050. In this scenario, the diffusion of alternative renewable energy sources (RESs) play a key role, particularly electric energy production from wind and photovoltaic power plants. Regardless, the nonprogrammable nature of these power sources led recent studies to focus the interest on the power-to-gas solution (PtG), consisting of the electrolytic transformation of excesses of unused electric energy into hydrogen. The complexity of this technology requires the development of strategic optimization models aimed at finding the best locations for new PtG plants in specific territorial scenarios. This paper presents the development of a GIS-based optimization model that combines an operational research approach with territorial services based on geographic information system (GIS) data. The study is located in Sicily (Italy), considering the large renewable energy penetration in the larger Mediterranean island. The developed model allows us to find the best location for new PtG installations in the considered area by combining GIS automated processing with cost function resolution. The results of this work could be useful in the years to come in light of the rapid spread of hydrogen energy production in Italy. [Display omitted] [ABSTRACT FROM AUTHOR]

Although the socio-economic determinants of terrorism are conducted by many researchers using different samples and time spans, the impact of renewable energy consumption on terrorism has been ignored for a long time. To bridge the gap, this paper aims to investigate the impact of renewable energy consumption on terrorism regarding economic growth, non-renewable energy consumption, and income inequality over the period straddling 1990 and 2019 for a panel of the USA, China, India, Iran, Germany, and Russia. We employ the CUP-FM and CUP-BC estimators to reveal the long-run relationship between variables. The empirical findings suggest that renewable energy consumption has a negative impact on terrorism. A 1% increase in renewable energy consumption decreases terrorism by 0.315% and 0.631%, according to the CUP-FM and CUP-BC estimators, respectively. Economic growth also has a negative impact on terrorism, whereas non-renewable energy consumption and income inequality positively affect terrorism. Our empirical findings highlighted that renewable energy consumption and economic growth are crucial for combating terrorism in these countries. Therefore, these countries need to improve comprehensive policies in terms of renewable energy consumption and simultaneously decrease non-renewable energy consumption and income inequality. • Renewable energy consumption helps to lower the terrorism index. • Inequality of income expedites the rise of terrorism. • Terrorism is exacerbated as a result of fossil fuel consumption. [ABSTRACT FROM AUTHOR]

Super-hot rock geothermal is an emerging source of renewable and carbon-free energy. This paper is the first attempt to explore fluid and heat flow dynamics in the reservoir-wellbore coupled system, to assess the power generation performance of a super-hot (>450 °C) enhanced geothermal system (EGS). We developed a high-performance code and built a 3-D wellbore-reservoir coupled model based on data from a recently completed deep-drilling project at Larderello, Italy. The general pattern of the super-hot EGS is characterized by a significant temperature plummet (>60 °C), after which the production fluid evolves from steam to a two-phase mixture till the end of the operation period. Reservoir pressure emerges as a key parameter to determine the temperature of the two-phase mixture. By realistically capturing phase transitions driven by coupled thermo-hydraulic processes during operations, our numerical model predicts a lower power generation efficiency compared to previous attempts based on ultra-simplified models. Although finalized at assessing the thermodynamic viability of a specific system, this modeling approach provides general information on fundamental thermo-hydraulic processes in the Earth crust that might be applied for the design of similar EGS projects elsewhere. [ABSTRACT FROM AUTHOR]

Green economic growth and sustainable development are inextricably linked, and encouraging green economic growth has practical implications in today's world. In this context, this study examines the impact of environmental regulation on renewable energy development and China's green economy from 1990 to 2018. We look at how environmental regulations affect green economic growth and renewable energy technologies. Using the Meta frontier SBM model's super-efficient data envelopment analysis, it is possible to determine the relative level of green economic growth in China's provinces based on their energy efficiency. Environmental regulations were also assessed using an improved fuzzy inclusive appraisal method. Finally, we investigate the possible mechanism and discuss our findings. The study discovered an unreliable indicator of green growth during the research period, attributed to the non-serious nature of government strategies. The results show that the DEA method consistently confirms how the piece is put together. On the other hand, the sub-results models invariably affect countries with high GDP per capita. Finally, the impact of environmental regulations on the growth of renewable energy sources was studied. Green economic growth depends on environmental regulation policies, which contribute significantly to renewable energy development. Population size, economic development level, technological innovation, industrial structure, urbanization, environmental regulation, and FDI influence green economic growth, but the spatial effect of each influencing factor varies. The findings of this paper form the basis for China's pursuit of green economic growth and the development of renewable energy policies. • Proposed a novel framework on R & D expenditures, low carbon energy transition and green economic growth. • Study analyzes the effects of the multiple R & D expenditures in the context of Belt & Road Initiative economies. • Dynamic linking is considered when the connections of players' change. • Established vibrant empirical model and suggested implications for green economic recovery. [ABSTRACT FROM AUTHOR]

The energy-growth nexus has been explored extensively by researchers and academia; however, the role of cleaner energy, especially in the context of emerging economies, i.e., Nex-11 countries, have been ignored. Therefore, to fill the gap in the literature, this paper considers a non-parametric panel method, to test directly for the importance of renewable energy in economic performance for Next eleven (N-11) countries. The econometric estimations—which focused on a panel of N-11 countries—determined that: (i) renewable energy consumption boosts economic growth in short run only; and (ii) industry value added, human development, and consumption expenditures accelerate economic, whereas globalization decrease it. Hence, all countries need to reduce the risk associated with renewable energy so that to make them effective for economic growth. Moreover, there is a need to provide different types of invested capital for ongoing activities of renewable energy production. In general, this study provides relevant policy implications in the context of renewable energy, globalisation and economic growth for the Nex-11 economies. • Renewable Energy led Economic Growth Hypothesis is tested in the Next-11 countries. • The novel Method of Moments Panel Quantile Regression is employed. • Renewable energy led economic growth is valid in the selected panel economies. • Consumption expenditures, Human Development, Industry Value Added enhances growth. • Globalisation is found to limit economic growth in case of Next-11 countries. [ABSTRACT FROM AUTHOR]

The article deals with the subject of energy storage. This important issue relates to the ongoing transformation toward renewable energy sources. Liquid Air Energy Storage (LAES) is a mechanical energy storage technology that is suitable for large-scale energy storage. The article presents a method to increase the efficiency of LAES by coupling it with the transcritical carbon dioxide cycle. To this end, the paper presents a numerical analysis of two Kapitza LAES systems with the transcritical CO 2 cycle: in parallel and subsequent mode. In both cases, maximizing CO 2 pressure contributes to greater overall efficiency. It is only profitable to direct residual heat to the CO 2 cycle. In contrast, lowering the air temperature prior to expansion in hopes of providing a greater amount of heat to the CO 2 cycle actually delivers worse results. Parallel system implementation can add 5–6% to storage efficiency, depending on other factors. In comparison, the subsequent system only adds some 3.5%–5% to storage efficiency. [ABSTRACT FROM AUTHOR]

The improvement of energy transition programs towards renewable energy sources and efficiency of energy savings programs should focus towards new energy behavioral characteristics for reducing energy consumption and maintaining people well-being. This paper deals with the results of a survey campaign focused on social energy behavior of customers after complete liberalization of the electricity market and facing the increase of electricity prices occurring in the last year. The energy behavioral assistance programs require indicators that can be quantified. The standardization of these results will determine useful information to be derived from the survey poll. The available data on energy consumption from energy utilities could help researchers and companies in estimating the efficiency of the actions towards energy transition. In addition, the up-scaling of various energy behavioral programs and life-cycle of the obtained energy savings should be monitored and evaluated. The energy consumption can be reduced using various behavior assistance programs, tuned for specific end users. The customer can diffuse the good practices involving more and more users of different age, involving and transforming the end-user in an active part. The analysis of the adopted methodology is very positive considering the obtained results with respect to the established objectives. • Social behavior analysis of customers after complete liberalization of the electricity market. • Positive energy transition with renewable energy sources. • Survey of energy behavior at national level. [ABSTRACT FROM AUTHOR]

Given its widespread potential and technological advancements, it is critical to use the greatest amount of wind power in reaching the 100% renewable energy target in power grids. SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis is frequently used to evaluate alternative strategies in multi-criteria decision issues. This paper employs a hybrid Fuzzy Analytic Network Process (FANP) approach based on SWOT to assess the future development of wind power capacities in Turkey in light of the sectoral effects of the Covid-19 outbreak in 2020. To validate the proposed approach, the results are compared to the results of the SWOT-based Analytic Network Process (ANP), Analytic Hierarchy Process (AHP), and fuzzy AHP (FAHP). According to the findings, "Development of domestic and efficient technologies (ST1)" and "Sustaining support mechanisms in investments and technological research (SO2)" are the best alternative strategies in all analysis models. While the priority ranks of other alternative strategies are the same in AHP and FAHP hierarchical techniques, FANP differs from ANP when the linguistic assessment process is taken into account. This study proposes long-term strategies for increasing wind power capacity and sector sustainability, and it demonstrates that FANP could be an appropriate approach for prioritizing these strategies in current scenarios. [ABSTRACT FROM AUTHOR]

The parabolic-trough solar concentrating systems are often considered element of heat generation systems from renewable energy sources. It is important to use appropriate optical systems and solar trackers because parabolic trough collectors utilize only direct solar radiation. The paper presents the results of an analysis of the effect of solar tracker error on the optical and thermodynamic efficiency of linear absorbers. The results are presented for low concentrated geometry, popular among scientific institutions, consistent with the existing facility operating under natural conditions. Two diameters of the linear receiver were considered in the analysis: 33.7 mm and 21.3 mm. The research was carried out in optical engineering software based on the Monte Carlo ray-tracing method. Thermodynamic analysis was performed based on the mathematical model of the radiation absorption phenomenon by heat transfer fluid. The maximum angle error of the solar tracker for the tested geometry, not significantly affecting the performance of the linear absorber for a diameter of 33.7 mm is 1.5°, and for 21.3 mm is 0.9°. The reduction in efficiency for 2° error is 4.7% points, and 42.5% points respectively. The analysis also presents the results of the radiation distribution on the surface of the absorber tube. • Monte Carlo ray tracing method and mathematical model were applied. • Vacuum and no-vacuum envelope cases were analysed. • The PTC efficiency as a function of the solar tracker error was determined. • Analysed linear absorber can operate efficiently up to 1.5° or 0.9° tracker error. • The radiation distribution on the surface of the absorber tube was presented. [ABSTRACT FROM AUTHOR]

The integration of renewable energy sources (RES) based distributed energy resources (DER) lead to reduction in overall system inertia which causes large voltage and frequency fluctuations during any intermittency. This necessitates the integration of fast and robust controllers for low-inertia microgrids. Therefore, this paper proposes disturbance observer based control (DOBC) approach for frequency and voltage regulation of microgrid consisting of solar PV and diesel generator (DG) based hybrid microgrid under islanding situations. The DOBC is included as feed-forward control to the synchronous generator-based DG, which handles the real-time power mismatches and regulates frequency and voltage of islanded microgrid. To demonstrate the operational resilience of the designed controller under real-time uncertainties in PV and load, the controller has been evaluated under the most extreme uncertainty scenarios. The suggested controller has been implemented on a MATLAB/Simulink platform, and results have been validated utilising the real-time simulator OPAL-RT. In addition, the efficacy of the suggested control strategy has been evaluated in the presence of communication delays and noisy load circumstances. Results demonstrate the controller's dynamic performance in regulating the frequency and voltage for low-inertia microgrids. Finally, the proposed control technique has been executed on laboratory-scale microgrid to demonstrate the potential of developed controller. • Robust auxiliary DOBC for frequency & voltage regulation of PV-Diesel Microgrid. • Robust handling of real-time generation & load uncertainty through polyhedral sets. • Performance verification in presence of communication delay & noisy load conditions. • Real-time testing on OPAL-RT & hardware implementation on lab-scale microgrid setup. [ABSTRACT FROM AUTHOR]

This research examines the effect of environmental policy stringency on green innovation in renewable energy technology and whether the green innovation response differs with varying degrees of environmental policy. Based on panel data of 33 countries over the period 1990–2015, we show that a stringent environmental policy does encourage green innovation in renewable energy technology, and this impact is more pronounced in OECD countries and high-income countries. More specifically, a stringent non-market-based environmental policy induces more patents in renewable energy generation. The findings also show that a stringent environmental policy yields green innovation for geothermal energy, hydro energy, and marine energy, but not for wind energy and solar energy. Heterogeneity analysis suggests that innovation capacity and environmental pressure enhance the impact of environmental policy stringency on green innovation in the renewable energy field. Finally, the paper presents that clean energy investment plays the role of a mechanism through which environmental policy stringency spurs green innovation in the renewable energy field, offering insights into the influence of environmental policy stringency on green innovation. [ABSTRACT FROM AUTHOR]

This paper presents an experimental performance comparison of self-excited induction generator (SEIG) and permanent magnet synchronous generator (PMSG) for renewable energy-based standalone applications. These two generators have gained popularity in constant speed prime mover-driven power generation systems due to their inherent advantages. Many researchers have proposed various configurations with and without power electronics and battery energy storage for SEIG and PMSG systems. In the isolated systems, the maximum generation and load capacities are known and the primary goal is to maintain a constant voltage and frequency across load terminals. In this context, the performance comparison of both generators is needed to identify the simple, viable, and economical solution for a dedicated source and fixed isolated loads. Therefore, an attempt is made on the performance analysis of micro-hydro turbine driven SEIG and PMSG with resistor heating and induction motor driven pump load applications and compared experimentally to identify suitable voltage regulated generator. The proposed study is not employing power electronic based switches for reactive power (VAR) compensation to make the system cost effective with ease of operation. The working procedure and minimum requirements are discussed in detail for the experimental purpose. Keywords - Self-excited induction generator (SEIG), permanent magnet synchronous generator (PMSG), renewable energy sources, power generation, isolated loads, voltage regulation (VR). • Identification of a suitable generator for small-scale pico hydro applications. • Performance of the self-excited induction generator under different loads. • Performance of the specially designed permanent magnet synchronous generator. • Comparative analysis between SEIG and PMSG under the same experimental conditions. [ABSTRACT FROM AUTHOR]

The energy needs of a Net Zero Energy Building (NZEB) are fully met by renewable energy sources. Nevertheless, the time span of the energy balance can affect the effective energy self-sufficiency of the building. The aim of this paper is to demonstrate the lack of reliability that a yearly energy balance has in characterizing an NZEB. At this scope, comparisons between two different photovoltaic systems (fixed and tracking) and two kinds of energy balance (yearly and monthly) are made for a real NZEB building located in South-Italy. The investigation was carried out through dynamic energy simulations after validating the building model. The results show that the PV surface which attains the NZEB target on yearly basis not always achieves the same objective as the monthly balance. Furthermore, considering a monthly balance, the size of the photovoltaic system with biaxial solar tracking is 50% minor than the fixed one, thanks to a steadier energy production. Also, solar tracking systems show a significantly lower reduction of operational and embodied CO 2 emissions. A final technical-economic analysis shows, however, that design solutions that satisfy NZEB target not always can meet the financial interest of the private stakeholder, showing a high discounted payback period. • The energy needs of an existing NZEB are evaluated through dynamic simulation. • Fixed and tracking PV systems are designed and compared to obtain the NZEB target. • Comparisons between yearly and monthly balance using different PV systems are made. • Yearly balance is not adequate to characterize energy self-sufficiency for an NZEB. • Tracking PVs reduce monthly withdrawal from electricity grid and CO 2 emissions. [ABSTRACT FROM AUTHOR]

Green finance has emerged as a strategy that encompasses not only instruments for mitigating greenhouse gas emissions and adapting to climate change, but also financial products and services that address a broader range of environmental concerns, including industrial pollution control, waste management, sanitation and hygiene, and ecological protection. The study employs an integrative approach comprising a bibliometric and manual review of sample studies to understand the subject of knowledge in green finance and its transition from theory to practice, indicating the current state of research and its evolution tendencies. The current study analyzes the publications that highlight the various dynamics of green finance by conducting a bibliometric analysis on a sample of 222 relevant papers retrieved from the Web of Science and Scopus databases. The study discusses the theoretical underpinnings of the constructs/themes uncovered through the results and identifies current research trends, hotspots, and prospective research opportunities. Finally, we identify key topics in the field of green finance and suggest a four-part conceptual framework (goal, procedure, place, and perspective) based on the results of the thematic map. This framework serves as a guide for future research. • Conducts integrative review to analyze green finance literature transitioning from theory to practice. • Analyses 222 sample studies retrieved from the Web of Science and Scopus databases. • Provides key topics and suggest a four-part conceptual framework. • Identifies current research trends, hotspots, and prospective research opportunities. [ABSTRACT FROM AUTHOR]

The objective of this paper is to develop an optimal scheduling scheme for an Energy Storage System (ESS), in a grid-connected microgrid, which is used for two main energy services, namely Operating Cost Minimization Service (OCMS) and Contracted Service (CS). OCMS refers to minimizing the overall operating cost of the microgrid. CS is a specified balancing service for the grid operator in UK to manage the actual demand when the demand is greater than forecast or generation availability. In this service, a constant contracted level of power is delivered by the ESS on instruction from the grid. A linear programming (LP) based optimization method is proposed to effectively combine these two services. Different simulation studies are conducted to test the effectiveness of the proposed method under variations in the renewable energy sources such as photovoltaic (PV) and wind in given microgrid. The proposed method is compared with a conventionally used Fuzzy Logic Control (FLC) based optimization method and is also experimentally validated. Simulation and experimental studies show that LP based optimization method can achieve a lower operating cost (up to 20%) in the microgrid and thus maximize the economic benefits of using an ESS by effectively managing different energy services. [ABSTRACT FROM AUTHOR]

With the increasing penetration of volatile renewable energy sources (RES) in power systems, the formulation of RES uncertainty set in the unit commitment (UC) problem poses significant challenges to the operators especially those in AC-DC systems. To overcome the over-conservativeness and computational redundancy in conventional uncertainty formulation methods, this paper induces the stochastic rationale into the robust dispatch model and proposes a two-stage robust frequency risk-constrained unit commitment (FRCUC) model to excavate the system flexibility. Based on the typical characteristics of AC-DC dispatch system, the frequency violation risk (FVR) factors are proposed to enhance the adaptability of uncertainty sets, wherein the HVDC regulation is activated to cope with the extreme uncertain scenarios with lower probability. As a result, being aware of the wind power distribution, the proposed model succeeds in managing the operational risks by fully exploiting the controllability of HVDC system, and the over-conservativeness from conventional robust model is handled by the proposed FVR factors. The outperformance of our model is validated by the numerical experiments on a modified AC-DC system, it is validated that the operational risks are evaluated when considering the violated wind power distribution, and therefore the model economic benefits are promoted when ensuring the reliability. [ABSTRACT FROM AUTHOR]

As a result of the COVID-19 epidemic, a worldwide economic slump has reduced the depletion of natural resources, lowering their costs. The loss of renewable energy profitability might hinder the attainment of specified goals of sustainable development goals. By using Chinese provinces data from 1995 to 2020, this research examined the relationships between renewable energy investment (REI), green finance (GFI), growth of the economy (GDP), renewable energy production (REP), and private sector participation (PSP) in China. According to this analysis, REI, REP, and GFI are more variable throughout the given period than GDP. And PSP. A bidirectional substantial causal correlation between REI and REP was identified using the Generalized method of moments (GMM). Still, the regression coefficient between GDP and REI and REI. and GFI has a one-way causal relationship. There was no evidence that the PSP directly impacted the REI. Based on the empirical findings of this research, we propose that policies be designed to reduce volatility in REI GFI, and REP and increase support to improve sustainable economic development and environmental and renewable energy production. Examine between green financing and environmental conservation for long-term environmental quality. • There is a dire need to measure the examined the relationships between renewable energy investment (REI), green finance (GFi). • Bidirectional substantial causal correlation between REI and REP was identified using the Generalized method of moments (GMM). • There was no evidence that the PSP had a direct impact on the REI. • This paper improve sustainable economic development as well as environmental and renewable energy production. [ABSTRACT FROM AUTHOR]

As countries implement renewable energy policies, it's important to understand the impacts of policies on sustainability. Population, economic and production changes affects in land use, water consumption and emissions along with trade-offs for limited resources to achieve food and energy security. Thailand faces increasing electricity imports and agricultural production, causing residue burning, a resource utilized for electricity generation. Thailand implemented a renewable energy policy and another to curb sugarcane residue burning addressing above challenges. The paper uses an extended input-output model in Thailand and the Northeast to understand impacts of these policies on output, labor income, employment, land and water use, etc. The study concludes these policies lead to supplementary increase in income, employment and value added contributing towards achieving SDGs through energy security, climate action, decent work and economic growth. At a national level, renewable energy policy is unable to capture a large potential of biomass electricity, while the no burn policy is better able to achieve sustainability through total output, income, employment, and water use. The renewable energy policy in Northeast Thailand is better able to capture the electricity potential. The Northeast also sees land use shifts from rice to cane, which could cause food security challenges. • Thailand faces growing challenges with energy security and crop residue burning. • To address the challenges, they implemented RE policies and crop burning policies. • The study uses extended input-output models in Thailand and Northeast Thailand. • We see positive effects of the policies on the economy, society and environment. • The policies fall short in capturing the full potential of biomass electricity. [ABSTRACT FROM AUTHOR]

The studies exploring inter-relations between non-renewable energy consumption, renewable energy consumption, GDP, and CO2 emission are quite limited in Vietnam due to the limitation of data. Different major players in this market, such as investors, regulators, and other financial actors have different time horizons. By applying innovative multivariate wavelet analysis tools, including partial wavelet coherency and partial wavelet gain, this paper investigates these relations in the time and frequency dimensions in Vietnam during the 1985–2019 period. The multiple coherencies between the non-renewable energy consumption and GDP and CO2 growth suggest that these regions were located at medium frequencies (5–12 years) and concentrated on the 1985–2000 period and the 2003–2019 period. Regarding the relation between renewable consumption and GDP and CO2 growth that the region only concentrated in the high-frequency band (from 2 to 12-year frequency-band) running from 1985 to 2001 and low-frequency band (from 22 to 25-year frequency-band) running from 2011 to 2019. The partial coherency between non-renewable energy consumption and GDP reveals two phases. In the first phase (the beginning of sample to 2000), changes in the non-renewable energy consumption led to changes in GDP, and the relation is negative, while GDP is in-phase with non-renewable energy consumption leading in the second phase (from 2000 to 2015). The partial phase-difference between non-renewable energy consumption and CO2 emission suggests that changes in CO2 emission led to changes in non-renewable energy consumption, and the relation was negative. Regarding the partial coherency between renewable consumption and GDP, most regions were located in the 2–12-year frequency band running from 1985 to 2001, from 2001 to 2003, and from 2005 to 2012. During the 1985–2991 period, the results indicate the anti-phase relation with the GDP growth leading, while changes in renewable energy consumption led to changes in GDP growth, and the association is negative from 2001 to 2003. Since 2003, there was an anti-phase relation with the GDP growth leading. Lastly, the partial wavelet coherency of renewable energy consumption and CO2 emission indicates that regions were found to be statistically significant in the 3-4- and 7-15-year frequency band and there was the anti-phase relation with the CO2 emission leading. [ABSTRACT FROM AUTHOR]

The application of green energy technologies to supply berthed ships in ports with the necessary power instead of using their diesel generators is considered an initiative towards sustainability and climate change mitigation. Therefore, the current paper investigates the implementation of solar panels, offshore wind turbines, and hydrogen fuel cell systems as green technologies to supply the berthed ships with power in three Egyptian ports. The power requirements are determined by analyzing the annual ship traffic data and estimating the energy demand for each ship type. As a relevant result, the annual energy demand for ships berthed in Alexandria, Damietta, and Safaga ports is about 44.2 × 103 MWh, 22 × 103 MWh, and 5.6 × 103 MWh, respectively. The analysis results reveal a potential annual carbon dioxide reduction of 31.7 k-tons, 15.7 k-tons, and 4.2 k-tons in Alexandria, Damietta, and Safaga ports, respectively. From an economic perspective, the levelized cost of energy (LCOE) of solar panels is estimated to be 80.7–90.1 $/MWh, while hydrogen fuel cells have a cost of 166.8–172 $/MWh. On the other hand, LCOE in the case of wind turbines is estimated to be 140.8 $/MWh for Alexandria ports, 178.3 $/MWh for Damietta port, and 103.9 $/MWh for Safaga port. [ABSTRACT FROM AUTHOR]

The present paper describes the development of a novel framework for the creation of specialised Micro-Credentials supporting the training and re-training of students and professionals on the integration of renewable energy and sustainable fuels in urban settings. The framework is built upon a set of stackable micro-credentials, co-designed with the stakeholders input and it uses advanced natural language processing (NLP) and machine learning algorithms to assess the impact on the job market at regional level. The use of Micro-Credentials are considered to be the optimal methodology for enhancing the knowledge of specific topics especially for life-long learning for professionals. A co-design approach of such an innovative educational framework with relevant stakeholders fosters a tailored educational path for green upskilling. Finally, the framework is validated processing and analysing a large dataset of job descriptions, extracting the skills required by the market, organising the skills in categories and clusters. All this process lead to the creation of a basket of 74 Micro-Credentials oriented to students and professional with both a technical and non-technical backgrounds. • Renewable job-market skill needs identification through NLP and machine learning. • Educational co-creation approach based on stakeholders interaction. • Microcredential (MC) framework for life-long learning in the renewable sector. [ABSTRACT FROM AUTHOR]

This paper utilizes data from 26 countries to document the relationship between renewable energy consumption, shadow banking, traditional banking, and economic growth covering 2010–2021. Employing panel quantile approaches, the results indicate a negative and significant impact of renewable energy consumption on economic growth, highlighting the initial high costs inherent in transitioning to renewable energy sources. Moreover, the findings reveal that shadow banking, along with traditional banking, tends to weaken the negative impacts of renewable energy consumption on economic growth, particularly in countries with medium and high levels of economic development. Finally, panel causality tests confirm bidirectional causality between economic growth and renewable energy consumption, economic growth and shadow banking, and renewable energy consumption and shadow banking. These insights underscore the need for policymakers to consider the role of alternative financing mechanisms in the transition to renewable energy. [ABSTRACT FROM AUTHOR]

This paper presents a tool that allows to perform an ex-ante estimation of the profitability to participate to the electric energy and service markets for a microgrid or a polygeneration power plant. The tool is the evolution of an Energy Management System (EMS) previously developed by the University of Genoa and Renantis Solutions Srl. Constraints are added to the original EMS to model the Ancillary Service Market (ASM) and Day Ahead Market (DAM) mechanisms in the framework of a planning tool that allows to get estimates of the microgrid/plant costs and revenues over a long-time horizon. As the market outcome strongly depends on the Transmission System Operator (TSO) acceptance/rejection of bids and offers, a statistical approach is proposed. The optimization process is split in two steps: the first one optimally dispatches the energy units and proposes DAM offers and ASM bid and offers over a specified time horizon. Then, a Monte Carlo method is launched; at each extraction the TSO acceptance/rejection of each ASM bid and offer is simulated and there is a second step of optimization in which the energy sources are optimally re-dispatched to meet the bidding program and so to avoid imbalance power exchange that would increase the energy cost. The cost/revenue is thus computed at each extraction. The result is the probability density function of the costs/revenues that allows to estimate the profitability of the participation to the electricity markets. One test performed on a real microgrid shows that the computational time needed to complete one iteration related to a time horizon of one month is approximately 20 s. Moreover, the comparison of the outcomes with two independent launches to define the set of bids and offers to be accepted in ASM demonstrates that the statistical analysis allows to avoid misleading conclusions on the costs/revenues. Consequently, the fact that the developed EMS allows to perform a statistical analysis in a reasonable time enables the possibility of comparing multiple scenarios and gives an indication related to the range of cost/revenues in which the microgrid/plant may incur. Finally, the computational efficiency of the proposed approach allows to conclude that the developed EMS is appropriate to perform a long-time horizon (of the order of magnitude of years) analysis and, at the same time, allows to model all the involved components with a high level of details. [ABSTRACT FROM AUTHOR]

The depletion of conventional fuel reserves and the high carbon emissions have alarmed the energy sector drivers. The integration of renewable energy resources (RERs) towards power system transformation is an obvious approach for a new-zero future. However, this integration also brings challenges in terms of voltage stability and power losses due to the variable output of RERs. To address these challenges, this work proposes a novel approach utilizing photovoltaic (PV) inverters and static var compensators (SVCs) for reactive power control in power distribution networks (PDNs). It enhances voltage stability and minimizes power losses. The proposed study deploys a proximal policy optimization (PPO) algorithm for real-time communication and control between reactive power devices. Performance evaluation was made on an IEEE-33 Bus system to demonstrate the effectiveness of the proposed scheme in integrating RER-based distributed generators (DGs). The proposed system achieved 68 % voltage control, keeping the voltage within a certain range of ±5 % while minimizing power losses. The proposed system also reduced the voltage out-of-control ratio to 0.044, which indicates minimum voltage deviation from the standard value. The proposed study provides a promising solution for controlling the voltage of DGs integrated PDN, which can potentially enhance the efficiency and reliability of the power system. • This paper introduces PV inverters and SVC-based reactive power voltage regulation for renewable DG-integrated systems. • Reactive power control in the DG-integrated system is adopted using Reinforcement Learning-Driven PPO. • The validation of the proposed method uses the IEEE-33 bus system to integrate RERs-based DGs and achieve PPO-based control. • The proposed method achieved 68% voltage control, reduced power loss, and reduced the voltage out-of-control ratio to 0.044. • This research compares the suggested approach to different methodologies to demonstrate its validity and applicability. [ABSTRACT FROM AUTHOR]

The intermittent nature of renewable energy resources is a major obstacle in utilizing such resources for power generation despite their abundance. In this paper, a dynamic analysis of an integrated system based on photovoltaic (PV) panels and wind turbines coupled with pumped hydro energy storage is presented. When the power generation exceeds the power demand, surplus electricity is used to pump the water to the upper reservoir. The natural inflow of the river obviates the necessity for oversized reservoirs and saves costs. A recently introduced multi-objective equilibrium optimizer algorithm is developed to find the optimal size of the integrated hybrid energy system. The objectives are to minimize the levelized cost of electricity and maximize the reliability of the proposed system. The results show that the correlation between solar and wind power generation in the selected location is mildly strong with a value of 0.3. The total energy generation from hydro, solar, and wind resources are 77,508.7 kWh, 103,323 kWh, and 47,375.4 kWh, respectively. Comparing the results with other algorithms indicates that the equilibrium optimizer has a better performance in finding the optimal design. [ABSTRACT FROM AUTHOR]

Energy complementarity is a promising approach in the realm of renewable energy systems, enabling the integration of multiple energy sources to achieve a stable and sustainable power supply. This paper presents a comprehensive solar-wind complementarity study encompassing all regions of Morocco. A novel method for assessing complementarity is introduced, utilizing a fluctuation approach that classifies the power output of each source based on the median and the standard deviation. The classifications of both solar and wind sources are then combined to establish a basis for complementary classification, categorizing each day as complementary, non-complementary, low-complementary, or concurrent for both sources. An innovative complementarity index is proposed, ranging from 0 to 1, with values closer to 1 indicating high complementarity. This index is applicable to any location and is used to generate maps illustrating solar-wind complementarity. Additionally, dominance metric is derived from this approach that indicates which source is most likely to complement the other source. The results reveal that temporal complementarity is high in the internal Northern regions reaching indices above 0.7, followed by the Northern coastal regions with indices that range between 0.6 and 0.7. The lowest complementarity occurs in the South with indices below 0.6. Additionally, the complementarity plots that displays the monthly indices reveled, for most regions, that complementarity maintains certain level except in the summer where it peaks or drops. The solar dominance is higher in the South reaching above 60 %, even though the wind potential is important in those regions. For spatial complementarity, two locations were considered and the method is applied for four scenarios: solar-wind, wind-solar, solar-solar and wind-wind. Results favor all the combinations except for the solar-solar scenario. The suggested index yields similar results to Kendall's tau correlation. The negative correlation index indicates high complementarity when positive and a low complementarity when close to −1. For this approach, it is not limited to the degree complementarity but can describe other states of complementarity and its frequency of occurrence compared to other states. This provides additional insights compared to the commonly used correlation methods. The proposed method contributes to a more profound understanding of complementarity between two energy sources. [ABSTRACT FROM AUTHOR]

The uncertainty of renewable energy makes the optimal scheduling of integrated energy systems (IES) challenging and complex. The paper suggests a novel two-stage optimized scheduling model based on distributionally robust adaptive model predictive control (DRAMPC), which effectively improves scheduling accuracy and efficiency while taking robustness and economy into account. In the day-ahead stage, the multi-objective distributionally robust optimization (MODRO) model is composed based on the imprecise dirichlet model (IDM), which incorporates robustness and operating cost metrics into the optimization objective to achieve synergistic optimization of robustness and economy. The adaptive step double-loop model predictive control (ASDL-MPC) utilizes the dual closed-loop feedback of renewable energy output prediction errors and operating cost prediction errors to adaptively adjust the rolling time step, correcting the day-ahead scheduling bias while improving scheduling efficiency. The model is resolved using the cross-entropy-radar scanning differential evolution (CE-RSDE) algorithm. The results show that the DRAMPC model can balance economy and robustness, improving the economy of IES by 2.27% while ensuring robustness. The ASDL-MPC intra-day rolling optimization further improves scheduling accuracy and also increases computational efficiency by 6.58%. [ABSTRACT FROM AUTHOR]

The issue of large-scale retirements of renewable energy modules has attracted considerable attention from governments and the public worldwide. Using the Chinese wind and photovoltaic industries as examples, this paper, for the first time, employs a real options approach to explore the optimal time for energy firms to retire their power plants and to predict the future trend of renewable energy wastage from a bottom-up perspective. The results show that the optimal retirement time for the four subdivided categories ranges from 16 to 23 years. The later the investments are made, the earlier the decommissioning time comes and the lower the project returns. Furthermore, wind projects have been found to generate more revenue than PV projects for the same size, and the gap continues to widen. Offshore wind technology always has the longest optimal service life (18.62 years in 2022) and the greatest project returns (10.84 million CNY in 2022). Annual utilization hours, the renewable electricity price and the waste price can accelerate the retirement of plants and generate more revenue for energy companies, while the initial investment cost has a completely opposite effect. The first wave of PV retirements will occur in 2035 at 305.82 GW, while onshore wind will be in 2036 at 530.77 GW and offshore wind will not explode until 2040 at 65.84 GW. An assessment of potential policies suggests that for every 100 CNY increase in incentive strength, the retirement wave arrives 1 year earlier. In contrast, for every 100 CNY increase in the strength of penalties, the retirement wave is delayed by 1 year. In addition, we verify that the size of the plants does not affect the forecast of the retirement trend, indicating that the assumptions about installed capacity do not cause bias. [ABSTRACT FROM AUTHOR]

This paper addresses the critical challenge of sizing hybrid renewable energy systems over their lifespan while accounting for uncertainties in energy sources and load demands. By leveraging stochastic programming, we introduce a novel modeling technique that ensures robust optimization without compromising numerical tractability. Unlike conventional methods, which determine system parameters for the entire project duration upfront, our approach enables annual adjustments to the renewable components' sizing. This dynamic strategy alleviates early-stage under-utilization, aligning system capacity with evolving demand patterns. Central to our approach is the reformulation of the two-stage stochastic program as a quasi-optimal control. This reduces the number of optimization variables significantly, simplifying the solution process. Moreover, thousands of constraints are replaced with a system of differential equations, enhancing computational efficiency. By minimizing capital costs and dynamic operating expenses, we achieve an optimal system size. Through a real-world application in a rural area of South Africa, we demonstrate the effectiveness of our approach. The results showed a remarkable improvement in problem-solving efficiency, reduced under-utilization, and heightened adaptability to unpredictable weather conditions. This innovative framework represents a substantial leap forward in hybrid renewable energy systems design, offering a more agile and efficient solution for sustainable energy generation. [ABSTRACT FROM AUTHOR]

Accurate wind power prediction is a vital factor in day-ahead dispatch and increasing the high penetration of renewable energy integration. Some combined prediction models based on weight are proposed to provide uncertain information about wind power. However, the optimal weight issues to be addressed are still a tough problem. This paper proposes an adaptively combined prediction model based on the induced ordered weighted averaging operator. First, four classical prediction models are used as a predictor to forecast wind power. Second, the optimal weight is expressed as an optimization problem to minimize the prediction errors with the nonnegative constraints and summation constraint of weights, and the optimal optimization problem is transformed into a quadratic programming model, which can be easily solved to determine the optimal weights for multiple prediction models. Third, an interval prediction mode based on errors distribution produced by the proposed combined model with different confidence intervals is constructed, which can perform deterministic and probabilistic prediction of wind power simultaneously. Furthermore, the model's effectiveness is comprehensively evaluated using both deterministic and probabilistic approaches. This analysis is further enriched with a comprehensive examination of a year-round dataset obtained from a wind farm cluster in Ningxia, China. The data, recorded at 15-min intervals, offer robust evidence of the combined model's superior performance. The results show that the proposed approach can achieve higher accuracy than other benchmark prediction models, further verifying its reliability for wind power dispatch. [ABSTRACT FROM AUTHOR]

Stand-alone renewable energy systems, which harness and use electricity without connection to a distribution grid, can benefit from using resource forecasts when making real-time decisions on how to manage power. An example of this is an ocean observation system that uses a wave energy converter (WEC) and battery bank to produce and store electricity in order to meet electrical load requirements for oceanographic sensors and instrumentation. By using wave forecasts to optimize the power consumption of this system, it is possible to reduce the size of the WEC and battery bank needed, thereby reducing the overall system's cost and complexity. In this paper, we assess the benefits of forecasting for a generic wave-powered ocean observation system. We model an observation platform powered by a WEC and battery-storage system that can switch between four power states, full power: 600 W, medium power: 450 W, low power: 45 W, and survival mode: 1 W. To determine which power state to enter over time, we present a stochastic optimization method that interprets wave forecasts and system information to select a power state on an hourly basis and simulate over two months of consecutive decisions. Using this simulation framework, we compare 8 power management strategies across a range of WEC sizes (3–5 m) and battery capacities (2.5–35 kWh). We find that it is possible to maintain full (600 W) power consumption over the entire simulation window with a 5 m diameter WEC and 25 kWh battery bank, which is on the upper end of the ranges evaluated. To employ a smaller WEC or battery, load flexibility is required. We find that forecast-based methods for this power management handle tradeoffs in performance (e.g., cumulative power consumption, reducing intermittencies and meeting scheduled load targets) more effectively than power management strategies that do not use forecasting. Overall, our results indicate that forecasting for our stand-alone renewable energy system is most impactful when some loads must be met on or within a defined schedule. • A forecast-based method for managing a load met by wave energy is presented. • This method handles performance tradeoffs better than non-forecasting strategies. • These benefits are most impactful when loads must be met on or within a schedule. • Forecast uncertainty has notable influence, suggesting opportunities for improvement. [ABSTRACT FROM AUTHOR]