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Waste paper as a kind of biomass contains a great quantity of cellulose which is a renewable energy resource. However, complex cellulose supramolecular structure restricts the conversion of waste paper in near-critical water. This study aimed to investigate the change characteristics of cellulose supramolecular structure (hydrogen bond models and crystallinity) during hydrolysis and its effects on 5-HMF yield. Waste paper has been treated in near-critical water at 375 °C and 22.5 MPa for a reaction time (160–240 s) and correlation between 5-HMF yield and the supramolecular structure of cellulose residues has been built up. The 5-HMF yield was increased with the increase of intermolecular hydrogen bonds content in cellulose residues and was increased first and then decreased with the increase of crystallinity of cellulose residues. The rate of decrystallization was out of sync with that of depolymerization, which also influenced 5-HMF yield. Reaction time can be a macro method to adjust the supramolecular structure of cellulose during the conversion of waste paper to obtain more 5-HMF. It showed that 5-HMF yield reached maximum 9.41% ± 0.47% when the intermolecular hydrogen bonds content of cellulose in residue was 67.77% and the crystallinity of cellulose in residue was 57.14% at 200 s. [ABSTRACT FROM AUTHOR]

An enormous gap exists between Africa's current electrification rate and the 2030 UN goal to ensure universal access to modern energy. A study by Sanoh et al. published in Renewable Energy in 2014 [1] is a rare example of finding a cost minimal solution for the Africa-wide generation and transmission network. Unfortunately, however, the paper exhibits a number of relatively serious flaws that demand attention given the alarming paucity of such research on Africa. Five issues of the study by Sanoh et al. are identified and discussed in this commentary paper. Specifically, the study does not account for capacity factors when deriving required capacity additions, misses transmission losses when sizing generation capacity, models country-level import constraints incorrectly, introduces a supply option redundancy, and reports optimisation results that can be shown to be mathematically sub-optimal. As a result of some of these issues, the Sanoh et al. significantly underreport the required capacity to meet additional African demand in 2025. In addition to discussing these flaws, this paper provides potential approaches to avoid each of the five issues. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of combining CO2 capture and storage with alternative systems for biomass-based combined heat and power production (CHP) in Kraft pulp and paper mills. We compare heat, power, and CO2 balances of systems with alternative configurations of the CHP and CO2-capture systems. Because the captured CO2 comes from renewable biomass, the studied systems yield negative CO2 emissions. It is shown that pulp mills and integrated pulp and paper mills have the potential to become net exporters of biomass-based electricity while at the same time removing CO2 from the atmosphere on a net basis. The study shows that that the overall best CO2 abatement is achieved when CO2 capture is carried out within a biomass integrated gasifier with combined cycle where the syngas undergoes a CO-shift reaction. This configuration combines efficient energy conversion with a high CO2 capture efficiency. Furthermore, cost curves are constructed, which show how the cost of CO2 capture and storage in pulp and paper mills depends on system configuration and the CO2 transportation distance. [Copyright &y& Elsevier]

This paper investigates the impacts of economic (in)stability on carbon emissions and the role of renewable energy in these effects at the crossroads of accelerated climate change and rising global economic instability. The paper hypothesizes that these implications should be examined not by direct impacts across variables, but rather via indirect effects serially mediated by renewable energy consumption and economic growth. This paper analyzes the United States from January 1980 and April 2022 using manifest structural equation modeling. The paper reaches two major conclusions. First, there are clear distinctions between (i) the direct and indirect effects of economic stability, surrogated by inflation and policy interest rate, on carbon emissions, (ii) the symmetric and asymmetric indirect effects, and (iii) the roles of aggregate renewable energy and its components, such as biomass and hydropower energy use, in mediating these symmetric and asymmetric indirect effects. Second, renewable energy significantly reduces the carbon-increasing effects of inflation and interest rates. The paper contains proper policy suggestions based on the findings. [ABSTRACT FROM AUTHOR]

With further penetration of low-carbon energy conversion, microgrids (MGs) have become a necessary tool for expanding the consumption of renewable energies. In this paper, an optimal operation model for a microgrid-based multi-agent system is proposed. The goal is to save the total energy cost, which is expressed as a sum of locally observable convex functions. Therefore, improving the operational efficiency of microgrids is the key to promoting renewable energy development. This paper develops a three-layer multi-agent system model considering energy storage system and power thermal load demand response to solve the energy management problem of microgrids. In order to investigate the effect of energy storage system and demand response in microgrids, this paper designs three simulation cases, namely infrastructure case, energy storage case and demand response case. In order to prove the effectiveness of the proposed method, this paper uses the proposed method to solve three cases and compare the result with other meta-heuristic algorithms. The comparison results show that: (1) the multi-agent system model can realize the joint optimization of "resource, network, load and storage". (2) The introduction of energy storage and demand response system in microgrids can stabilize the output. Renewable energy units promote the use of renewable energy and reduce the overall operating cost of microgrids. Moreover, the results clearly demonstrate that the proposed algorithm has far better performance than other optimization methods. Also, the analysis obtained from the results shows that the cost is reduced by 1.82%. PV and WT output increased by 14.54% and 2.42%. In addition, their standard deviation decreases after ESS participation. The proposed approach is very effective through a simulation case study, which shows high potential for applications. [ABSTRACT FROM AUTHOR]

Global warming has focused attention on how the world produces the energy required to power the planet. It has driven a major need to move away from using fossil fuels for energy production toward cleaner and more sustainable methods of producing renewable energy. The development of offshore windfarms, which harness the power of the wind, is seen as a viable approach to creating renewable energy but they can be difficult to design efficiently. The complexity of their design can benefit significantly from the use of computational optimisation. The windfarm optimisation problem typically consists of two smaller optimisation problems: turbine placement and cable routing, which are generally solved separately. This paper aims to utilise selection hyper-heuristics to optimise both turbine placement and cable routing simultaneously within one optimisation problem. This paper identifies and confirms the feasibility of using selection hyper-heuristics within windfarm optimisation to consider both cabling and turbine positioning within the same single optimisation problem. Key results could not identify a conclusive advantage to combining this into one optimisation problem as opposed to considering both as two sequential optimisation problems. [ABSTRACT FROM AUTHOR]

This paper examines the impact of green finance on environmental performance in developing countries. Using panel cointegration analysis and panel vector error correction model (VECM) to a sample of 76 developing economies from 2010 to 2019, this study confirms that carbon emissions (CO 2) is cointegrated with green finance, real gross domestic product, urbanization, and renewable energy under different specifications and therefore we estimate the long-run relationships among these variables. Specifically, both green finance and renewable energy are found to exert significant and inhibitory effects on CO 2 emissions, reaffirming the necessity to promote green finance and renewable energy. Results from the paper also document the existence of the Environmental Kuznets Curve and the increasing effects of urbanization on CO 2 emissions. Several policy implications and recommendations are drawn from this study. • We examine impact of green finance on environmental performance. • 76 developing economies from 2010 to 2019 are considered. • Green finance and renewable energy exert inhibitory effects on CO 2 emissions. • Results support the existence of the Environmental Kuznets Curve. [ABSTRACT FROM AUTHOR]

The present paper analyses the evolution of renewable energy generation in the European Union through a decomposition analysis based on the Index Decomposition Analysis together with the Logarithmic Mean Divisia Index within the EU27 between 2000 and 2020. A four factors decomposition approach is considered for decomposing the total RES generation and a five factors model is employed to decompose the carbon emissions. Furthermore, a focus on wind and solar photovoltaic generation is introduced through a four factors decomposition calculated in the period 2010–2020. The most influential factors affecting the RES generation trend in the period 2000–2020 are the RES share and energy efficiency wich determined an increase of 1841 TWh and a decrease of 635 TWh respectively. Variations of carbon emissions are mostly affected by the energy intensity, namely the amount of energy necessary to produce one unit of GDP, which determined a reduction of 1040 Mt. Through the decomposition analysis, the paper successfully identifies the specific drivers supporting RES development and controlling carbon emissions, thus adequate policy measures can be designed to reach planned targets. • LMDI methodology is used to study decomposition of RES generation in EU. • Technical and socio-economic factors are highlighted by using 4 or 5 factors identity. • Technical factors have the main impact on the increase in RES generation. [ABSTRACT FROM AUTHOR]

Non-interconnected island systems around the globe present a great variety and substantial particularities regarding the methods applied in generation scheduling, primarily under high renewable energy sources penetration levels. Under such conditions, one of the main challenges in island systems is the coherent treatment of intermittent renewable generation and the implementation of robust unit commitment and economic dispatch methodologies, seeking to achieve high RES absorption rates, least cost scheduling, and system security. In this paper, an extensive and in-depth literature review is undertaken to identify the generation scheduling principles and methods applied in island systems experiencing high renewable penetrations. Principal features of electricity markets in islands are highlighted, state-of-the-art unit commitment and economic dispatch models suitable for such applications are identified, and their advantages and limitations are discussed. The effect of renewables uncertainty on the islands' scheduling is analyzed, especially regarding the classification and quantification of system operating reserves to enhance operational security and system stability. Given the isolated nature and limited inertia of islands, very high RES penetration targets may impact their ability to survive severe contingencies, a topic also addressed in this paper, extending the review to include literature on frequency-related dynamic phenomena for isolated systems. • An overview of generation scheduling principles for island systems is presented. • Techniques available to deal with intermittent RES uncertainty are discussed. • A taxonomy of operating reserves adopted in the literature is performed. • A survey on island systems dynamics under high RES penetrations has been conducted. [ABSTRACT FROM AUTHOR]

This paper probes the effectiveness of competitive industrial performance (CIP) and renewable energy in enhancing load capacity factor in top-10 CIP economies for the period 1990–2018. We run panel econometric techniques that address cross-sectional dependence, endogeneity and heterogeneity to provide policy recommendations with the applications of industry, innovation, and infrastructure (SDG 9), which is linked to affordable and clean energy (SDG 7) and climate action (SDG 13). In the empirical analysis, two different environmental quality indicators such as CO 2 emissions and load capacity factor are used. While cointegration between variables cannot be detected in the emissions model, evidence for the existence of cointegration is presented in the load capacity factor model. The findings in the paper suggest that economic growth and competitive industrial performance adversely impact environmental quality, while renewable energy consumption and human capital can improve load capacity factor. The result shows that human capital and renewable energy consumption can be strong tools for stimulating load capacity factor in top-10 CIP economies. Countries with high competitive industrial performance need to return to a green economy without losing their competitiveness. • SDG-based environmental policies was presented for the top-10 CIP economies. • A battery of second generations methods was employed. • Investigating the impacts of Competitive industrial performance on environmental quality. • Competitive industrial performance has a negative impact on environmental quality. [ABSTRACT FROM AUTHOR]

Tidal currents are renewable and predictable energy sources that could prove fundamental to decrease dependency from fossil fuels. Tidal currents, however, are highly unsteady and non uniform, resulting in undesirable load fluctuations on the blades and the drive train of turbines. A passive morphing blade concept capable to reduce the load fluctuations without affecting the mean loads has recently been formulated and demonstrated with numerical simulations (Pisetta et al., 2022). In this paper, we present the first demonstration of this morphing blade concept, through experimental tests on a 1.2-m diameter turbine. We show that fluctuations in the root-bending moment, thrust and torque are consistently reduced over a broad range of tip-speed ratios. This work also highlights some critical design aspects of morphing blades. For instance, it is showed that the friction resistance can substantially decrease the effectiveness of the system and thus must be minimised by design. Overall this paper demonstrates for the first time the effectiveness of morphing blades for tidal turbines, paving the way to the future development of this technology. • We test a model-scale tidal turbine equipped with a passively pitching blade. • The blade angle of attack decreases with an increase in instantaneous loads. • This does not affect the time-averaged power generated by the tidal turbine. • Torque and thrust fluctuations are reduced by at least 40% at on-design conditions. • Friction on the turbine shaft affects performance and must be minimised. [ABSTRACT FROM AUTHOR]

The primary purpose of this paper is to investigate the effects of two variables, trade openness and the issuance of green bonds, on the consumption of renewable energy in Southeast Asian countries. Quarterly data throughout 2016–2021 in the framework of the panel data method were used for the case of 6 selected countries (Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam). The results confirmed that the issuance of green bonds is an effective green financing tool in the implementation of the development policy of the deployment of renewable energy in the countries of the Southeast Asian region. The degree of trade openness has a driving effect on increasing renewable energy consumption due to the increased possibility of transferring green technologies and increasing interactions with leading countries in the field of sustainable development. The typical standard of green bonds, green scientific network (GSN), the development of e-commerce, and the publication of digital green papers are the recommended practical policies of this research. • Green bond is an effective tool to increase of deployment of renewable energy. • Trade liberalism increases the deployment of renewable energy. • Green R&D is a leading factor in the field of clean energy consumption. [ABSTRACT FROM AUTHOR]

This paper collects monthly data for the United States from January 2005 to April 2021 and develops a time-varying parameter vector autoregressive model with stochastic volatility (TVP-SV-VAR) model to investigate the time-varying relationship between climate policy uncertainty, oil prices, and renewable energy consumption. In addition, this paper discusses the dynamic impact of climate policy uncertainty on five types of renewable energy consumption. Our results show that the relationship between them is time-varying. In most periods, climate policy uncertainty positively affects oil prices in the short and medium term, and positively affects total renewable energy consumption in the short and long term. In addition, the impact of climate policy uncertainty on the consumption of the five types of renewable energy is heterogeneous. The results of the robustness tests indicate that our results are robust and our study has important implications for the development of relevant policies. [ABSTRACT FROM AUTHOR]

Recently, renewable energy generation (REG) forecasting has become a challenging task for effective energy management. To date, a number of time-series models utilizing physical models, statistical techniques, and artificial intelligence algorithms have been proposed to deal with this problem. Fuzzy time series (FTS) models stand out among these methods since they do not need extensive historical data or some statistical assumptions like the normal distribution. Because intuitionistic fuzzy sets incorporate non-membership values in addition to membership values, they provide more information than conventional fuzzy sets do. In this regard, this paper recommends a hybrid methodology that combines the intuitionistic FTS method with the intuitionistic fuzzy c-means method for REG forecasting of Turkey between the years 2000–2020. According to the empirical results, it can be concluded that the presented integrated model showed good performance in terms of accuracy. The suggested framework is a useful tool not only for REG forecasting but also for other time series forecasting problems. [ABSTRACT FROM AUTHOR]

Power-to-ammonia (P2A) technology has attracted more and more attention since ammonia is recognized as a natural zero-carbon fuel. In this context, this paper constructs a renewable energy powered multi-energy hub (MEH) system which integrates with a thermo-electrochemical effect based P2A facility. Subsequently, the energy management of proposed MEH system is casted to a multi-agent coordinated optimization problem, which aims to minimize operating cost and carbon dioxide emissions while satisfying constraints. Then, a novel multi-agent deep reinforcement learning method called CommNet is applied to solve this problem to obtain the optimal coordinated energy management strategy of each energy hub by achieving the distributed computation of global information. Finally, the simulation results show that the proposed method can achieve better performance on reducing operating cost and carbon emissions than other benchmark methods. [ABSTRACT FROM AUTHOR]

To improve the renewable energy sources (RES) utilization of isolated microgrids (IMG) in frequency regulation process, an adaptive frequency regulation strategy with high renewable energy participating level is proposed in this paper: 1) an adaptive droop control method is conceived for primary frequency regulation, in which the designed droop coefficients are adjustable with the real-time wind velocity and state of charge (SoC) of energy storage units (ESUs); as the most important contribution, 2) a general flexible model predictive control (FMPC) framework with adaptive cost function and constraints is developed for secondary frequency regulation. For 2), i) the weight coefficients of the cost function can be adaptively adjusted according to frequency deviation through a pre-designed intelligent function, in which the specification of determining the key parameters is involved; ii) the designed constraints' boundaries can dynamically shift with wind velocity and ESU's SoC; iii) the negative impact of model's uncertainties can also be mitigated by implementing the proposed FMPC. Finally, the effectiveness of the proposal is verified by the comprehensive simulation and experimental study, and the results show that the proposal can significantly improve RES's utilization level while guaranteeing frequency regulation performance and operation safety in IMG. [ABSTRACT FROM AUTHOR]

As the solar energy utilization technology for renewable clean energy, actual parabolic trough receivers are subject to tracking errors and absorber tube installation errors, and the bellows and Kovar ring under these errors have a significant impact on the receiver's safety. Based on the MCRT-FVM-FEM principles in this paper, a receiver's optical-thermal-stress mathematical model is modeled and the thermal-stress performance and safety of the receiver's key components under two errors are evaluated. The correlation between the bellows and Kovar ring's performance and the two errors is analyzed. The results demonstrate that the lower tracking errors and larger installation errors markedly increment the absorber's deformation and have a negative impact on the receiver safety. Bellows and Kovar ring's asymmetrical temperature distribution causes variable swell and uneven stress under tracking and installation errors. Temperature gradient variation of bellows is more sensitive under errors than Kovar rings. Kovar ring's compressive stress rises substantially as the Y-directional installation error varied from −15 mm to 15 mm compared to other errors. With tracking errors exceeding 8 mrad, bellows' tensile stress and Kovar ring's compressive stress diminish under installation error. Thus, larger tracking errors significantly reduce the threat to the receiver when installation errors exist. [ABSTRACT FROM AUTHOR]

With the high penetration of renewable energy, its intermittency and volatility also bring challenges to traditional power system such as maintaining reliable operation of system and improving the utilization of renewable energy. Under the background of Energy Internet (EI), energy router (ER) emerges as the times require. Aiming to improve the ability of support of energy storage units to DC buses and suppressing power shocks both inside and outside the ER, in this paper, an ER based on multi-hybrid energy storage system (MHESS) is proposed. As the principle of maximizing the utilization of renewable energy, a corresponding energy coordinated management strategy is proposed. Charging/discharging timespan optimization model is established to ensure MHESS as available as possible. The reference power of MHESS is allocated based on the proposed optimization model. Simulation analysis of different working conditions in 4 operation scenarios are carried out and the results show that the power oscillation on different buses of ER can be dampened within 0.1s and the bus voltages fluctuate within 2% while operation scenarios are switched, which verifies the feasibility and effectiveness of the proposed energy coordinated management strategy. [ABSTRACT FROM AUTHOR]

Over the last two decades, there has been a significant interest in developing solutions to improve the efficiency of power systems, such as optimal energy consumption and management. The demand response programs (DRP) have long been one of the most effective strategies to encourage consumers to change their consumption behavior. In this paper, a novel hybrid DRP has been implemented by combining the time of use (TOU) and incentive-based (IB) DRP methods. To meet the load demand, a PV-WT-BESS hybrid renewable energy system (HRES) has been proposed in this work. Further, to analyze the impact of hybrid DRP on the capacity allocation of different system components, optimal sizing has been performed in two scenarios, one with the actual load and the second with the load after considering the hybrid DRP. The optimization has been carried out by using an improved search space reduction (ISSR) algorithm. To demonstrate the effectiveness of the ISSR algorithm, the obtained results are compared with other algorithms such as particle swarm optimization (PSO), grey wolf optimization (GWO), teaching-learning based algorithm (TLBO), seagull optimization algorithm (SOA), and sine cosine algorithm (SCA). Finally, a novel energy management strategy (EMS) is also proposed in this work on the supply side of the HRES, which intelligently uses the variations in the grid tariff to charge the BESS when the tariff is low. To demonstrate the proposed DRP and EMS-based sizing, a case study has been performed for a grid-connected PV-WT-BESS for the location of Kanyakumari, India. From the results obtained, it has been concluded that the hybrid DRP reduces the peak demand up to 5%, which reduces the levelized cost of energy (LCE) by 22%. Furthermore, the proposed novel EMS reduces the LCE further by 5%. The overall cost reduction of up to 25% has been achieved by using both the proposed hybrid DRP and EMS, while satisfying all necessary constraints. [Display omitted] [ABSTRACT FROM AUTHOR]

Strengthening environmental regulation (Reg) is an important measure to solve energy and environmental problems, then to realize the profit sustainable growth (Gro). Taking 116 listed renewable energy enterprises in China from 2010 to 2019 as samples, this paper uses FE and SYS-GMM models to examine the moderating effect of three types of Reg in the relationship of factor market distortions (Dist) and the Gro. The conclusions are as follows: For the direct impact, capital and labor market distortions (DistK and DistL) hinder the Gro. Specifically, the absolute value of the coefficient of DistK in state-owned enterprises (SOEs) is greater than that of the DistL, which indicates that the inhibitory effect of DistK in SOEs is more significant. For the indirect impact, the coefficients of economic and supervised environmental regulation (RegE and RegS) are positive and significant, and promote the Gro of SOEs and non-SOEs, while legal environmental regulation (RegL) is the opposite, which shows that Reg has significant "cost effect" and "rebound effect". Moreover, Reg has a positive moderating effect, which is mainly reflected in SOEs, and alleviates the inhibitory effect of DistK and DistL on Gro to a certain extent. Finally, this paper puts forward some targeted policy suggestions. [ABSTRACT FROM AUTHOR]

As the penetration of renewable energy sources continues to increase, the stability of the grid is being challenged. Solutions are needed to curb fluctuations in renewable energy generation and ensure a stable electricity supply. As a clean and efficient secondary energy source, hydrogen energy plays an important role in the power system. However, the development of hydrogen energy storage systems is currently limited by technology and costs, making it difficult to scale up. How to invest to make hydrogen storage economical is worth studying. This paper constructs a regional microgrid system, considering the economics of investment by renewable energy generators (REGs) and integrated energy operators (IEOs), and the sensitivity of the payback period under conditions of market adjustment and technological progress. A combination of the Gurobi and Particle Swarm Optimization (PSO) algorithm is used to solve the investment optimization model, and Shapley is used to allocate multi-intelligence benefits. The results show that: (1) the investment returns and payback periods of REG are within a reasonable range; (2) IEO is hardly economical in the presence of market price changes and technological advances. On this basis, this paper constructs a win-win investment model for REG and IEO and explores the distribution of benefits under their cooperation model. The results show an increase in return on investment of 0.34% for REG and 1% for IEO following investments by REG in partnership with IEO. [ABSTRACT FROM AUTHOR]

Renewable energy is regarded as an effective method to alleviate environmental pollution and accelerate the green transition in China. This paper systematically investigates the impact of financial inclusion on renewable energy demand by using S-GMM model based on provincial data in the green finance era. This paper also analyzes the asymmetry, heterogeneity, and mediating mechanism in the nexus between financial inclusion and renewable energy demand, and highlights the following findings: (1) Improved financial inclusion can promote renewable energy development in China and present the characteristics of green finance; (2) the impact of financial inclusion on renewable energy demand is asymmetric and heterogeneous; specifically, this impact is much higher in northern China and the regions with higher renewable energy development; and (3) wind and photovoltaic power generation are effective mediators between financial inclusion and renewable energy industry, while the mediation effects of hydropower and nuclear power are not significant. New evidence in this study is presented for the achievement of green transition in China, as well as practical policy implications for improving financial inclusion and increasing renewable energy consumption. For instance, fiscal and tax incentives and green investment subsidies in the renewable energy sector need to be further improved. • This study explores the impact of financial inclusion (FI) on renewable energy demand (RED) in China. • Asymmetry, heterogeneity, and the mediating mechanism are further discussed. • Increased FI can promote RED , which presents the characteristics of green finance. • The impact of FI on RED is asymmetric and heterogeneous. • Wind and photovoltaic power are effective mediators between FI and RED. [ABSTRACT FROM AUTHOR]

Despite their economic success, the BRICS countries have yet to achieve environmental sustainability. On the other hand, these countries will not be able to maintain their economic expansion if they do not protect the natural environment. In this regard, this paper intends to assess the effects of financial integration (globalization) on ecological footprint. The paper also considers other ecological footprint drivers, including economic expansion, urbanization, renewable energy and technological innovation. The research utilizes a dataset spanning from 1990 to 2018. The study employed the method of moments quantile regression (MMQR) approach, which is robust to cross-sectional dependence and slope homogeneity issues. The outcomes from the MMQR disclose that the effect of financial globalization on ecological footprint is positive across all quantiles (0.1–0.90), thus validating the pollution haven hypothesis (PHH) in the BRICS nations. Furthermore, both renewable energy and technological innovation curb ecological footprint across all quantiles (0.1–0.90). Moreover, technological innovation is proven to impact the environment positively across all quantiles (0.1–0.90) via the path of urbanization. As a result, technological innovation is projected to help the BRICS nations achieve sustainable urbanization. The DOLS, FMOLS, FE-OLS outcomes also validate the outcomes of MMQR. Based on these results, policies were proposed. • MMQR applied to integrate asymmetric effects. • Renewable energy consumption and technological innovation derive ecological sustainability. • Financial integration-led Pollution-haven-hypothesis is confirmed. • Economic growth and urbanization lead to higher ecological footprints. • Technology innovation neutralizes the negative impact of urbanization on ecological sustainability. [ABSTRACT FROM AUTHOR]

This paper evaluates the impact of climate policy uncertainty on renewable and non-renewable energy consumption in the United States over the quarterly data from 2000Q1 to 2021Q3. Economic growth and crude oil prices are added to the energy consumption functions as control variables. The paper considers several approaches to model both renewable and non-renewable energy demand. It is found that crude oil prices promote non-renewable energy demand and climate policy uncertainty reduces it. Surprisingly, the impact of economic growth on non-renewable energy consumption is positive but insignificant. It is also observed that economic growth promotes renewable energy demand, and crude oil prices reduce it. Furthermore, climate policy uncertainty positively affects renewable energy demand in the long run. Some policy implications are provided for reducing non-renewable energy consumption and promoting renewable energy use in the United States through climate policy implementation. • We examine the impact of the Climate Policy Uncertainty (CPU) on renewable and non-renewable energy consumption. • We use the quarterly data from 2000Q1 to 2021Q3 in the United States. • The CPU reduces non-renewable energy demand. • The CPU positively affects renewable energy demand in the long run. • Promoting renewable energy use through climate policy implementation is discussed. [ABSTRACT FROM AUTHOR]

This paper uses panel data on renewable energy in China. Thus, the current analysis fills the gaps by examining the relationship between green technology innovation and renewable energy and CO 2 emissions from 1990 to 2018. The current study examines all concerns connected to panel data analysis with advanced panel estimators, such as cross-sectional dependence, stationarity, variation in slope parameters, and structural break. Our findings show that test results reveal that green technology innovation and renewable energy have a negative and considerable influence on CO2 emissions in the long run. Moreover, the short-run relationship of green technology innovation, on the other hand, is not significant—as evidenced by the findings of robustness tests such as AMG and CCEMG. Other empirical results revealed that GTI, REN and NEN significantly reduced local CO 2 emission, while POP and PI had no obvious reduction effects on CO 2 emissions. Different GTIs had the same spatial "symbiotic effects" on CO 2 emission reduction in the short term, showing positive spatial spillover reduction effects. Lastly, we conclude that the use of green technology innovation has positive externalities. Some policies to assist green innovation technologies and renewable energy resources have been suggested for the Chinese government to enact. • This paper uses panel data on renewable energy in China. • The current study examines all concerns connected to panel data analysis with advanced panel estimators. • The short-run relationship of green technology innovation is not significant. • We conclude that the use of green technology innovation has positive externalities. [ABSTRACT FROM AUTHOR]

Significant increases in renewable energy are needed in electricity systems in order to reduce greenhouse gas emissions, particularly in the face of increasing electricity demand arising from the electrification of heat and transport. Greater flexibility is required in the electricity system to facilitate this, using proven flexibility providers such as batteries and interconnection or new technologies yet to be proven. This paper investigates how the relationship between battery and interconnection development and carbon price can impact carbon dioxide emissions and renewable energy curtailment. The study simulates twenty-eight scenarios and sensitivities using a unit commitment and economic dispatch model of a 2030 European power system that acknowledges that coal will not be fully eliminated from the 2030 generation mix. The results show that interconnection and battery deployment can alleviate renewable energy curtailment by over 2.4 TWh for the basecase, but a high carbon price is critical to ensuring their deployment plays a complementary role in reducing emissions. The paper also examines the impact of batteries and interconnection on solar and wind energy curtailment. It reveals that battery development nearly doubled the solar energy benefits achieved by interconnection development in some cases, while wind energy benefited more from interconnection development. • A high CO 2 price is critical to IC and batteries achieving emissions reductions. • IC can facilitate production of cheaper higher emitting fuels when CO 2 price is low. • Solar energy benefits more from deployment of batteries due to similar timescales. • Diversity of wind profiles can be leveraged with increased interconnection. • Regardless of CO 2 price IC and batteries alleviate renewable energy curtailment. [ABSTRACT FROM AUTHOR]

In the context of climate change, today's adoption of renewable energy sources in isolated power systems is becoming an increasingly more significant issue. Micro-hydro power plants are emerging as a mature balancing technology and a great alternative to large hydropower plants as they do not encounter population displacement and many environmental problems. It is worth noting that hydroelectric power plants combined with various sources require improvement in control laws and algorithms. Strong disturbing impacts, namely transient processes, in an isolated electric power system cause an appreciable decrease in dynamic stability. This paper presents research conducted to ensure synchronous parallel operation of permanent-magnet generators used in micro-hydroelectric power plants in an isolated power system with a controllable flexible coupling between turbine and generator. The importance of this study lies in the issue of electromechanical compatibility to be achieved in parallel operation of generators that have different parameters of time constant of mechanical inertia of rotors of electrical machines. This paper provides an overview of possible solutions to the identified problem. A concept based on a controllable flexible coupling between generator and turbine is proposed as a promising avenue to solve this problem. The mathematical models are presented along with the laws and algorithms developed for automatic control of the generator speed. Oscillograms of simulation and physical modeling presented in the final part of the paper show parallel operation of permanent-magnet synchronous generators in an isolated electric power system for various electrical distances of three-phase short circuit points. • Increasing the dynamic stability of an isolated power system. • Electromagnetic correction of turbine and generator. • Electromechanical transients with controlled flexible coupling. • Mathematical modeling of a hydraulic turbine. [ABSTRACT FROM AUTHOR]

In this paper, we provide an in-depth analysis of factors determining energy import demand of EU countries. We suggest a novel approach to study the role of renewable versus non renewable energy sources in shaping the demand for energy imports. The aim of the paper is twofold. First, we provide a comprehensive analysis of the EU energy market structure using country-by-country I–O tables to show the rate of interdependency between EU member states in terms of renewable and non renewable energy flows. Second, we investigate on the role of renewable energy sources in reducing energy dependency in EU countries. The econometric analysis uses data from 26 EU countries observed between 2007 and 2016 available from the Eurostat energy statistics database. The descriptive analysis of I–O electricity tables shows some degree of heterogeneity between countries in terms of energy in- and out-flows. Such heterogeneous market structure suggests the use of panel models in the econometric analysis. Moreover, a lasso regression method has been employed for variables selection to avoid the collinearity. The results show that benefits may arise from replacing energy imports with domestic energy production and from reducing energy dependency rate. Moreover, if import substitution occurs with domestic renewable energy sources additional positive effects are produced in terms of either energy dependency, energy security and sustainable development. [ABSTRACT FROM AUTHOR]

Increasing the demand for water and energy resources as well as the clean energy policies and the need for pollution emission reduction has developed the research on the renewable energy resources. This paper reviews the recent advances in multi-generation units for heat, electricity, and desalinated water production. It tries to investigate the new papers in this arena which were not mentioned in the previous reviews. The main parts of this work introduce the co-generation systems for the production of "water and electricity", "heat and water", and "electricity, water, and heat". The results show that among the solar energy receiving devices, Photovoltaic/Thermal panels (PV/Ts) and parabolic trough solar collectors are the most used in co-generation systems. On the other hand, a combination of solar collectors and power cycles makes them a suitable choice for the establishment of a large-scale co-generation plant. Therefore, solar collector-based electricity and water co-generation systems have at least 10 times more output capacity than PV- or PV/T-based systems. On the other hand, most heat and water co-generation systems can achieve an output temperature of 60 °C or more and produce around 10000 kg/year of freshwater based on system size. Examining the co-generation systems of water, electricity and heat also shows that these systems have a high production capacity compared to other co-generation systems. Systems based on heliostat solar tower can produce maximum powers of more than 18 MW and fresh water of 90 kg/s. • Recent advances in solar multi-generation units are reviewed. • PV/Ts and parabolic trough solar collectors are most used collectors in cogeneration systems. • RO and MED have more applications in solar-based co-generation units. • Using waste heat can increase technical and economic performance of system. [ABSTRACT FROM AUTHOR]

Using daily data from the beginning of 2018 to the end of 2022 and the Seemingly Unrelated Regression method, this paper sought to determine the relationship between green and non-green cryptocurrency indices as representative of blockchain technologies on three green bond indices in two periods before the outbreak of COVID-19 and the corona period. The preliminary results confirmed that by spreading the coronavirus, the sensitivity of the green bond market has increased to the gold index. In addition, the green cryptocurrency index (Cardano) significantly impacts green bonds more during the Corona era. The negative effect of the Bitcoin index on the index of green bonds in the Corona era is less than its adverse effect in the pre-corona period. Developing green cryptocurrencies and linking cryptocurrencies and digital green financing are two significant recommended policy implications for scholars and policymakers. • Green cryptocurrency has a greater impact on green bonds during the Corona era. • During coronavirus, the sensitivity of the green bond to gold price has increased. • Bitcoin has negative impact on green bond indices before the COVID-19. [ABSTRACT FROM AUTHOR]

This paper investigates the potential of 15 RCEP (The Regional Comprehensive Economic Partnership) member countries to advance green investments from 2000 to 2021. Based on the results from the Panel Pooled Mean Group (PMG) technique, the investment potential has positive short- and long-term coefficients. The EKC (Environmental Kuznets Curve) hypothesis exists, indicating that gross domestic product per capita in the short term is the factor that inhibits the growth of renewable energy consumption. The financial development index has a non-significant coefficient in the short term. However, it has a positive coefficient in the long term. The climate policy uncertainty negatively impacts renewable energy deployment in the short- and long-term. The conclusions provide some policy implications, such as the support of green SMEs, the establishment of a digital green financing market, and the creation of green multilateralism through the establishment of a green investment network. • Environmental Kuznets Curve hypothesis exists in RCEP economies. • Financial development index has a positive and significant effect coefficient. • The climate policy uncertainty negatively impacts renewable energy deployment. [ABSTRACT FROM AUTHOR]

It is becoming increasingly important for human societies to use renewable energy. More effective energy storage solutions are crucial to increase the share of renewable energy in the domestic and industrial sectors, which consumes a large amount of thermal energy for heating and cooling purposes. There has been little quantitative analysis of thermal energy storage in solar-based cold production units. An efficient method of designing heat and/or cold storage systems and smart operation planning can help a cooling/heating system to be smaller for the same capacity of supply and thereby reducing the costs of initial investment and costs of operation. This paper attempts to show how the size of a heat and cold storage system affects its thermal performance and how it can lower costs and emissions. For this, a solar-assisted thermally driven cooling supply system with various designs and integrations of their cold storage unit is simulated dynamically through a whole year in Qassim region as the case study. The results show that a system design with double solar heat storage and double cold storage in parallel arrangement results in the best techno-economic-environmental performance. For this case, the levelized cost of cooling will be 383 USD/MWhr, which will be at least 3% lower than the typical hot/cold buffer tank design scenario. [ABSTRACT FROM AUTHOR]

Hydropower plants play an integral role in energy supply and are one of the main renewable energy sources. The efficiency of hydropower reservoir systems is controlled by operating rules that need to be optimized to maximize energy production. Here, a novel optimization algorithm, influential flower pollination algorithm (IFPA), is developed in this paper. IFPA has three enhancements: an efficient exploration mechanism based on an adaptive coefficient, a new exploitation mechanism around the best solution, and a rank-based strategy to smoothly transition from exploration to exploitation. IFPA is tested in two benchmark multi-reservoir systems and a real-world five-reservoir hydropower system in Iran. The results show IFPA outperforms other advanced methods in terms of convergence speed and preciseness to achieve the global solution. The tested algorithms include adaptive guided differential evolution (AGDE), composite DE (CODE), hybridizing sum-local search optimizer (HSLSO), improved teaching learning-based optimization (ITLBO), self-adapting control parameters in DE (jDE), self-adaptive TLBO (SATLBO), and a multi-strategy hybrid of DE and particle swarm optimization (MS-DEPSO). IFPA also achieved better total power production in the real-world case study compared to other algorithms. Overall, IFPA can provide better solutions with less power deficit and shows as a promising method for optimizing hydropower reservoir problems. [ABSTRACT FROM AUTHOR]

Accurate prediction of renewable energy generation acts as a critical role which not only provides short-term power generation in the future, but also facilitates scheduling and pre-configuration of energy storage systems. More importantly, the power generation prediction is of great significance to the demand response management (DRM) of renewable energy to participate in the electricity spot market. Therefore, DRM helps improve the stability and reliability of renewable energy systems. This paper presents a novel prediction-smoothing based methodology to reduce and eliminate the influence caused by the uncertainty of renewable energy output. Firstly, the Whale Optimization Algorithm (WOA) is combined with Long Short-Term Memory (LSTM) to predict short-term wind power output. Then, the Hampel-Butterworth-SG filtering strategy with outlier regression and specific risk band elimination is introduced. After that, according to the short-term output forecast results, the scheduling and pre-configuration scheme of peak-filling type energy storage is developed. Finally, based on the predicted renewable energy output and electricity price, the dynamic changes of demand response (DR) are calculated based on Logistics function, optimistic response and pessimistic response factors. Through extensive case studies, it is demonstrated that the assessment deviations in different scenarios is less than 5%, which are 0.64% for Scenario 1 and 3.64% for Scenario 2, and no additional penalty is required at this time. In addition, the proposed Demand Response Load Adjustment Rate (DRLAR) help compare the differences between predicted and actual DR, which are DRLAR = 0.03% in Scenario 1 and DRLAR = 0.01% in Scenario 2. Users are able to adjust the DR dynamically according to the electricity price to realize the optimal scheduling of their renewable resources. The proposed methodology creates a special connection between DRM and renewable energy prediction, which provides a reliable reference for future work. [ABSTRACT FROM AUTHOR]

World electricity consumption has grown permanently since 1990, dramatically increasing the emission of greenhouse gases. The worldwide efforts to reduce them and address climate change are leading to the massive electrification of different end-users, increasing the power demand. Therefore, achieving Sustainable Development Goals regarding affordable and clean energy requires the extensive availability of capital investments in electricity generation from renewable sources. Project Finance (PF) is a suitable financing alternative for large projects. This paper presents the advantages of PF contracts in allocating risks to appropriate counterparts and reducing the likelihood of default. Additionally, this study analyzes the characteristics that favor PF financing for renewable energy projects. The results reveal that country's governance levels, well-developed financial systems, and project costs affect the financing probability of a PF initiative, particularly for low and middle-income countries. Therefore, public policies aimed at increasing the availability of resources to renewable projects must tackle these factors. • The world requires massive renewable energy investments to meet Sustainable Goals. • Project Finance is a widely financing structure for large investment projects. • We study the determinants of renewable energy Project Finance. • Low governance and financial development hinder renewable energy PF initiatives. • Policies to develop capital markets and PF will help to reach the net zero target. [ABSTRACT FROM AUTHOR]

In this paper, the authors present a two-step model to obtain quasi-optimal solutions for the storage and transportation of renewable energy as its installation becomes more widespread in remote areas. The model is formulated as a total cost minimization linear programming problem and considers both renewable energy facilities and the energy supply and demand of the entire country. The first step of the model optimizes the entire country, while the second step determines the marginal capacity of energy storage and transportation facilities when the excess production capacity of remote renewable energy is added. This approximation for reducing computational complexity is shown to be sufficiently accurate under realistic conditions. The authors apply the model to analyze energy storage and hydrogen production at renewable energy power plants in Japan in 2050. The study shows that photovoltaic power generation uses storage batteries attached to the power plant for electricity transmission. In contrast, wind power generation transmits most electricity directly without storage batteries and converts some into hydrogen for consumers. The proposed lightweight model allows for numeral sensitivity analyses, which provide valuable insight into optimizing energy storage and transport of renewable energy. • We developed a 2-step model for quasi-optimization of equipment at VRE site. • This model optimizes energy storage and transport with VRE deployment. • If additional VRE is sufficiently small, the model division retains sufficient accuracy. • Energy supply costs minimized by combining power transmission and H 2 transportation. • PV has large LIB, while WT has direct transmission and H 2 production. [ABSTRACT FROM AUTHOR]

The number and importance of renewable energy communities (RECs) are increasing in all European countries due to the support of EU and national policies in order to foster the energy transition through participatory strategies for distributed energy systems. However, their development is rather slow in some countries, including Italy. The paper addressed the issue of the emergence of these socio-technical configurations in Italy, after the related law which entered into force in 2020 allowing the possibility of creating them. Our study focused on the alliances among different actors (professionals, institutions, NGOs, citizens) highlighting possible trends or models for the future that need to be confirmed in further research. The approach proposed to analyse this current process is the Actor-Network Theory, aiming at drawing the assemblages of human and non-human actants at a general level. Accordingly, we selected three case studies in order to show their different ways of organising, the relevance of trust in establishing each REC and the influence of local context on the composition and features of the actor-networks. [ABSTRACT FROM AUTHOR]

Developing new technologies to utilize natural renewable energy resources and fluxes is critical to mitigate climate change and energy crisis. As a renewable energy resource, wave energy is more predictable and has a higher power density compared to solar and wind. However, the technology for wave energy harvesting is still relatively nascent. One of the major challenges as the sector developers is the lack of spatial–temporal representation of wave resources, or wave power generation, from a generic WEC. This paper proposes a novel Wave Net Power Assessment (WNPA) method by utilizing the theoretical Wave Energy Converter (WEC) power limits (including the radiation power limits, Budal's limit, and gross wave power), and applies it to a decade of wave conditions across the USA East Coast, West Coast and Hawaiian Islands. The WNPA method assesses the wave resource from device point of view (unlike traditional gross wave resource assessment) and is generally applicable to WECs regardless of dimension, size, and degrees of freedom (DoFs). The geospatial application of the WNPA method allowed for the analysis of wave power production potential along U.S. coastlines and provides WEC developers meaningful data to make decisions about the best spatial region to deploy certain WECs. Numerical simulations are conducted for WECs with 5 different sizes, 3 different operating modes across the West Coast, East Coast, and Hawaii over 10 years. In addition, productivity, efficiency and gross power quality comparisons are made in terms of the size and degree-of-freedom for WECs deployed at certain ocean sites (e.g., PacWave). A few of the most important findings: (1) The net wave power is dramatically smaller than the gross wave power, which indicates the new WNPA method has a more conservative assessment of the wave power potential; (2) A heaving 10 m WEC is found to have the highest (compared to other sizes and degrees of freedom) absorption efficiency on the West Coast and Hawaii; (3) For smaller 2 m surging/pitching WECs, ocean sites on the East Coast (e.g., Diamond Shoals, NC) maximize power production. (4) There are distinct trade-offs between maximizing power or minimizing power quality and dependencies exists between the location of interest, the WEC size, and the priority degree of freedom. The proposed methodology can be utilized by WEC technology and project developers to conduct apriori preliminary analysis of WEC deployment locations and device characteristics. • Introduction of novel Wave Net Power Assessment (WNPA) methodology for assessing the wave energy resource by providing an upper practical limit of WEC power generation. • Derivation of generic methodology to predict the performance of a WEC; depending only on WEC characteristic dimension and mode of motion. • Geospatial analysis of WEC generation across the US West Coast, East Coast and Hawaiian Islands with five differing WEC sizes, with three different degrees of motion, over a 10-yr period. • Quantification of the mean power, conversion efficiency and co-efficient of variation over a decade. • Ability to quickly understand the spatial and temporal monthly variability of various WEC archetypes in specific locations within US waters. [ABSTRACT FROM AUTHOR]

Wave energy is a huge renewable energy resource with great potential for development. It can be used to power monitoring sensors on offshore work platforms and bridges. In this paper, a novel piezoelectric wave energy harvester based on cylindrical-conical buoy structure and magnetic coupling (C-PWEH) is proposed. As the wave oscillates up and down, it drives the buoy up and down and forces the piezoelectric patches to deform under magnetic force, thereby collecting the energy from the wave. The efficiency of the wave energy conversion can be improved by optimising the design of the buoy. With magnetic coupling, the low-frequency wave motion can be converted into high-frequency vibrations of the piezoelectric patches thus enabling the device to achieve a better output performance. Experiment findings reveal that the C-PWEH may deliver effective energy production when subjected to wave excitation. When the best matching resistance is 5000Ω, the maximum output power of 41.5 mW can be obtained. Under the optimal experimental parameters, 82 LEDs can be illuminated and power storage tests are performed using capacitors, further demonstrating the feasibility of the C-PWEH powering some low-power sensors. [ABSTRACT FROM AUTHOR]

The fundamental way for China to achieve carbon peak and carbon neutrality is to continuously improve the penetration of renewable energy (RE) in the power system and establish an electricity mix dominated by RE power. According to China's 14th Five-Year Plan, the proportion of non-fossil energy power generation should reach about 39% by 2025. However, the impact of the increase in share of RE power on carbon emissions of the electricity sector remains to be estimated. To this end, the purpose of this paper is to capture the nonlinear characteristics of RE on electricity-related carbon emissions by using panel smooth transition regression (PSTR) model and provincial panel data covering the period 1991–2020 under the background of provincial RE quota system. The estimation results indicate that, (i) in the four transition variables of PSTR model such as the installed capacity of power generation, substation equipment capacity, total electricity consumption and total power generation, the nexus between RE deployment and electricity-related carbon emissions was detected as nonlinear. (ii) The heterogeneous RE carbon abatement effect is reflected in its increasing penetration in provincial power systems. (iii) Carbon abatement performance of RE generation decreases in the negative range with the increase of transition variables. (iv) The estimation coefficient of RE is positive at the higher value of the transition variable in the PSTR model of carbon emissions per capita. As a result, the RE quota with the best emission abatement performance should be designed based on the provincial power resource endowment and the medium and long-term expected electricity consumption. [ABSTRACT FROM AUTHOR]

The increase of Renewable Energy (RE) production to fight the climate crisis is posing new technological and financial challenges, due to the availability and variability of RE Sources (RES). These challenges can be addressed by selecting the most suitable mix of RES to optimise power production, to assure grid resilience and to promote local energy use. To facilitate the selection of such combination, this paper presents an original methodology that allows to compare mixing scenarios with different RES, also in presence of batteries and backup system. It simultaneously optimises the energy surplus with respect to the eventual external electrical load and the missing energy with respect to the same electrical load. This method, which can cope with isolated or plugged-to-grid systems, is here applied to a novel case study, an oil&gas platform under decommissioning, located in the Adriatic Sea (Italy). The RE production from wind, wave and solar panels is supposed to support other activities for the platform reuse, such as aquaculture, monitoring and mineral deposition. In this case, solar energy is providing the greatest contribution to the optimal mix in terms of production, while wave energy assures the most relevant contribution in terms of continuity. [ABSTRACT FROM AUTHOR]

This paper aims to examine the relationship between oil prices and the indices of renewable energy and technology companies using Quantile Regression (QR.), Quantile-on-Quantile Regression (QQR), and Granger-Causality in Quantiles (GCQ) techniques. The results show strong evidence of an asymmetric effect at the sum of oil prices and technology companies' index on clean energy, indicating that the relationship is vital when these variables decrease than increase. The main finding of the QQR method demonstrates that the impact of oil prices and the technology stock index on clean energy is higher at the upper quantile than the lower quantile. We also establish bi-directional GCQ indicating the considerable change in oil price led to a change in renewable energy; besides, the outcome of the change in renewable energy does not support the causal link to the variation in oil prices across lower extreme quantile at 1%. Finally, our findings support the bi-directional causality from the tech companies market to the conventional and unconventional energy markets. Results identify the substantial role of renewable energy, with implications for global policy, decision-makers, and fund managers. [ABSTRACT FROM AUTHOR]

In this paper, we explore the co-movements between renewable and non-renewable energy sources and CO 2 emissions and GDP per capita in Saudi Arabia, respectively. Using the spectral Granger causality approach, our results suggested that non-renewable energy sources lead to carbon emission expansion in the frequency domain. Taken together, a significant causal relationship from fossil to economic growth is perceived over the long-term horizon while renewable energy source drives economic growth over different frequencies and considerably contributes to carbon emissions reduction. The wavelet plots revealed strong discrepancies in all variables in the time-frequency space. While non-renewable energy sources indorsed the economic growth across short-and medium-term scales and contribute to a polluted environment, renewable energy consumption has a substantial effect on carbon emission drop and on economic growth in the short-term. The multiple wavelet outcomes show that renewable energy may not only stimulate the economic growth but also promote sustainable and cleaner environment. The combined effects of non-renewable energy sources rise the carbon emissions. Thus, Saudi's government is counselled to promote the green energy investments and accelerate the transition to renewable energy production as its use as a substitute of fossil fuels carries advantages and opportunities alternating from environment to social-economic. [Display omitted] [ABSTRACT FROM AUTHOR]

The development of information and communication technology (ICT), a subset of many functions such as visual communication, can positively affect renewable energy development in different countries. In this paper, focusing on China as the world's largest emitter of greenhouse gases, the relationship between visual communication and the deployment of renewable energy is investigated using the dynamic ARDL (autoregressive distributed lag) method and annual data from 1990 to 2021. Regarding the empirical estimations, a 1% increase in green finance market size leads to an improvement of sustainable energy deployment by 0.01%. In addition, the ICT development index has a significant and positive effect only in the long term. Furthermore, there is evidence of uni-directional causality from ICT to renewable energy deployment in the medium and long term. The recommended practical policies by the research are developing green financing tools, green economic growth policies, and creating virtual portals for financial interactions. • There is uni-directional causality from visual communication to renewable deployment. • ICT development index has a positive effect in the long term. • Effect of GDP on the development of renewable energy consumption is negative. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable energy, the traditional energy storage operation based on individual framework —users own and operate independently mode may become impracticable due to conflicting interests, insufficient utilization, and poor interoperability. Riding on the wave of the proliferation of sharing economy, storage energy sharing expands the existing storage energy without requiring costly and time-consuming infrastructure investments. However, the development path of shared energy storage (SES) mode is not clear due to the asymmetric decision-making of the owners of energy storage systems under bounded rationality. In this paper, the diffusion of the business model of SES among multiple renewable energy stations (the owners, RES) and its key factors are analyzed based on the evolutionary game. The goal is to maximize social welfare and ensure the continuous growth of the sharing market. The numerical simulation is carried out based on the data from northwest China to interpret the development path. The result shows that, in renewable energy cluster the stations with intermittent output or with the higher prediction accuracy are more willing to participate in sharing. The energy storage sharing mode fails when the energy storage capacity ratio of RES is less than 10%. While the high-level ratio (more than 30%) is not conducive to the diffusion of the sharing model in RESs with low power generation prediction accuracy. [Display omitted] [ABSTRACT FROM AUTHOR]

Many subarctic communities rely entirely on fossil fuels for their energy needs. Solar-assisted ground-coupled heat pumps (SAGCHP) can be a solution to integrate renewable energy sources into their energy portfolios. However, it is currently unknown how such systems could operate in the context of the high North (cold ground, extreme mismatch between insolation and heating need, electricity from diesel). The objective of the paper is to develop a detailed model of a SAGCHP heating a house in Nunavik (Quebec, Canada) in order to gain a better understanding of its potential and limitations. The solar assistance is provided by PVs. Simulations with and without electric storage (batteries) were run. A complex tradeoff between four different modes of operation was obtained depending on the conditions of the system at each time step. For the test case, results show that the ground experiences a weak long-term thermal depletion partly compensated solar energy, but that a significant portion of the PV power production is preferably used by the compressor or stored in batteries rather than stored in the ground as heat. Over ten years, the SAGCHP system reduced fuel consumption respectively by 38.2% (without a battery) and 59.1% (with a battery). [ABSTRACT FROM AUTHOR]

By considering the significant role economic growth has played in environmental function between 1990 and 2019, this paper examines the relationships between renewable energy development, trade openness, and institutional quality in the development of green finance in South Asian countries. The effectiveness of institutions and trade transparency are factors in green finance. We use a panel data model to ascertain the cointegration among the variables. The study employs the OLS fixed pool method along with a quantile regression to assess the model and reveal that, although growth in renewable energy development and trade openness worsen the ecological environment, institutional quality and the use of renewable energy promotes green finance development. The findings indicate that trade openness and institutional quality have a positive link with green financing. Institutional quality drives the use of renewable energy, whereas gross domestic product (GDP) drives the environmental impact. In light of these findings, policymakers can put in place beneficial policies for renewable energy development as an economic instrument to minimize ecological footprints and enhance green finance development. • Trade openness. • Renewable energy development. • Green finance. • Institutional quality. [ABSTRACT FROM AUTHOR]

The increasing penetration of renewable energies in power systems demands new services from renewable generation plants. System operators are concerned about system stability since renewable generators behave as constant power sources. Therefore, new requirements have been imposed to grid-following generators to improve their contribution to system stability acting as grid-supporting generators. Nevertheless, grid-supporting control can still compromise system stability for high penetration of renewables, and grid-forming control has arised to ensure proper operation. This paper proposes a novel grid-forming control scheme for doubly-fed induction generators, so they behave as real voltage sources. The proposed grid-forming control is based on the rotor flux orientation to a reference axis obtained from the emulation of the synchronous generator swing equation. The rotor flux is oriented to the reference axis by means of a flux controller that also controls the flux magnitude. The flux orientation in turn allows to control the doubly-fed induction generator torque, while the flux magnitude control allows to regulate the generator reactive power or terminal voltage. The proposed control system has been validated through a comprehensive real-time simulation with hardware in the loop, assessing its grid-forming capability. Moreover, small signal analysis has also been performed to assess system stability. [ABSTRACT FROM AUTHOR]

Renewable Portfolio Standards (RPS) is a mandatory institutional change to promote low-carbon energy transformation and renewable energy development. Its successful implementation requires the scientific design of relevant incentive mechanisms and rules. To make up for the defects in the current RPS mechanism design and the problems exposed in the Tradable Green Certificate (TGC) market, this paper takes China as an example and uses the system dynamics method to study the supply side incentives. The results show that: (1) Scientific setting the relevant system parameters of RPS (such as quota, benchmark price and penalty) and promoting the electricity market reform will effectively stimulate the power generation and investment on the supply side, and improve manufacturers' profit. (2) Higher quotas and lower benchmark prices can increase the manufacturers' power generation, profit and investment, and stimulate the supply side to conduct TGC transactions. However, when the penalty is set at different multiples of the benchmark price, the incentive effect on supply side power generation, investment and profit differ. (3) Marketed on-grid prices can significantly stimulate the supply side and promote renewable energy development. This paper can provide reference for the design of RPS incentive mechanism and institutional parameters. [ABSTRACT FROM AUTHOR]

Renewable portfolio standard is an effective administrative tool to guide the behavior of electricity producers and impact the renewable energy diffusion. However, currently the renewable energy quota is generally set to be static and the efficiency is limited. In this paper, we proposed a dynamic renewable portfolio standard policy and we aimed to analyze how it will impact the renewable energy diffusion in China. The connections between electricity producers were simulated under both the perfectly competitive market and monopoly market. And a networked evolutionary game approach is applied considering dynamic linking between the electricity producers. The results show that dynamic quota policy is effective in promoting the proportion of wind power generation from 20% to 59.17% and promoting the proportion of solar power generation from 20% to 79.25%. With the sensitivity analysis, we found that renewable energy quota and the on-grid price are the most influential parameters. The proportion will reach 76.47% if quota is 0.7 and 68.1% if on-grid price is 630 Yuan/MWh. And the influence of tradable green certificate prices and generation cost is limited in promoting renewable energy diffusion. This paper offers the Chinese government a potential implementation for the perfection of national renewable energy diffusion. [Display omitted] • Propose a novel dynamic renewable portfolio standard scheme. • Analyze the influences of different kinds of the electricity market. • Investigate parameters affecting the wind power and solar power generation. • Establish dynamic networked evolutionary game models. • Dynamic linking is considered when the connections of players change. [ABSTRACT FROM AUTHOR]