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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 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]

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]

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]

Renewable energy adaptation can play a critical role to halt climate change, although many researchers in the past tried to estimate its effect toward the environment, but the findings are still unclear and complex due to limitation of data and adopted methodologies. Therefore, to overcome the weaknesses, this paper aims to re-investigate the role of renewable energy adaptation, financial development and globalization toward environmental quality and economic progress in leading economies, we call it big five economies (B5) of the world. These economies (USA, China, UK, Germany, and Japan) were chosen based on ranking by the IMF. In this paper, we applied panel techniques for data analysis including panel data unit roots test, padroni cointegration analysis and panel data FMOLS and panel DOLS. Further, to explore country specific results and to ensure the robustness of findings, frequency domain causality test was applied. Results of estimation reveal that renewable energy adaptation mitigate the environmental impact to improve environmental quality and reinforce economic progress in B5 countries. Although, financial development, capital formation, natural resources and globalization improve economic progress, but these factors create adverse consequence for the environmental quality. Similarly, it can be stated that it's a tradeoff between economy and the environment. Further, the role of trade is found as constructive for environmental quality and economic progress in B5 economies. We believe that the conclusions of our study hold promise for key insights for the policy development. • This paper adopted panel of Big five economies. • Renewable energy adaptation holds a critical role for the environment. • Financial development in selected economies boost the economic output. • Resources utilization reinforce economic progress and environmental degradation. [ABSTRACT FROM AUTHOR]

Global warming is one of the most important environmental problems in the world. One might state that the most potential considerable cause of global warming is the increase in greenhouse gas emissions in the atmosphere. The commonly suggested method used to struggle with this potential problem is to consume renewable energy sources instead of fossil fuels. In today's World, where the rate of urbanization is very high, the research on the effect of the energy demand of the residential sector on global warming has become a crucial research topic in the energy and climatic literature. Among different solar sectors, the residential sector is a major energy consumer. Considering the residential, commercial, and industrial solar sectors, the residential solar sector has become a major component of total solar energy. It accounts for approximately 43% of total solar. On the other hand, to the best of my knowledge, there exists no empirical study in the literature considering the influence of residential solar consumption on environmental quality. Thus, determining the effect of the most used energy source, residential solar, energy consumption on the environmental quality has arisen the key research problem of this paper. This research analyzes the effects of residential solar energy usage on CO 2 emissions for the period 1989:1–2020:1 in the USA. It has been observed throughout Morlet wavelet analyses that the use of residential solar energy has a strong effect on mitigating CO 2 emissions in the 1–2 year frequency. Eventually, this paper provides relevant potential energy policies that can enhance the efficiency of residential solar energy consumption. Partial wavelet coherence (RSolar-CO 2 || Coal, Hydro, IP), 1989:1–2020:1. [Display omitted] • Considers the impact of residential solar consumption (RSolar) on CO 2 emissions. • Follows the data for the USA for the monthly period 1989:1–2020:1. • Launches wavelet models in which RSolar, CO 2 , Coal, Hydro, and IP are employed. • Reaches the negative impact of RSolar on CO 2 in the USA for the period 1989:1–2020:1 at 1-2 year-cycle period. • Through potential energy policies, residential solar energy consumption efficiency should be increased. [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]

The dispatch-down of excess wind energy is a growing concern, especially for countries integrating high levels of variable renewable energy. Demand flexibility presents an opportunity to move consumers loads to periods of excess wind energy, which could provide numerous values to the system. While previous research has focused on managing wind energy curtailment (a system-wide issue), much wind energy is rejected due to constraint (a local issue) and hence can only be resolved by local load-on-demand. This paper provides a framework to assess the value of demand flexibility for managing wind energy constraint and curtailment. A methodology to determine the optimal number of subscribers to yield sufficient reduction in excess wind energy while ensuring reasonable cost savings for the subscribers is developed. Analysis shows that this optimal number of subscribers could provide a 67% reduction in constraint and a 74% reduction in curtailment. Consumers can save up to £220 per year, depending on their priority in the dispatch process. A 10-MW wind farm could earn £19,400 annually from avoided curtailments. System operators could save up to 78% on constraint payments. The paper also assesses the network impact of flexible loads and provides a methodology for calculating the heat-pump hosting capacity of the grid. • A framework for utilizing wasted wind energy for heating homes is investigated. • Currently wasted wind energy could save fuel poor households up to £220 per year. • A 10 MW wind farm could earn about £20,000 annually from avoided curtailment. • System Operators could save up to 78% on constraint payments. • Mathematical model to determine heat pump hosting capacity of a grid is developed. [ABSTRACT FROM AUTHOR]

Using panel data of 102 countries from 1990 to 2018, this research investigates the varying effect of renewable energy policies on renewable energy green innovation along with the distribution of green innovation. The panel quantile model with additive fixed effect is adopted in this paper, and the research conclusions are as follows. (1) Green innovation positively correlates with national renewable energy policy. (2) Renewable policy is more effective in countries with stronger green innovation capacity. (3) In five different areas of renewable energy, renewable policy is unable to promote green innovation in the lowest innovative countries. (4) Renewable policy exerts the smallest influence on green innovation of geothermal energy compared to other renewable energies. In sum, this paper provides an empirical reference for governments to launch renewable energy policies. [ABSTRACT FROM AUTHOR]

Global economy is developing rapidly and consequently energy requirements has been focused, particularly in developing countries. There are potentials of using renewable energies in the cities and Islands located in Iranian Seas. In this study, five locations in the Persian Gulf and the Gulf of Oman, combining of wind and solar energies have been considered. This paper evaluates the best locations for using different renewable energies in some important cities in the south of Iran. The paper presents a comparative study among different hybrid renewable energies (Wind and Solar) in five cities of Iran located in the coast of the Persian Gulf and the Gulf of Oman namely, Kish Island, Qeshm Island, Chabahar, Jask, and Genaveh. To evaluate the feasibility of using renewable energies in the above-mentioned locations, four types of building namely; hospital, large hotel, medium office, and strip mall have been analyzed. HOMER Software has been used to analyze and optimize different configurations. Considering the load profiles of chosen cases, the optimum solution for different configuration along with cost summary is obtained and analyzed. The simulation results presents that Kish Island owns the most load profile among other cities and PV-Diesel-Battery-Converter is the most suitable hybrid system, which possesses the optimum cost for the considered buildings. Moreover, Chabahar has mostly the most amount of carbon emission for the proposed case studies and owns the maximum lowest cost system among all considered cities except in the case of large hotel where Jask has the maximum initial capital cost. [ABSTRACT FROM AUTHOR]

Given the role that renewable energy consumption plays in transitioning to a low-carbon economy, it is critical for policymakers to understand its determinants. Although uncertainty has increased significantly since the early 2000s, little is known about its effect. To fill this gap, the paper provides novel evidence of the effect of policy-induced uncertainty on renewable energy consumption after controlling for income, institutions and innovation in G7 countries over the period 1997–2019. Using the nonlinear autoregressive distributed lag model, the paper reveals its asymmetric effects in the long run, implying that both a negative and a positive shock in lagged uncertainty reduce renewable energy consumption. The effect of uncertainty proved to be significant in the same direction, but not asymmetric in the short run. However, the effect of all other variables remained insignificant in the short run, which is not the case in the long run. Indeed, the results confirm that income and investment in research and development drive renewables, while it is hindered by more economic freedom in the long run. Therefore, consistent, clear and well-communicated energy and economic policies are called for, along with technological advances, as they can help minimize policy uncertainty and promote renewable energy use. [ABSTRACT FROM AUTHOR]

The continuous increase in global energy consumption as a result of rapid population growth, combined with the detrimental impact of fossil fuels on the atmosphere, has made it critical to extract renewable energy through various technologies and turn it into electricity. A hybrid photovoltaic-thermal collector can be an innovative alternative to harness renewable energy. The utilization of hybrid photovoltaic-thermal solar collectors is increasing day by day due to its advantages. This type of collector can generate both heat and electricity at the same time and convert absorbed solar radiation more efficiently than a solar thermal collector or a typical photovoltaic module. In order to improve the performance of the hybrid photovoltaic-thermal (PV/T) solar collector, nanofluid can be an effective solution. It has been found that serpentine, rectangular, microchannel, sheet and tube, etc., are some categories of geometries utilized in the PV/T system. Both experimental and computational studies were conducted related to nanofluids application in PV/T collectors in recent years. Most of the studies were done utilizing some common nanofluids, e.g., Al 2 O 3 , CuO, ZnO, and SiO 2. It has been noticed that utilizing nanofluids significantly enhances overall performance, thermal and electrical efficiency, heat transfer characteristics, and exergy. This paper comprehensively reviewed various aspects of using nanofluids, including energy efficiency, exergy efficiency, overall efficiency, heat transfer coefficient, daily yield, power generation, entropy production, exergy loss, and temperature drop in hybrid PV/T collectors in a systematic way. Besides, the paper incorporated all recent findings and included experimental, numerical, and combined studies in the review. • MWCNT nanoparticle provides more efficiency compared to oxide-based nanoparticles. • Ag–H 2 O can enhance thermal output up to 13% than the water-cooled system. • SWCNT nanoparticles improve daily yield and have a relatively cheap production cost. • Energetic and exegetic performance can be increased by utilizing nanoparticles. • Using nanoparticles notably enhance power generation rate, and heat transfer ability. [ABSTRACT FROM AUTHOR]

Renewable Energy Systems are considered to be a powerful component of local sustainability innovation strategies. This paper uses a policy mix approach to study innovation policy criteria, which include municipalities' location factors, stakeholder collaboration activities, and local knowledge about renewable energy sources and projects. The aim is to study the impact of these factors on decision-making and developing renewable energy projects and their local sources. Moreover, this paper aims to understand the impact of the mix of different policies on the energy sector and technological innovation systems, through the innovation policy criteria that has been identified. These impacts are studied as they constitute the policy mix, and affect the process of developing renewable energy sources in the Palestinian municipalities and local councils. In this study a sample of 216 Palestinian municipalities and local councils is analyzed. The results indicate the need for policymakers to promote cooperation between the public and private sectors, and the importance of focusing on location factors such as energy import reduction, incentives, and emissions that directly affect renewable energy sources. Whereas, local knowledge does not have a direct impact on the process of developing renewable energy systems, as it can constitute indirect support at a later stage for the implementation of other policy criteria discussed in this study. The results confirm that increasing the potential for developing renewable energy sources takes place when policymakers adopt the role of facilitator and establish a local innovation network in which different actors cooperate so that public and private stakeholders can provide support in order to develop local renewable energy systems. • Different policies impact on RE sector by innovation policy criteria are measured. • The policies and practices of 216 Palestinian local government units are analyzed. • Positioning factors, collaborative activities, & local knowledge standards are used.≥. [ABSTRACT FROM AUTHOR]

The transition to renewable energy is key for sustainable development. Therefore, one of the sustainable development goals (SDG) of United Nations (UN) is to shift towards clean energy. However, in many resource-rich countries several factors can stand as barriers towards the transition process. In this regard, this paper examines the influence of higher oil price, CO 2 emissions, and income on renewable energy consumption in Iran from 1980 to 2019, employing General to Specific (Gets) modeling approach. Estimation results indicated that oil price and CO 2 emissions both have statistically significant and negative impact on renewable energy consumption. The negative influence of higher oil prices on renewable energy consumption may be interpreted as sign of satisfaction coming from higher oil prices, which postpones the transition from traditional energy sources to renewable for Iran. Furthermore, we concluded that income does not have a statistically significant influence on renewable energy use. The paper discusses alternative policies to promote renewable energy consumption. • The effect of higher oil price on renewable energy consumption was studied. • A novel version of General to Specific (Gets) modeling approach was employed. • We found significant, negative impact of oil price on renewable energy use in Iran. • The paper discusses alternative policies for Iran to promote renewable energy use. [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]

Integrating biomass, photovoltaic, and other renewable energy sources for hydrogen production can form a biomass-photovoltaic-hydrogen integrated energy system (BPH-IES). The system features multi-energy storage and joint supply, as well as cascaded utilization, is a promising co-generation way to meet the system's electricity, heat and hydrogen needs, and has significant energy-exergy-economy-environment (4E) performance. Therefore, scientific and effective evaluation of the BPH-IES is an important prerequisite for promoting its development. Firstly, by analyzing the structure of the BPH-IES system, this paper constructs a comprehensive performance evaluation index system of the system from the 4E dimensions. Secondly, a hybrid multi-criterion decision making (MCDM) framework for the 4E comprehensive performance evaluation of the BPH-IES is constructed, in which the anti-entropy weighting method is used to determine the objective weights, the subjective weights are determined by the decision making trial and evaluation laboratory method improved by intuitionistic fuzzy sets, and the final combined weighting results are obtained based on a game-theoretic method that the objective and subjective weights' heterogeneity can be fully minimized. The grey-relation-analysis-based measurement alternatives and ranking according to the compromise solution method is proposed to determine the ranking of alternatives. This paper selected 8 typical BPH-IES cases for 4E evaluation analysis. The results showed that energy performance is the core dimension that reflects the 4E performance of the system, and system's economy indicators such as energy supply income and energy supply cost will also significantly affect the system's 4E performance. Therefore, the 4E performance of BPH-IES can be effectively improved by expanding the system's demand and supply scale and increasing the system's installed proportion of clean energy and hydrogen penetration. Finally, the ranking consistency test, Leave-One-Out analysis and sample separation test demonstrate that the developed hybrid MCDM can ensure robustness meanwhile improve the decision efficiency. [ABSTRACT FROM AUTHOR]

In recent years, the government has attached great importance to promoting innovation in new energy technologies, particularly in the area of solar power generation. Photovoltaic (PV) power generation has become an essential factor in the promotion of renewable energy due to its inherent safety, environmental sustainability and abundant solar energy resources. The efficiency and stability of PV generation systems are closely related to the accurate prediction of real-time global horizontal irradiance (GHI). However, some existing research methods have made some progress in hourly resolution, but the multi-step prediction accuracy and model generalization ability in high time resolution are still unsatisfactory. Therefore, this paper proposes a novel minutely multi-step irradiance forecasting based on all-sky images using LSTM-InformerStack hybrid model with dual feature enhancement scheme. In this scheme, the advantages of both LSTM and InformerStack models are combined to further enhance the global and local features, which can better capture the short-term time series patterns and long-term dependencies and improve the accuracy of the time series. The experimental validation results show that the performance of this prediction scheme is improved by 11.2%, and 26.0% for nRMSE and R2, respectively, and the 24-step prediction can be improved up to 26.1% vs. the persistent model. Meanwhile, the prediction scheme of this paper is also expected to provide a reference in future multi-step time series accurate prediction with higher resolution. [ABSTRACT FROM AUTHOR]

The integration of renewable energy (RE) sources is increasing day by day because of their permanent existence and the limited quantities of fossil fuels. One of the most promising RE sources is photovoltaic (PV) technology, which is developing quickly in many countries worldwide. PV cells generate electricity by converting the sunlight to DC voltage. PV arrays are installed in outdoor areas and on the rooftops of homes to be directly subjected to the sun. Consequently, they are frequently subjected to lightning strikes, which may cause damage to PV arrays, service interruption, and additional cost for PV replacement. Therefore, an adequate lightning protection system (LPS) must be installed to protect the PV panels. In addition, the transient performance of PV panels during lightning strikes must be analyzed well. This paper presents a comprehensive review of the superior modeling methods of PV systems during lightning strikes. In addition, the paper displays the different platforms to simulate the transient effects of lightning strikes on PV systems. The lightning transient effects on PV arrays are studied based on the system modeling to assess the recommended LPS designs studied in the literature. The paper also gives some recommendations about the modeling methods and protection of PV systems during lightning strike. [ABSTRACT FROM AUTHOR]

In this paper, the day-ahead optimal dispatching model of power system that is combined by wind-photovoltaic-hydropower-thermal-pumped storage is established. Firstly, according to the characteristics of the short-term hydropower system dispatching problem, a new mathematical model of the cascade hydropower group system with pumped storage power stations is proposed. The coordinated optimized dispatching model of the hydropower group system formed by the cascading of pumped storage power plants and conventional hydropower in the power system is studied. Secondly, the opportunity constraint programming model of forecast error reserve is used to deal with the output uncertainty of wind power and photovoltaic. The randomness and intermittency of renewable energy on the stability of the power system are overcame by the combination of wind-photovoltaic-pumped storage. Thirdly, the model for the joint optimal dispatch of short-term wind, photovoltaic, hydropower and thermal power systems with pumped storage is developed with system economics as the goal. Fourthly, the operation volatility coefficient of thermal power units is proposed to study the impact of renewable energy on the operation of thermal power. Finally, an example system is used to verify the correctness of the proposed dispatching optimal scheduling model, and the results prove that the daily dispatch optimization model proposed in this paper can increase the economic efficiency of the power system by 5%, reduce the start-stop times of thermal power units by 36.55%, and reduce the fluctuation coefficient of the unit by 2.8. • A new mathematical model of the cascade hydropower group system is proposed. • The integral flow constraint of lag time in the daily scheduling is considered. • The operation volatility coefficient of thermal power units is proposed. [ABSTRACT FROM AUTHOR]

The challenge of global warming requires deep decarbonization of the electricity system, which can be achieved with a higher share of renewables in the electricity mix. However, the driving mechanism for renewable penetration in electricity production has not been clearly revealed so far. Using the data of the European Union (EU) during 2001–2017, this paper aims to investigate the spatial-temporal heterogeneity and dynamic evolution mechanism of renewable electricity penetration. To this end, from the investment-production-consumption perspective, renewable electricity generation is decomposed into seven factors through temporal and spatial factor decomposition methods. Then, this paper integrates the factor decomposition results into a coupling elasticity analysis to study the dynamic evolution mechanism of renewable penetration in electricity production. The results are as follows. (1) Investment structure contributes the most to increasing renewable electricity generation, while the energy intensity effect and renewable generation-to-capacity ratio effect are the main reasons for the reduction in renewable electricity generation. The effect of technological structure is minor. (2) The economic scale effect and the investment structure effect are dominating factors accounting for the regional difference of renewable power generation between the EU countries and the benchmark region. (3) The progress of renewable electricity penetration accelerates over time for the EU, western EU, and eastern EU. The Western EU has realized remarkable progress in facilitating renewable electricity penetration during 2009–2017. (4) On the whole, the investment effect makes the largest contribution to promoting renewable electricity penetration, while the production effect is the major inhibiting factor, showing that there is considerable potential in renewable generation efficiency improvement in the EU. This paper provides insightful implications for energy policies aimed at the shift towards a low-carbon electricity system in the EU, which also gives a reference for other economies. [ABSTRACT FROM AUTHOR]

System risks caused by volatility spillover would possibly threaten the stability of financial markets. Effective control of volatility spillover is conducive to prevent of financial system risks. Therefore, this paper studies volatility spillover in the main renewable energy markets from 2010 to 2019 and analyzes how risks spread in hope of finding effective management to reduce financial system risks. For this purpose, this paper identifies the volatility spillover effect from a multidimensional perspective by using the BEKK model and reveals the risk spread path by using the multidimensional analysis method. Further, the risk spread relationships among the renewable energy markets are comprehensively analyzed. The main findings of the paper are: (1) The volatility spillover in the renewable energy markets tends to exist in the high dimensions. (2) In the renewable energy market system, the volatility spillover relationships involving multiple markets are more complicated than those between two markets. (3) The fuel cell energy market and solar energy markets occupy a significant position in the path of risk spread which should be paid more attention by policymakers to prevent financial system risks. [ABSTRACT FROM AUTHOR]

There has been an increase in the use of renewable energy sources over recent years, which has led to a strand of literature examining the determinants of renewable energy consumption. However, most of the research used linear estimation models while reviewing the determinants of renewable energy consumption and ignored the indirect effect of democratic institutions on renewable energy consumption. With the use of a panel threshold model, this paper demonstrates that democratic institutions play a significant role in renewable energy consumption. In countries in which the democratic rights of people are preserved better, higher economic growth leads to increased use of renewable energy consumption; however, there is a negative association between economic growth and renewable energy consumption in less democratic countries. Increased trade openness leads to lower growth rates of renewable energy consumption in less democratic countries, while increases in real oil prices lead to increased renewable energy consumption in less democratic countries but play no significant role in more democratic countries. The findings of this paper suggest that democratic institutions are vital in channelling economic resources (economic growth) to renewable energy, and increased trade openness is associated with lower rates of renewable energy deployment in less democratic countries. [ABSTRACT FROM AUTHOR]

This paper considers off-grid microgrids (MGs) from the Philippine archipelago and analyses their energy generation in differents aspects. Seven different energy clusters are used, representing realistic configurations and renewable energy shares. A Robust Model Predictive Control (MPC) framework is used for the energy management and coordination task of these island MGs. The MPC is based on a min./max. optimization procedure, which takes into account the whole uncertainty set. The reliability of the MG operations are analysed with respect to the different clusters; this evaluation is conducted using μ -analysis, performed with respect to the baseline model and the uncertainty set. The demand-side compliance of the MG is also investigated, with respect to stochastic behaviours of the demands and of the renewable sources (wind and solar). Numerical simulation results are presented in order to demonstrate that reliable power outlets are produced despite variation in renewables and of the demands. This paper offers a thorough analysis of simple energy system coordinated via MPC, showing how this method can indeed be used for renewable MG management, offering robustness and ensuring reliability. • A generalized model is presented for Off-Grid Microgrids with multiple carriers. • The Philippine Off-grid islands are considered, with diesel, solar, and wind energy. • A Robust Model Predictive Control scheme is proposed to manage these Microgrids. • Demand compliance and operation reliability are assessed through robustness analysis. • Numerical simulation illustrate reliability under multiple scenarios. [ABSTRACT FROM AUTHOR]

The installation of fast electric vehicle charging stations (EVCS) will be essential to promote the acceptance by the users of electric vehicles (EVs). However, if EVCS are exclusively supplied by the grid, negative impacts on its stability together with possible CO 2 emission increases could be produced. Introduction of hybrid renewable energy systems (HRES) for EVCS can cope with both drawbacks by reducing the load on the grid and generating clean electricity. This paper develops a weighted multicriteria methodology to design the most suitable configuration of HRES for EVCS. This method determines the local renewable resources and the EVCS electricity demand. Then, taking into account environmental, economic and technical aspects, it deduces the most adequate HRES power generation planning for EVCS. Besides, an experimental stage to validate the design deduced from the multicriteria methodology is included. Therefore, the final power generation planning for the HRES in EVCS is supported not only by a complete numerical evaluation, but also by an experimental verification of the demand being fully covered. Methodology application to Valencia (Spain) proves that an off-grid HRES with solar PV, wind and batteries support would be the most suitable configuration for the system. This solution was also experimentally verified. • The paper presents a novel multicriteria methodology to design HRES for EVCS. • An experimental stage of the power balance and SOC is included in the methodology. • Valencia (Spain) is chosen as a case study due to its environmental policies. • The best configuration is an off-grid HRES with solar PV, wind resources and batteries. [ABSTRACT FROM AUTHOR]

The global economic costs of environmental pollution increase the importance of renewable energy sources. This paper analyzes the impact of financial development on renewable energy consumption in 34 upper middle income developing countries from 1994 to 2015. The long-term relationship between variables is estimated by applying Panel Pedroni cointegration and Kao cointegration tests. The long run effect of financial development on renewable energy consumption is investigated by using Fully-Modified OLS (FMOLS) approach. The empirical results indicate the presence of long run relationship between renewable energy consumption and financial development. Moreover, financial development increases the demand for renewable energy. Economic growth has a negative effect on renewable energy consumption, but consumer prices have a statistically insignificant impact on renewable energy consumption. The empirical evidence reveals that financial development triggers in increasing demand for environmentally friendly energy sources, i.e., renewable energy. Renewable energy consumption reduces the amount of greenhouse gases in nature as opposed to fossil energy consumption. Therefore, to achieve sustainable development goals, governments should implement incentives and tax policies that increase the demand of enterprises for renewable energy resources. In addition, investment opportunities in renewable energy resources to be created by public-private cooperation via financial arrangements should be increased. - This paper examines how financial development affects renewable energy consumption? - The panel Pedroni cointegration and Kao cointegration approaches are applied. - The Fully-Modified OLS (FMOLS) approach is employed for long run association. - Financial development promotes renewable energy demand. - Economic growth declines renewable energy consumption. [ABSTRACT FROM AUTHOR]

In recent years, harvesting solar energy as a renewable and sustainable energy source has been studied extensively across engineering fields. Having reviewed more than 50 large-scale projects of Hydronic Asphalt Pavement (HAP), this paper offers a series of findings: the range of construction cost of asphalt collector varies between 25 and 151 €/m2 and 1.760–3.000 €/m2 for the heat exchanger and the total cost. The energy harvest capacity of asphalt solar collector systems (0,6–0,8 GJ/m2/year) and the required amount of heat for snow melting projects (100–900 W/m2) vary significantly in different projects. Using grid supports for easier pipe placement and protection of pipes against heavy loads during and after construction is recommended. Pavement solar collector systems reduced carbon dioxide emissions by 8–100% in different projects by changing their source of energy from fossil fuels to renewable and sustainable sources. Moreover, in order to further evaluate the sustainability of the HAP systems, a detailed life cycle assessment is required, including all available data related to the energy performance, pavement service life, material end-of-life recycling, etc. Finally, the paper identifies the knowledge gaps requiring further research especially in the area of energy output of the HAP systems, pavement service life and life cycle assessment. • A comprehensive review of large-scale hydronic asphalt pavement projects is provided. • Potential challenges in the large-scale hydronic asphalt pavement are investigated. • Technical specifications, operational aspects and performance are explored. • Construction cost and structural response of systems are analyzed. • The projects' performance is evaluated based on energy output and sustainability. [ABSTRACT FROM AUTHOR]

Systems involving more than one energy source, namely hybrid systems, can be arranged in different configurations and layouts depending on the available or used energy source, application and scale of the system. Despite an increasing awareness and penetration of renewable energy sources at different scales in many countries over the world, the adoption of hybrid and novel renewable systems is relatively scarce, especially at a small scale. This scenario is also presented from the point of view of the research of such systems. Therefore, the scope of the paper is to improve the knowledge regarding small-scale hybrid renewable energy systems performance and operation by investigating a novel trigeneration system based on a biomass fired steam cycle, wind turbine, photovoltaic panels and adsorption chiller. In the proposed system, the thermal energy recovered by the steam cycle is used to match the user thermal demand by means of a storage tank supplying directly heat to the user during winter, and driving the adsorption unit during summer. The electrical energy produced by the steam turbine, photovoltaic field and wind turbine is managed by a control system that integrates a bidirectional connection with the electric grid. The grid allows one to virtually store the electrical energy produced in excess and to recover it in part when needed by the user. In order to assess the system performance, a farm and residential buildings are considered as case study. The proposed system is modelled and dynamically simulated by means of Transient System Simulation software. In the paper, the dynamic operation of the system and the energy and economic performance of the system is assessed. The operation of the system is presented in a daily and monthly basis, while the global performance parameters of the system are reported considering a one-year period. The primary energy saving of the system is above 70% when a reference system based on natural gas, electric chiller and grid is considered. For this scenario, the Simple Pay Back of about 10 years is achieved. The results of the analysis show that the system is feasible from the technical and energy point of view, whereas its economic profitability is significantly affected by its cost and the reference system that is adopted by the user. • Modeling and dynamic simulation was performed with TRNSYS software. • Energy and economic performance of the system was assessed. • Different reference systems are considered for heating. • Primary Energy Saving ratio was between 57.4 and 73.3%. • The minimum Simple Pay Back is about 10 years. [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]

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]