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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]

• We employed MRA to specify the authentic empirical effect based on 328 estimation results from 33 primary studies. • Financial development leads to higher renewable energy consumption / use / capacity / production according to the MRA. • There is no publication bias in the existing literature. • The authentic empirical effect may change depending on financial development or renewable energy indicators used, time period covered, the unit analyzed, and the estimation technique employed. • There is an omitted variable bias in the existing literature. The current paper tries to determine and quantify the authentic empirical effect of financial development on renewable energy beyond publication selection bias, if any, based on 328 estimation results from 33 primary studies that were published or presented over the period of 2009-2022. Bivariate and multivariate FAT-PET analyses were used as tools of meta-regression analysis. A positive significant authentic empirical effect of financial development on renewable energy is found as a first contribution. Hence the results support Hypothesis 1; by offering more reliable, efficient, and less costly funds to investors; whether private or public, financial development boosts renewable energy. An absence of publication bias is resulted regarding the overall findings of the primary studies or design characteristics (moderating variables) as a second contribution. Based on the results for moderating variables, the authentic empirical effect may change in direction and magnitude due to the financial development or renewable energy indicators used, the time period covered, the unit analyzed, and/or the estimation technique employed as a third contribution. Omitted variable bias is found in the existing literature analyzing this subject. [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]

As stated in Sustainable Development Goals number 6 and 13, clean water and sanitation and energy-related carbon emissions as climate action issues have emerged as serious issues within the United Nations. Around 150 countries rely on seawater desalination plants as their water resource. Reverse osmosis membrane technology is the most widely used seawater desalination technology for water supply. Taking water resources, developing renewable energy, and recycling resources have become the United Nations' core sustainable development goal. Therefore, this paper aims to provide an overview of renewable energy in reverse osmosis, especially newly developed renewable energy such as wave power. This paper includes technical issues, environment, and economic impact. In addition, compared with other energy sources, photovoltaic and hydropower energy utilization leads to a lower carbon footprint. Both energy produce a carbon footprint of around 0.08 kg CO 2 eq/m3. Control systems and energy storage management are the challenges in developing integrated renewable energy with reverse osmosis. Suitable pretreatment and the effect of direct use of renewable energy on the reverse osmosis process, especially on membrane and pump lifetime, should also be considered in future studies. [Display omitted] • Fluctuations and intermittence in wind and PV would affect on the process performance. • Energy storage management helps to keep the system stable • Water storage can assist in having enough water and store extra • PV and hydropower energy produce carbon footprint around 0.08 kg CO 2 eq/m3. [ABSTRACT FROM AUTHOR]

The energy sector prioritizes innovative clean energy production. This research explores a versatile hybrid solar-biomass trigeneration system, integrating organic Rankine cycle (ORC), a heat pump, and a proton exchange membrane electrolyser. Sustainable and adaptable, it produces electricity, heating, and hydrogen for Indian paper and pulp industries. The study assesses the system's thermodynamic, economic, and environmental feasibility. Initially, parametric analysis and first layer multi-objective optimization (MOO) are performed to select the efficient working fluid and operating temperatures. Benzene outperforms other fluids, achieving an energy utilization ratio (EUR) of 0.27 and exergy efficiency of 75 %. A typical heat requirement of 250 kW for processing 150 kg of paper necessitates collector areas of 3500 m2 and 4500 m2 in Aurangabad and Tiruchirappalli, respectively, and biomass waste of 0.05 kg/s. The combined system performance during day time and night time operation was studied by altering the critical solar radiation, ambient temperature and biomass waste flow rate. The second layer MOO revealed an optimum EUR of 0.25 and exergy efficiency of 9 % at the lowest cost of 33 $/h for biomass waste operation. In comparison to the conventional electricity-powered system, the proposed system would reduce CO 2 emissions by 90 kg/h to 270 kg/h. [Display omitted] • Solar and biomass waste powered systems proposed for paper and pulp applications. • ORC integrated heat pump system for heating, electricity, and green H 2 generation. • Collector area and biomass flow rate are designed for daily paper output of 300 kg. • Benzene is an efficient working fluid, produced 815 kW of heat and 3 kg/h of H 2. • The recommended system reduced CO 2 emissions by 90 kg/h to 270 kg/h. [ABSTRACT FROM AUTHOR]

The motivation of this paper is to investigate the resistance of countries' energy research and development (RD&D) expenditures to random shocks. The analysis includes the five countries (France, Germany, Japan, the United States, and the United Kingdom) that are the biggest investors in RD&D in fossil fuels, renewables, energy efficiency, and nuclear energy. Thus, economies will be able to take precautions against global shocks in producing sustainable energy policies. To achieve this aim, this paper uses the artificial neural network approach, which uses a distributed computing model that can store and generalize data after a learning period. Empirical results widely depend on countries and distinct energy technology policy fields. The key findings provide evidence that RD&D expenditures, except for renewables, do not tend to mean revert. The economies of Japan, Germany, and the United States should make more renewable investments to reduce the resistance of renewable energy sources to shocks and thus produce policies for both environmental sustainability and energy security. The economies of France and the United Kingdom can ensure energy security by continuing their sustainable energy policies. • Applied SDG policies focused on energy technology RD&D are presented. • The stochastic characteristics of energy technology investments are examined. • Carbon-reducing policies are recommended for the top five economies. • Energy technologies are perused through artificial intelligence approach. [ABSTRACT FROM AUTHOR]

Carbon emission flow is an effective tool to obtain carbon emission distribution in power systems, which can guide the active carbon reductions of consumers through proper incentive schemes. With the increasing penetration of renewable energy, the existing single-valued carbon emission flow model based on deterministic forecasted power outputs cannot describe the impacts of renewable energy uncertainties on carbon flows. Therefore, this paper mainly focuses on the assessment of the probabilistic carbon emission flow through the power systems considering the impacts of load and renewable energy uncertainties. In this paper, the probabilistic carbon emission flow (PCEF) is innovatively proposed. With the PCEF, consumers can make better energy use plans considering their own risk appetites for carbon emission payment. Firstly, the impact factors of the PCEF are modeled, including load and renewable energy uncertainties and integrated carbon intensity of thermal plants. The uncertainties of load, wind power and photovoltaics are modeled based on a p-box method while the uncertainty of hydropower is modeled based on the multi-state model. Besides, the integrated carbon intensity model of thermal plants are proposed considering the carbon intensity variations during the operating, start-up, and shut-down stages. Furthermore, the probabilistic carbon emission evaluation framework is proposed to assess the probabilistic carbon distribution. In this framework, novel probabilistic carbon indices are defined to precisely characterize the carbon emission situation with probabilistic representations. A solution method based on an adaptive interval point estimation (AIPEM) algorithm is proposed to efficiently solve the developed evaluation problem. Tests on an IEEE-30 node system, and a real provincial power system in China validate the effectiveness and application of the proposed model. The results showed that the PCEF can be a useful tool for obtaining the probabilistic representation of carbon emission flow and guiding the consumers' active carbon reduction in power systems. • Probabilistic carbon emission flow is proposed considering multiple uncertainties. • Integrated carbon intensity model for thermal plants is developed. • A p-box model is used to describe the uncertainties of load and renewable energy. • PCEF can help consumers balance the cost and carbon risk when making decisions. [ABSTRACT FROM AUTHOR]

In recent decades, the use of fossil fuels has had a harsh impact on the climate, and the frequency and intensity of various extreme weather events have increased, which has triggered an increased the use of renewable energy sources and reflection on technological advances. Many countries are trying to promote renewable energy to reduce their impact on climate change, but the impact of national energy policies in the climate risk framework remains poorly understood. Based on the panel data of 84 developed/developing countries around the world from 2006 to 2019, this paper studies and analyzes the impact of renewable energy use on climate risk. The study found that the increase in the proportion of renewable energy use can reduce the climate risk, and this result is still robust after undergoing robustness tests such as changing variables, samples, and research methods. The findings offer an important solution for European countries, where climate risks are most acute. The heterogeneity analysis shows that the higher the level of economic development, population density and the lower the level of incorruptibility, the weaker the inhibitory effect of renewable energy use on climate risk. The mechanism analysis also shows that the increase in the proportion of renewable energy use can reduce climate risk by reducing carbon dioxide (CO 2), methane (CH 4), nitrogen monoxide (NO), PM2.5 emissions, and the proportion of fossil fuel use, but it does not reduce climate risk by increasing biodiversity. In particular, we find that technological progress has not played a role in the use of renewable energy to reduce climate risk, breaking the stereotype. The policy recommendation of this paper is that under the increasing pressure of climate change, the transition to clean energy is an indispensable option, and the need to accelerate the energy transition becomes more urgent. There is a greater need to further protect biodiversity and enhance technological progress. • The increase in the proportion of renewable energy use can reduce the climate risk. • The mechanism is to reduce CO 2 , CH 4 , NO, PM2.5 emissions and fossil fuels use. • The use of renewable energy cannot reduce climate risks by increasing biodiversity. • The impact of renewable energy use on climate risk is heterogeneous. • Technological progress has not played a role in the use of renewable energy to reduce climate risk. [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]

This study analyzes the impact of green finance and renewable energy on energy efficiency in E−7 economies. We analyzed the nonlinear and asymmetric effects of green finance and renewable energy on energy efficiency. We collected data from 1985 to 2017 and applied the NARDL and 2SLS methods. The results reveal that the differences in green finance development in the E−7 region are as follows: China (0.61), Brazil (0.55), India (0.53), Indonesia (0.49), Mexico (0.37), and Russia (0.39). In 2019, the Gini coefficient was the largest in Russia (0.57), followed by Turkey. Based on empirical findings, the largest barrier to green energy efficiency is insufficient private and governmental investment in the energy sector to improve access to power, to increase energy security and promote economic growth in an environmentally sustainable manner. The findings point to a promising but vulnerable future for renewable energy and energy efficiency deployment in E−7 countries. This paper emphasizes that green financing and renewable energy policy limitations must be addressed to realize the funding potential of energy efficiency in E−7 countries. • We have analyzed the barrieres for renewable energy and energy efficiency. • Non-linear and asymmetric effects is observed on energy efficiency. • We have applied NARDL model to examine the relationship among variables. [ABSTRACT FROM AUTHOR]

Hydropower renewable energy is known to be pro-environment: flexible and affordable. Above all, it is compatible with other energy frames and also with the policies that otherwise prove to be inimical towards its future. Where environmental stability is concerned it needs an assiduous study coupled with research by the policymakers to get around knowing the different perspectives of hydropower renewable energy. The study has taken nine different and diverse perspectives of hydropower renewable energy into account to stop the process of environmental degradation. EKC framework has been put to use in a case study of South and East Asia economies. Time period has been selected from 1975 to 2020 to measure the long-term impact. GMM model has been used for the panel estimation besides getting future dynamics. The results which have come about confirmed EKC in the selected countries. Non-renewable energy (coal and gas) had an adverse impact on environmental stability. However, switching towards hydropower renewable energy can mitigate these environmental losses. Empirical findings have proved that more use of clean energy production can bring about a considerable amount of environmental stability. Insofar as East Asia economies are considered they have reached the second stage of EKC with a turning point of $13844 (per capita income). This paper, therefore, suggests that the future depends upon renewable hydropower energies in South and East Asia economies. That being said, there appears to be a dire need to undertake the role of various socioeconomic and geographic factors that influence hydropower renewable energies to check the long-term effect. [Display omitted] [ABSTRACT FROM AUTHOR]

In the background of exhaustion of the traditional fossil energy sources and environmental deterioration, developing renewable energy has become a strategic choice for countries to achieve energy sustainable utilization and carbon neutrality target. Different renewable energy technical plans have different characteristics under multiple criteria. Therefore, before the further exploitation of renewable energy sources, it is of great significance to evaluate the comprehensive performance of different plans and then determine the best renewable energy sources. However, the commonly used weight calculation methods in the existing renewable energy evaluation have obvious shortcomings, such as the randomness of the subjective method is strong and the gap in the weight allocation of the objective method is too large, which affect the reliability and accuracy of the sorting result. In this paper, a novel weight calculation method based on non-dominated sorting genetic algorithm (NSGA-II) is proposed, and is applied to renewable energy evaluation. The study in this paper focuses on methodology. Firstly, for the linear normalized and Zeros normalized evaluation data, the differences between renewable energy plans in the two normalized evaluation data are measured, and the ranking deviations of the two normalized data are calculated. Then, the multi-objective weight solving model is constructed in terms of plans differences minimization and ranking vectors deviations minimization. The NSGA-II algorithm is applied to the optimization of multi-objective functions to find the Pareto non-dominated solution, so as to determine the weight values of each evaluation index. Finally, the TOPSIS method is used to determine the relative closeness value of each plan, and the rankings of renewable energy technical plans are achieved. Based on the actual renewable energy development data of a province in China, experiments were carried out to investigate the effectiveness of the proposed method. Experimental results show that the proposed method performs better than some popular renewable energy evaluation methods. [Display omitted] • Propose a novel evaluation method for renewable energy technical plans. • Apply non-dominated sorting genetic algorithm II to determine the index weights. • Compared with the existing evaluation method, the proposed method performs better. [ABSTRACT FROM AUTHOR]

This study aims to investigate the factors of renewable energy consumption in the fifth Technology Revolution with specific evidence from ASEAN countries. The study applies an autoregressive distributed lag (ARDL) approach. The paper also uses the unrestricted fixed and random panel data methods. The manuscript identifies significant factors such as technological innovation, governmental policies, public awareness, electricity consumption, country population, foreign direct investment inflows, imports, exports, and economic growth that have influenced the renewable energy sector in these nations. This study also investigates the determinants that influence renewable energy in the context of international integration and the fifth technology revolution in ASEAN countries. The research analyzes data spanning two decades, from 2000 to 2022, through a combination of econometric modeling and machine learning techniques. Preliminary findings indicate that technological innovation, government policies, and public awareness significantly affect renewable energy consumption in these countries. The empirical results offer insights for policymakers and stakeholders in leveraging technological advancements for sustainable energy development. The findings from this study on the determinants of renewable consumption in the context of the Fifth Technology Revolution in ASEAN countries also have several important policy implications for the sustainable development goal. • This study aims to investigate the factors of renewable energy consumption in the fifth Technology Revolution. • The study uses panel data analysis, and the paper identifies significant factors that have influenced the renewable energy sector. [ABSTRACT FROM AUTHOR]

• The study makes the following main contributions: • 1) A mathematical layout is developed to include renewable resources for load scheduling in digital twin-based microgrids. • 2) Uncertainty modelling of PV production employing Beta PDF for load scheduling is utilized in digital twin environment. • 3) The load scheduling algorithm employing RL for minimizing the energy bills regarding a renewable resource is developed. Utility companies recognize the importance and necessity of demand response (DR) programs for reducing the increased production costs associated with rising energy demand. The advent of smart information and communication systems has made DR programs on the basis of cost a viable option to control load in smart microgrids. Small domestic consumers are rapidly using stochastic renewable energy resources such as photovoltaic (PV). The study examines an integrated layout for residential load scheduling or load commitment problems (LCP) with renewable energy resources no matter what kind of tariff is applied. Uncertainty-based decision-making problems are effectively solved using reinforcement learning (RL). The paper proposes an RL-enabled solution to the LCP in smart microgrids. An innovative aspect of the study is the development of an integrated layout containing an implementable solution that takes into account user satisfaction, stochastic renewable power, and tariffs. In simulation tests, the suggested layout is tested for its effectiveness and flexibility. An analysis of the algorithm's efficiency using a household user with schedule-able and non-schedulable devices, together with a PV resource, has been presented. [ABSTRACT FROM AUTHOR]

This paper aims to holistically study hydrogen production options essential for a sustainable and carbon-free future. This study also outlines the benefits and challenges of hydrogen production methods to provide sustainable alternatives to fossil fuels by meeting the global energy demand and net-zero targets. In this study, sixteen hydrogen production methods are selected for sustainability investigation based on seven different criteria. The criteria selected in the comparative evaluation cover various dimensions of hydrogen production in terms of economic, technical, environmental, and thermodynamic aspects for better sustainability. The current study results show that steam methane reforming with carbon capture could provide sustainable hydrogen in the near future while the other technologies' maturity levels increase and the costs decrease. In the medium- and long-terms, photonic and thermal-based hydrogen production methods can be the key to sustainable hydrogen production. [Display omitted] • A holistic study of hydrogen production options for a sustainable and carbon-free future. • It outlines the benefits and challenges of hydrogen production methods. • Sixteen methods are selected for sustainability investigation based on seven different criteria. • It covers economic, technical, environmental, and thermodynamic aspects of sustainability. • It can help stakeholders deploy a hydrogen roadmap for a more sustainable future. [ABSTRACT FROM AUTHOR]

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

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

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

• The effect of renewable energy on value-added in the agricultural, industrial, and service sectors is examined. • Renewable energy significantly enhances value-added in the three sectors in the long-run. • Renewable energy does not matter for sectoral value-added growth in the short-run. • One-way causality from renewable energy to agriculture value-added and from service value-added to renewable energy. • No causal relationship between renewable energy and industry value-added. A growing number of studies have investigated the growth-renewable energy nexus with mixed findings. However, they have mostly focused on aggregate growth ignoring the sectoral level differences. Like economic growth, it is been argued that there are sectoral dynamics in the determinants and impact of renewable energy. Hence, this paper examines the effect of renewable energy on value-added in the agricultural, industrial and service sectors in a selected sample of 12 Sub-Saharan African countries from 1985 to 2017. The findings from the PMG - ARDL model show that renewable energy significantly improves value-added in these sectors in the long run with the highest impact in the service sector. In the short run, however, renewable energy does not have a significant effect on sectoral value-added. Also, findings show that nonrenewable energy consumption significantly enhances the service value-added whereas capital and labor spur value-added in the three sectors. Finally, the causality test unveils a unilateral effect from renewable energy to agriculture value-added, from service value-added to renewable energy, and a neutral relationship exists between renewable energy and industry value-added. These findings suggest investments in renewable energy are long-term in nature. In the short term, however, governments could provide financial incentives such as subsidies and/or tax exemptions to boost the adoption of modern and more energy-efficient technologies across economic sectors. [ABSTRACT FROM AUTHOR]

[Display omitted] • PCM energy storage and PV/T coupled multi-source heat pump systems were combined. • The thermal performance, energy efficiency, and economy of the system were analyzed. • The performance of paraffin C17 and water as energy storage materials were compared. • The performance of six low-temperature PCMs applied to the system were analyzed. • Compared to the existing system, it saves 56 % of energy and 27.7 % of operating costs. To improve the application of renewable energy in the heating zone, as well as to address the limitations of air and water source heat pump. The study presents a PV/T (photovoltaic/thermal) coupled air–water source heat pump system integrated with phase change energy storage. A theoretical analytical model and TRNSYS simulation model of the system were developed to evaluate the thermal performance, energy efficiency and economics of the system. The performance of phase change energy storage was compared with that of water storage, and the effect of different phase change materials on the system characteristics. The results show that the coupled system achieves a seasonal performance factor of 2.3, a 56 % reduction in energy consumption, and a 27.7 % reduction in operating costs compared to a conventional gas boiler system. Comparative analysis with the water storage system showed that the system equipped with phase change materials performed well in terms of energy consumption, operating costs and heating stability. In addition, the density of the phase change material has a biased effect on the overall performance of the system. This paper can provide a reference value for the study of renewable energy heating systems in cold zone. [ABSTRACT FROM AUTHOR]

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

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

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

The proliferation of charging stations entails multiple challenges for power systems. In this regard, the installation of photovoltaic-battery systems may help to mitigate the negative effects of charging points. However, such assets should be carefully planned, paying attention to economic aspects, principally. Most of existing works optimize the photovoltaic-battery system in charging infrastructures taking a representative-space of the involved variables (e.g. photovoltaic potential, charging demand or energy prices). However, this approach tends to ignore low-probable scenarios. Thus, the best-case scenario for charging demand (i.e. that for which the highest charging profit is accessible) may not be included in the analysis and therefore such demand could be not attended properly, thus losing this monetary opportunity. This paper focuses on this issue and questions if considering the best-case scenario into planning photovoltaic-battery systems for charging stations is worthwhile or not. To this end, a novel best-case-aware planning tool is developed, including the best-case scenario through a novel chance-constrained formulation. The overall problem is then decomposed into a master-slave structure by which the economy of the system is optimized together with the number of scenarios for which the best-case profile can be attended. A case study serves to validate the developed tool and shed light on the questions arisen in this work. In particular, it is checked that considering the best-case scenario into planning tools is questionable from a monetary point of view. Nevertheless, its inclusion unlocks some collateral advantages such as incrementing the users' satisfaction or reducing the grid-dependency. [ABSTRACT FROM AUTHOR]

With the growing share of the climate-sensitive renewable energy market supply in China, estimating future energy drought risk (ED) is essential. In this paper, based on CMIP6, energy demand and power generation are estimated from 2023 to 2100 under SSP2-4.5 and SSP5-8.5 climate scenarios, and ED is defined from high demand (HD), low wind-solar generation (LWS), and residual load (RL). The results show that the ED exacerbation is relatively high under the SSP5-8.5. Between 2023 and 2100, the duration and severity of HD and RL notably increase, while LWS changes are relatively weak. We find that HD and RL exhibit high summer risks in the south and high winter risk in the north. The return periods vary significantly and extends over time in most regions. Moreover, there are few ED when the installed power generation capacity (IPGC) is increased. When the IPGC increases by 2%–5%, the LWS will decrease at least 20%–72%. With a 10% increase, the LWS will be mitigated by at least 80%, whereas the mitigation for RL is limited, approximately 3–17% at different rates. This work performs the first evaluation of future ED and provides the useful references for risk mitigation in China based on CMIP6. [ABSTRACT FROM AUTHOR]

The drive for improved energy efficiency and flexibility has birthed an innovative solution: an energy hub. This hub operates in sync with natural gas and electricity grids, integrating batteries and thermal storage to optimize renewable energy use, reduce costs, and bolster network stability. In addressing these objectives, a mathematical optimization model for energy hub operation is developed in this paper. This model captures the intricate interplays between electricity and natural gas networks, accounting for the intricacies posed by uncertainties and variations in renewable energy sources and demand profiles. Also, this paper uniquely delves into the integration of load response programs, an approach geared towards amplifying the energy hub system's flexibility and reliability. Through these programs, subscribers gain the agency to calibrate their energy consumption based on real-time pricing signals and incentives dispensed by the energy hub. The simulation findings serve as a compelling testament to the efficacy of the proposed system. Operating costs witness a substantial reduction, the adoption of renewable energy sources is markedly heightened, and the stability and reliability of the upstream energy networks are tangibly ameliorated. The integration of load response programs emerges as a particularly effective strategy in mitigating peak demand and augmenting the system's overall energy efficiency. Underpinning the entirety of this innovative solution is the transformation of the challenges into an optimization problem. This catalyzes the employment of a newly developed particle community algorithm, custom-tailored to surmount the challenges of local optima. This algorithm inherently bolsters the system's search capabilities, minimizing the risk of entrapment within localized solutions. Ultimately, the proposed energy hub system encapsulates a promising trajectory toward the realization of a sustainable and adaptable energy landscape. By seamlessly integrating diverse energy sources and storage systems, augmenting energy flexibility and efficiency, and aligning with broader energy transition and decarbonization goals, this solution presents a formidable contender. The simulation outcomes underscore its potential by showcasing a substantial 4.57 % reduction in the cost of procuring energy from the upstream electrical network. • Holistic energy hub engages in upstream electricity and heat markets, optimizing profit. • Empowered energy hub actively influences markets with optimized strategies. • Robust optimization ensures stable operations in uncertain renewable sources. • Advanced load management optimizes profiles, aligning consumption with pricing. • Particle swarm optimization algorithm enhances search for optimal solutions. [ABSTRACT FROM AUTHOR]

Innovation and adaptation of renewable energy technologies significantly reduce carbon dioxide (CO2) emissions and increase energy efficiency. Understanding the convergence patterns in renewable energy innovation will enable policymakers to design policies to increase energy efficiency and renewable energy consumption and reduce CO2 emissions. This paper applies the convergence algorithm proposed by Philips and Sul to assess the convergence in renewable energy innovation for 90 countries covering the period between 1993 and 2018. This paper also examines the determinants/factors driving the convergence clubs of the countries using Probit and Logit regression. The convergence analyses suggest that there is no global convergence in renewable energy innovation. Findings highlight two convergence clubs: i) a club comprising more innovative countries and ii) another club that includes less innovative countries. We find that countries with higher income per capita, CO2 emissions per capita, research and development (R&D) investment, better environmental regulations and stronger institutional settings are more likely to be part of the innovative club. Countries should increase their R&D investment and environmental regulations and improve their institutional quality to increase their likelihood of belonging to a more innovative club. Furthermore, less innovative countries could promote policies to transfer renewable energy technologies from innovative countries. [ABSTRACT FROM AUTHOR]

[Display omitted] • SAMA, a new open-source microgrid optimization software, was introduced an validated. • Validation compared SAMA's results with industry-standard, Homer Pro proved accuracy. • Results for different locations and climates, confirming SAMA's reliability and accuracy. • SAMA introduces unique emission optimization and top-down pricing methodology for first time. • SAMA is open-source and free, which ensures accessibility and fosters innovation. • SAMA is broadly applicable for renewable, off-grid, grid-tied, and backup power systems. Although there are many software tools for simulations of hybrid energy systems, Homer Pro and Homer Grid are the only tools offering optimal sizing of hybrid energy systems. Originally developed as open-source software, they have been closed, which limits user-developers abilities to adapt and improve the software. In addition, all current proprietary offering suffer from the following limitations: i) high costs that limit accessibility to low-resource labs and individuals, ii) incapable of conducting multi-objective optimization, iii) constrained on any new innovations in hybrid energy system design and operation, iv) difficulties for users to specifically define prices and costs in inputs, v) inability to model different electric utility billing structures, vi) complex pricing methodology, and vii) the absence of machine learning-based predictive modeling. To overcome these limitations, this paper introduces and validates SAMA (Solar Alone Multi-objective Advisor), an open-source microgrid optimization software program designed to optimize hybrid energy system sizes economically using metaheuristic algorithms based on specific load profiles and meteorological data. Through rigorous validation exercises, SAMA's outcomes are compared against those generated by the Homer Pro software across distinct climatic conditions and geographical locations (i.e., Sacramento, California in the marine west coast and New Bern in humid continental climate zones of U.S., respectively). The results demonstrate congruence between SAMA and Homer Pro. SAMA can be used for a diverse array of applications from renewable energy systems to off-grid and grid-tied configurations, and from policy formulation to feasibility assessment. Unique features of SAMA include multi-objective optimizer, levelized emission optimization, different pre-defined utility billing structures, and a top-down pricing methodology. These features further enhance SAMA's adaptability, allowing users to tailor the software to their specific needs and system configurations. Finally, the paper anticipates future advancements that could refine component modeling, accelerate optimization processes, and incorporate advanced data analysis techniques such as machine learning to predict energy demand and production patterns. [ABSTRACT FROM AUTHOR]

Malaysia is one of the leading producers and exporters of oil palm, and the industry contributes significantly to the growth of the national economy. Nonetheless, the consequential oil palm biomass (OPB) with a potential yield of ∼97 million tonnes annually presents both challenges and opportunities, demanding innovative waste management solutions. This paper explores the feasibility of converting OPB into valuable commodities by employing concentrated solar-driven pyrolysis. A detailed overview of the biomass produced from oil palm plantations and mills is provided, along with a discussion of the industry stakeholders and associated biomass management challenges. The pyrolysis of OPB is explored, emphasizing benefits, potential barriers, and techniques. The focus then shifts to Malaysia's solar potential, which ranges from 1470 to 1900 kWh/m2 annually. The potentials of solar pyrolysis are explored, encompassing discussions on solar concentrator types, reactors, and the distribution of solar and OPB resources throughout Malaysia. The paper then recommends Tawau in Sabah, as an ideal location for OPB solar pyrolysis, due to its solar availability (up to 1873 kWh/m2), potential OPB resources from 19 mills and 241 plantations, and supportive infrastructure. The paper proposes solar-driven pyrolysis as a sustainable solution for Malaysia's OPB management, offers insights for policy initiatives and technological innovations in optimizing OPB and solar energy utilization. • Analyzes oil palm biomass potential for solar pyrolysis in Malaysia. • Explores solar resources in Malaysia for solar-driven pyrolysis. • Examines solar concentrators and reactors for pyrolysis. • Identifies potential city, as the optimal location for solar pyrolysis. • Discusses commercialization challenges of solar-driven pyrolysis. [ABSTRACT FROM AUTHOR]

In the context of the increasing popularity of distributed energy, this paper proposes a home energy management system method considering the working state of flexible load to deal with the problem of mismatch between home energy supply and demand. Specifically, in this paper, the flexible load in the system is studied, and the model of flexible load and its working state are established. On this basis, combined with the real-time electricity price of the grid, the model of home energy management system is constructed to minimize the electricity purchase cost and improve the utilization rate of renewable energy, the genetic algorithm is used to solve it, and the influence of time step, flexible load ratio and whether to use energy storage equipment on the optimization degree of the model are analyzed. The research results show that, while meeting the requirements of human comfort and electricity demand, the daily electricity purchase cost of the system with flexible load scheduling is 22.5% lower than that of the system without flexible load scheduling, and the utilization rate of renewable energy is increased by 16.5%. In terms of model optimization, shortening the prediction time step, increasing the proportion of flexible load and using energy storage equipment can further reduce the electricity purchase cost. The case study confirms the effectiveness of the proposed home energy management system model, which can provide an efficient optimal scheduling scheme for household energy saving. • The optimal scheduling model for home energy management system of rural dwellings with flexible loads is proposed. • Influence of the proportion of flexible load and different time step sizes on the scheduling model are studied. • The operation cost by 26.62% of battery integration strategy based on load scheduling is further reduced. [ABSTRACT FROM AUTHOR]

Environment-friendly, safe and reliable energy supplies are indispensable to society for sustainable development and high life quality where even though social, environmental, political and economic challenges may play a vital role in their provision. Our continuously growing energy demand is driven by extensive growth in economic development and population and places an ever-increasing burden on fossil fuel utilization that represent a substantial percentage of this increasing energy demand but also creates challenges associated with increased greenhouse gas (GHG) emissions and resource depletion. Such challenges make the global transition obligatory from conventional to renewable energy sources. Hydrogen is emerging as a new energy vector outside its typical role and receiving more recognition globally as a potential fuel pathway, as it offers advantages in use cases and unlike synthetic carbon-based fuels can be truly carbon neutral or even negative on a life cycle basis. This review paper provides critical analysis of the state-of-the-art in blue and green hydrogen production methods using conventional and renewable energy sources, utilization of hydrogen, storage, transportation, distribution and key challenges and opportunities in the commercial deployment of such systems. Some of the key promising renewable energy sources to produce hydrogen, such as solar and wind, are intermittent; hydrogen appears to be the best candidate to be employed for multiple purposes blending the roles of fuel energy carrier and energy storage modality. Furthermore, this study offers a comparative assessment of different non-renewable and renewable hydrogen production systems based on system design, cost, global warming potential (GWP), infrastructure and efficiency. Finally the key challenges and opportunities associated with hydrogen production, storage, transportation and distribution and commercial-scale deployment are addressed. • A detailed review on hydrogen production methods and utilization. • Green, blue and purple hydrogen production methods are described thoroughly. • Hydrogen storage and infrastructure, transportation and distribution are also covered in utilization. • Recent advancements, challenges and opportunities are described in detail. • Comparative assessment is conducted on the basis of system design, cost, storage, GWP, infrastructure and efficiencies. [ABSTRACT FROM AUTHOR]

Woody biomass energy makes up a large share of renewable energy consumption in the EU, and the largest share in countries like Denmark. However, little is known about how the public perceive it. This paper presents the results of a questionnaire-based survey of the public in Denmark focusing on attitudes toward woody biomass for energy. The main findings are that, while more people favor than oppose it, a large proportion are undecided about the use of woody biomass. The survey also revealed a lack of knowledge about this energy source. A Best-Worst Scaling methodology revealed that Danes prioritize environmental sustainability concerns – namely biodiversity loss, the hindering of the development of other renewable energy sources and the climate change mitigation potential of woody biomass – over societal and/or economic ones when it comes to the promotion of woody biomass. Finally, it was found that concern about climate change, belief in the mitigation potential of woody biomass, and being younger explained the formation of positive attitudes toward woody biomass. Policy makers aiming to take public concerns into account in discussions about Denmark's energy future should focus more on minimizing the negative environmental impacts associated with woody biomass rather than on its economic benefits. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper proposes the first application of a split-range control technique on a concentrating solar collector to improve an absorption plant production. Solar absorption plants have solar power availability in phase with cooling demand under design conditions. Thus, it is a powerful cooling technology in the context of renewable energy and energy efficiency. These plants need control systems to cope with solar irradiance intermittency, reject irradiation disturbances, manage fossil fuels backup systems and dump closed-loop thermal-hydraulic oscillations. In this work, control techniques are proposed and simulated in an absorption plant in Spain. The plant consists of a concentrating Fresnel solar collector connected to an absorption chiller. The objectives are to operate with 100% renewable solar energy and avoid safety defocus events while reducing temperature oscillations and control actuators effort. Firstly, the current available plant controllers are defined, then two modifications are proposed. The first modification is a split-range controller capable of manipulating both flow and defocus of the Fresnel collector, the second modification is a PI controller to substitute the original chiller on-off controller. The results compare, through validated models, the different control systems and indicate that using both proposed controllers reduces 94% of the sum of actuators effort and 43% of the integral of absolute set-point tracking error compared to the plant's factory pre-set controllers. The suggested controllers increase 66% of energy production and 63% of exergy production. Besides, the split-range technique can be extended to any concentrating solar collector control. [Display omitted] [ABSTRACT FROM AUTHOR]

An important methodological point that has been over-looked by most of the literature is that renewable energy consumption (REC) is not only correlated in time but also in space. The omission of relevant spatial interaction terms in econometric analysis could be a methodological issue of major importance as it could lead to biased and inefficient estimates. This study accounts for spatial interaction effects to investigate the determinants of REC using a balanced panel of 41 countries in sub-Saharan Africa (SSA) over the period 2002 to 2015. The paper computes the Spatial Moran's I value to explore the spatial agglomeration phenomenon. Then, the Spatial Durbin Model (SDM) is applied to investigate the determinants of REC. The result from the Moran's I value indicates positive spatial correlation between REC and the spatial spill-over effect, representing spatial agglomeration. The decomposition of the SDM Model reveals that the direct effect of Gross Domestic Product per capita is negative while the direct effect of quality of governance level is positive. [ABSTRACT FROM AUTHOR]

The paper investigates the role of renewable energy and alternative and nuclear energy in mitigating CO 2 emissions. Trade openness is added to consider its effect on the environment, as it appears to be a crucial factor in interregional cooperation and development. We adopt a sample of nine signatories to the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) from 1971 to 2014. Various time-series econometric methods are utilized including two long-run estimators - fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) - and a Granger-causality test. Several noteworthy findings are achieved from this paper. First , the inverse U-shaped relationship is found in six countries: Australia, Canada, Chile, New Zealand, Peru and Vietnam. The U-shaped relationship is found in Japan and Malaysia whereas no evidence is observed in Mexico. Second , the adoption of either renewable energy or alternative and nuclear energy would mitigate CO 2 emissions and trade openness plays an important role in facilitating this effect. Third , the directions of Granger causality among the variables of interests including consumption of renewable energy; consumption of alternative and nuclear energy, trade openness and CO 2 emissions, do vary across countries and between the short term and the long term. • Inverse U-shaped relationship in Australia, Canada, Chile, New Zealand, Peru, Vietnam. • U-shaped relationship in Japan and Malaysia and no evidence in Mexico. • Consumption of renewable energy, alternative & nuclear energy reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

Although renewable energy has been emphasized to mitigate carbon emissions, energy policies may require rearrangement. This paper aims to suggest the possibility of needs in energy policy rearrangement by revealing if the mitigation impact of the renewable energy supply has been diminished with a case study on Organization for Economic Cooperation and Development (OECD) countries. Adopting the idea of the environmental Kuznets curve hypothesis, the study investigates the nonlinear relationship between the renewable energy supply and carbon emissions. We collected the longest panel data possible for 34 OECD countries from 1971 to 2019. While the cointegrating equation results suggest that renewable energy has contributed to carbon mitigation, nonlinear estimation and quantile regression propose that the marginal mitigation impact from renewable energy might be weakening. 1% increase in renewable energy supply and the share of renewable in energy mix has mitigated carbon emissions by 0.134% and 1.260%, respectively. The empirical results insist that policymakers discover alternatives to decarbonize the energy sector, other than renewable energy expansion. Options to achieve carbon neutrality include heat expansion via unused heat, that is, national energy system innovation towards wasted energy utilization. [ABSTRACT FROM AUTHOR]

• Shape interpolations between four common front shape extrema of the Energy-saving Chinese Solar Greenhouse (ECSG) were studied. • Two kinds of optimal ECSG shapes were identified in this study. • PCA analysis were conducted to determine the optimal greenhouse construction parameters. • The proposed model framework allows the investigation of the effects of different shape variations of solar greenhouses for any arbitrary latitude. Determining the optimal shape for greenhouses that is suitable for cold northern regions is essential for non-seasonal fruit production. In the present study, a structural model was developed for energy-saving Chinese solar greenhouses (ECSG), which combines a greenhouse energy balance model with a detailed shape analysis. All possible greenhouse shape interpolations within four common front shape extrema were systematically analysed to determine an optimal ECSG shape with a maximal energy performance for use during winter. The analysis revealed a direct relationship between the interception of solar radiation in the greenhouse and the height of the ridge. Our results indicated that the flatter the curve of the front cover, the more radiation is intercepted by the ground and north wall of the greenhouse. As a result, compared to the commonly used greenhouse type, two types of optimal ECSG shapes were identified, each attaining an increase of 2°C in the minimum night temperature. The general model framework developed in this study allows the investigation of the effects of different variations in the many small detailed interpolation shapes of ECSGs for any arbitrary latitude which can be used directly to provide guidance for the construction of a new generation of energy-efficient solar greenhouses. Also, with the interpolation method proposed in this paper, large-scale shape statistical analysis now can be performed to help qualified decision-making during the process of greenhouse construction. [ABSTRACT FROM AUTHOR]

As the world's largest energy consuming country, it is important to study the mechanisms of improving renewable energy and energy efficiency to achieve green economic growth in China and globally. Therefore, this study investigates the impact of environmental regulations on green economic growth and renewable energy development in China, respectively. First, this study measures the level of green economic growth in Chinese cities by the Metafrontier-Global-SBM super-efficient data envelopment analysis (DEA) model from the perspective of energy efficiency. And the environmental regulation intensity was measured using an improved fuzzy comprehensive evaluation method. Second, a spatial econometric model based on longitudinal data was constructed to examine the non-linear effects of environmental regulations on green economic growth and its spatial spillover and feedback effects. The results indicated a U-shaped non-linear effect of energy efficiency-related environmental regulation on green economic growth as well as a spatial spillover effect and spatial feedback effect. Finally, the impact of environmental regulation on renewable energy development was investigated. The results show that renewable energy development, an important component of green economic growth, is equally dependent on the implementation of environmental regulation policies and that environmental regulation makes a significant contribution to renewable energy development. The findings of this paper provide a basis for the realization of green economic growth and the formulation of renewable energy policies in China. • Impact of environmental regulation on renewable energy development was investigated. • A spatial econometric model of 286 Chinese cities from 2003 to 2018 was constructed. • Environmental regulation has a significant U-shaped effect on green economic growth. • Non-linear effects include spatial spillover and spatial feedback effects. • Environmental regulation promotes green growth earlier in resource-based cities. [ABSTRACT FROM AUTHOR]

• Dependence on fossil fuel reduces the hazard of private sector investment in renewable energy sector. • The role of fossil fuel dependence decreases in countries with prior investment projects. • Changes in oil price have competing effects on investment hazard. • Regulatory quality and renewable energy policies stimulate private sector investments in developing countries. Given the rapid population growth and subsequent increase in energy demand in developing countries, private sector investment in renewable energy projects is key for sustainable economic development. However, the current energy mix is still dependent on conventional fossil fuels. The paper examines the time duration to private sector investment in renewable energy projects and how the hazard rate is affected by dependence on fossil fuels. Using data on private sector participation in renewable energy projects in 134 developing and middle-income countries for the (1990–2012) period, this paper applies multiple failure time model. The results show significant negative effects of fossil fuel consumption and fuel rent on investment likelihood. Consistent with literature, a set of socio-economic variables, such as renewable energy policy and energy security concerns, play an important role in increasing the likelihood of private sector investment in renewable energy technologies. The findings of the paper resonate with concerns of the international community regarding the effect of fossil fuel dependence on the rate of adoption of renewable energy sources in developing countries. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates asymmetric effects of renewable and nuclear energy on economic growth by extending production function along with labor and capital for Pakistan's economy. Paper utilises non-linear autoregressive distributed lag model with the yearly data of 1990–2016 to extract reliable facts. Results reveal the presence of asymmetric co-integration among variables. Results offer evidence of positive and negative shocks to renewable and nuclear energy variables will have positive impact on economic growth. Further, capital formation contributes positive to economic growth. Addition to this, two more conventional models have been constructed to investigate asymmetric impacts of economic growth, oil prices, oil consumption and CO 2 emissions on nuclear and renewable energy consumption. Results reveal that oil consumption leads to a negative impact on renewable energy consumption while it is neutral for nuclear energy consumption. Oil price was having neutral impact on renewable and nuclear energy consumption. Policy suggestions are given based on empirical results. Highlights • Renewable energy consumption has asymmetric positive affect on economic growth. • Nuclear energy consumption shows a positive and asymmetric linkages with economic growth. • Oil consumption has negative impact on renewable energy consumption. • Oil price shows neutral impact on renewable and nuclear energy consumption. [ABSTRACT FROM AUTHOR]

In this study, the optimization of a multisource hybrid photovoltaic (PV)/Wind/Diesel/Fuel cell (FC) system is performed to meet three realistic loads demand for heavy, medium and small activities observed at Figuil, Cameroon. This paper also examines and compares the techno-economic viability of an off-grid hybrid PV/Wind/Diesel/FC, PV/Diesel/FC and Wind/Diesel/FC systems in terms of net present cost (NPC), cost of energy (COE) and environmental emissions. The effectiveness of different evolutionary algorithms employed in the designing problem of the various hybrid systems is also investigated. The results revealed that, for maximum loss of power supply probability (LPSP) of 5% and minimum renewable energy fraction of 85%, the PV/Wind/Diesel/FC system is economically the best choice for supplying the three types of non-domestic loads demand with corresponding NPC, COE and LPSP values of 159319.4$, 1.087$/kWh and 0.0397 for heavy activity; 150185.8$, 1.753$/kWh and 0.0411 for medium activity; and 144588.0$, 2.384$/kWh and 0.0288 for small activity, respectively. The results also demonstrated that, in terms of pollution emissions minimization, the PV/Wind/Diesel/FC configuration is a preferable option, with an overall yearly CO 2 emissions of 2946.1 kg, 2043.6 kg and 1504.2 kg corresponding to an annual total fuel consumption of 1115.9L, 774.1L and 569.8L for heavy, medium and small activities, respectively. [ABSTRACT FROM AUTHOR]

The operation of solar photovoltaic installations for many years may lead to problems such as reduced energy efficiency and aging of components. Under this framework, replacing certain components in the facility to extend the service life of the power plant is viewed, in some cases, as a feasible strategy. However, despite its enormous strategic interest for the solar PV industry, we find that revamping PV installations has been the focus of very few scientific publications, and even less so when it comes to analyzing real facilities. Thus, this paper performs a techno-economic analysis of three revamping strategies at a real PV power plant located in the south-east of Spain. The strategies consist of substituting, in each case, the PV modules, the inverter, and both components. The simulated results show that the highest production value by installed power is obtained when both the modules and the inverter are replaced. In the same vein, the economic analysis reveals this scenario as the most favorable in terms of profitability. Based on the results obtained, an interesting future line of research would be focused on the extension of the analysis at country level to study the joint impact of numerous revamping actions. • Techno-economic analysis of revamping projects of a real solar PV power plant. • Replacing modules and inverter emerges as the most feasible strategy. • Study's applicability extends to other revamping initiatives and geographical regions. • Economic outcomes allow the most cost-effective alternatives to be determined. • This research can contribute to efficient and sustainable energy planning. [ABSTRACT FROM AUTHOR]

In order to facilitate the carbon emission reduction to mitigate climate change, this paper proposes a coordinated multi-stage planning strategy for the transmission-level integrated electricity-gas-heating system. The strategy coordinates installations of gas-fired generation plants, renewable energy plants, gas wells, power-to-gas plants, transmission lines and pipelines, considering retirements of coal-fired generation plants. It can help facilitate carbon emission reduction of the electricity system as well as the integrated energy system. The objective is to minimize the total present value of the investment and the operation economic cost, with consideration of constraints from each sub-system and carbon emission restriction. In the case studies, the proposed planning strategy is verified to be able to obtain the installation plan of the related facilities. With which the system can reduce the proportion of fossil fuel energy utilization and increase renewable energy utilization. Hence, carbon emission reduction is achieved. In addition, it has demonstrated that integrating the multi-energy systems can help reduce the economic cost in the planning result. • Multi-stage planning strategy of the integrated energy system is proposed. • Energy conversions among different sub-systems are considered. • An aggregated model of district heating system is adopted. • Capability of carbon emission reduction is verified. • Contributions from flexibility of gas and heating systems are demonstrated. [ABSTRACT FROM AUTHOR]

Faced with international climate obligations and domestic pressure, Singapore has recently raised its climate goals significantly. The government had affirmed its intention for carbon emissions to peak before 2030 and for Singapore to attain net zero greenhouse gas emissions by 2050. However, as Singapore transitions to green energy, there remains much uncertainty if this transformation, coupled with rapidly evolving geopolitics, would present vulnerabilities to energy security. Hence, this paper is an attempt to investigate Singapore's possible paths to achieve these goals while enhancing energy security in view of present and future energy plans. Key parameters of energy security in Singapore's context are identified to determine how different policy decisions would influence them. The effects of various current and potential policies can thus be evaluated using a systems thinking and system dynamics approach to propose new energy solutions to improve energy security. System dynamics modelling reveals that new energy supply solutions would have to be considered in Singapore's Energy 2050 Plan while furthering efforts in reducing energy demand. Findings reveal that Singapore should have a target of >80% renewable energy by 2050, pursue a central strategy towards sustainable diversification of its energy sources into hydrogen, electricity imports and solar energy and reduce energy consumption. Accordingly, Singapore's energy security can then be improved in terms of the economic, energy supply chain and environmental dimensions, and towards attaining net-zero emissions. [Display omitted] • Systems approach to Singapore Green Plan 2030 and simulation of policies towards energy security and net zero. • Systems thinking and system dynamics modeling to evaluate key assumptions and energy security parameters. • Model validation, both structural and behavioral, through base model simulations as well as behavioral tests. • Effect of government policies on hydrogen energy, low carbon electricity imports and energy saving on energy security. • Simulations suggest policies for higher renewable energy targets to attain net zero carbon emissions and energy security. [ABSTRACT FROM AUTHOR]

In this paper, a real time implementable load coordination strategy is developed for the optimization of electric demands in a smart home. The strategy minimizes the electricity cost to the home owner, while limiting the disruptions associated with the deferring of flexible power loads. A multi-objective nonlinear mixed integer programming is formulated as a sequential model predictive control, which is then solved using genetic algorithm. The load shifting benefits obtained by deploying an advanced coordination strategy are compared against a baseline controller for various home characteristics, such as location, size and equipment. The simulation study shows that the deployment of the smart home energy management strategy achieves approximately 5% reduction in grid cost compared to a baseline strategy. This is achieved by deferring approximately 50% of the flexible loads, which is possible due to the use of the stationary energy storage. • Real-time load coordination strategy for optimizing electrical loads in smart homes. • Inclusion of renewable energy sources and stationary batteries in the coordination. • Definition of generalizable metrics for the evaluation of load shifting strategy. • Improvements in improved energy efficiency and reduced electricity costs. • Comprehensive analysis that considers diverse home characteristics such as location. [ABSTRACT FROM AUTHOR]

The African continent is endowed with massive energy resources such as hydropower, solar, wind, natural gas, wave energy, and many more, yet it is the continent with the least energy supply in the world thereby resulting in a lack of sufficient energy to meet its growing energy demand. Though the continent holds 100 GW of wind capabilities, the current installed capacity as at 2018 was 5.7 GW with countries in northern Africa as well as South Africa capturing over 90% of the wind energy share on the continent. Therefore, this paper reviews the wind energy industry in Africa by identifying the current installed and potential capacity of wind energy on the continent. The challenges faced by the wind energy industry such as policy, competition, technical and economic are also reviewed. Transitions, technological innovation systems, and strategic niche management theoretical sustainability transition framework as well as proposed pathways to overcome these prevailing challenges hindering the full exploration of the wind energy sector in Africa are also highlighted in order to uplift the continent's socio-economic status. Basically, this can be achieved through the adoption of strong 'political-will' by African national governments to drive wind energy development. There is also the need for institutional frameworks to ensure the practical adoption of new wind energy technologies. Furthermore, the major benefits Africa stands to gain from investment in wind energy are enumerated by comparing with the benefits realized by other countries' economies as a result of investing in the wind energy industry. For instance, cheap electricity, job creation, industrial growth, and eco-friendly energy source. • Reviewing wind energy industry in Africa and existing challenges. • The challenges faced by African's wind energy industry can be categorized under policy, competition, technical and economic. • Framework for transiting Africa's wind energy industry from small-scale production to large-scale commercial industry.. [ABSTRACT FROM AUTHOR]

This paper examines renewable and technological prices' asymmetric multifractality and efficiency in international and Chinese marketplaces. The asymmetric multifractal detrended fluctuation analytics (A-MFDFA), multifractal detrended fluctuation analytics (MFDFA), and fractal dimension techniques are employed for multifractality and herding behavior. In addition, market deficiency measures (MDM) and hurst exponents are used to construct the inefficiency index (MLM- Magnitude of long-memory) during and before Covid-19. The empirical outcomes supported the existence of asymmetric multifractality across all renewable and technological marketplaces. This multifractality has been observed in up-and-down trends. Moreover, during the COVID-19 outbreak, inefficiency in CELS and SPGlobal's green energy prices increased, which is more apparent in the descending trends. Fractal dimension outcomes suggest a herding behavior in these markets during pandemic. The SPTSX green energy pricing statistics demonstrate that its upward multifractality is larger than the downward in both phases, signifying the strong efficiency position in the market. The SPIC-SH green energy pricing displayed considerable asymmetric multifractality, higher levels of efficiency, and even low levels of market uncertainty during COVID-19. The findings imply that all financial market players should prioritize various green energy investments depending on its asymmetric efficiency and predictability. It will help in their decision-making and reduces herding behavior in the market. • Asymmetric multifractal behavior is tested in global renewable and technological prices. • A-MFDFA and MFDFA and fractal dimension are used to analyze efficiency, scaling and herding behavior during and before COVID. • CELS and SPGlobal's green energy prices showed herding behavior before and inefficacy during COVID. • Green Technology and Chinese green energy prices were stable during COVID. • All green and technological prices were more stable before COVID-19. [ABSTRACT FROM AUTHOR]

Green financing is essential because it guarantees that initiatives that seek to reduce the world's reliance on fossil fuels receive the necessary funding to be successful. Green financial metrics can be simultaneously made possible by specialized technological innovation and natural resource rent, thereby encouraging the adoption of sustainable energy. In this paper, we investigate the mediating mechanisms underlying the relationship between green financial indicators and renewable energy consumption RNEC and we contribute to the ongoing discussion surrounding this relationship. Our observational example is derived from data collected for 66 countries between 2004 and 2019 using a panel threshold regression model defined with the difference generalized method of moments (GMM). We find that green funding initiatives have accelerated the adoption of renewable energy sources by encouraging increases in the proportion of renewable energy in the fuel supply. Multiple analyses of reliability corroborate the existence of this link. Green funding has been shown to have an encouraging effect on the transition to renewable energy, and our findings indicate that technological advancement and natural resource leasing serve to mitigate this effect. To assist policymakers in reducing the world's reliance on polluting energy, our study demonstrates how green financial markets can be established through improved technological innovation and natural resource management. [ABSTRACT FROM AUTHOR]

• Investigated strategies that can deliver NZE performance for high-rise residential buildings in Australia. • It was challenging for tropical, subtropical and cold temperate climates to meet the NZE targets. • Design and optimisation of the envelope was effective in overcoming the challenges imposed by the more demanding climates. • The impacts of shading from neighbouring buildings presented the largest obstacle to energy production through the façade. • Study demonstrated a need to include density factors in the design consideration for NZE high-rise residential designs. Net-Zero Energy (NZE) buildings are gaining popularity globally as a solution to reduce operational energy usage and limit greenhouse gas emissions in the building industry. Their deployment is occurring rapidly as many countries are planning to make it mandatory for new developments. Despite the advancements in research in the various aspects of NZE, significant barriers do exist to its successful adoption and implementation, particularly with respect to high-rise residential buildings which are becoming a major portion of the housing supply in Australia. One of the challenges attributed to the achievement of NZEB performance is the uncertainty involved in selecting appropriate solution strategies that could deliver quality performances. This paper investigated strategies that can deliver NZE performance for high-rise residential buildings in Australia. A calibrated model of 26 storey high-rise apartment building with 396 units was prepared for detailed analysis of NZE strategies using building simulation. The impact of various interventions was evaluated across cities in five climate zones in Australia and a guideline for solution sets that can deliver the goal for each climate zone is presented. The findings show that NZE performance for high-rise residential buildings can be realised in Australia, albeit with some limitations. While the tropical, subtropical and cold temperate climates appear to be more challenging, proper design and optimisation of the envelope proved to be effective in overcoming the challenges imposed by the more demanding climates. The impacts of shading from neighbouring buildings and objects presented the largest impediment to energy production through the façade. [ABSTRACT FROM AUTHOR]

Energy extraction from renewable sources like hydrokinetic energy from the flowing water of rivers and canals is one of the affordable and clean energy generation technique. The current work is carried out towards performance enhancement of the Darrieus hydrokinetic turbine for open water channel utilization application. The investigation has been done using the flat and concave shape of blocking plate. Both blocking plates have been analyzed for different sizes as well as location at the upstream side of the turbine. The obtained results are reported after considering appropriate velocity correction. The blocking plates with projected width of 76 mm, 89 mm, 101 mm, 127 mm, 152 mm, and 203 mm are selected for the investigation. It is observed that 101 mm (Width Ratio , WR =0.36) with concave blocking plate provides maximum C p of 0.245 at 0.99 TSR. Also, the optimum region is found between 0.143 and 0.286 Distance Ratio (DR) from the top corner of the acrylic plate. The concave blocking plate enhance the performance more compared to flat blocking plate. The conclusion is made that, the performance with flat blocking plate with optimized width and location improve the power coefficient by 10.92% and that of concave blocking plate by 18.45%. • Energy extraction using Darrieus hydrokinetic turbine is one of the affordable and clean energy generation techniques. • The performance of the Darrieus water turbine has been compared with a bare rotor and with using two different types of blocking plates. • The concave and flat blocking plates have been experimentally analyzed, and its effect has been explored in the paper. • The different sizes of concave and flat blocking plates were placed at the upstream side of the Darrieus turbine to enhance the performance. • The paper also includes the optimum region of the optimized shape concave and flat blocking plates placed at the upstream location of the rotor. [ABSTRACT FROM AUTHOR]