Mitigating energy uncertainty in emerging economies: the role of renewable energy generation and governance

Geopolitical risks and mineral-driven renewable energy generation in China: A decomposed analysis

The energy sector of Argentina is predominantly reliant on fossil fuels. Consequently, such fossil fuel dependency within the nation's power sector, in particular, has aggravated the environmental qualityin Argentina by amplifying the nation'senergy production-based carbon emissionlevels. However, keeping into consideration the international commitments pledged byArgentinaunder the Paris Accord and the Sustainable Development Goals agenda, it is pertinent for this South American countryto curb its energy production-based emissionofgreenhouse gases, especially carbon dioxide. Against this milieu, this study examines the impacts of renewable electricity generation, economic globalization, economic growth, and urbanization on carbon dioxide emissions generated from the production of electricity and heat in the context ofArgentina. Using annual frequency data from 1971 to 2016, recent econometric methods are applied to control for multiple structural breaks in the data. The major findings from the ecnometric analyses affirmed long-run associations between renewable electricity generation, economic globalization, economic growth, urbanization, and energy production-based carbon dioxide emissions in Argentina. Besides, enhancing renewable electricity output shares is found to curb these emissions while economic globalization and urbanization are witnessed to boost them. Moreover, renewable electricity generation and economic globalization are found to jointly reduce the energy production-related carbon dioxideemissions in Argentina. The results also validate the authenticity of the Environmental Kuznets Curve (EKC)hypothesis. Finally, the causality analysis reveals evidence of unidirectional causalities running from renewable electricity generation, economic globalization, economic growth, and urbanization to energy production-related carbon dioxide emissions in Argentina. In line with these findings, this study recommends several viable policies which can be implemented to help Argentina control the growth of its energy production-based carbon dioxideemissions.

Optimal renewable energy generation – Approaches for managing ageing assets mechanisms

Purpose The purpose of this paper is to examine the impact of renewable energy on the power supply chain and to study whether the renewable generator or the power grid that purchases power from the power spot market is better when the actual generation of renewable energy is insufficient. The authors want to compare and analyze the different power supply chain operation modes and discuss the optimal mode selection for renewable energy generator and power grid in different situations. Design/methodology/approach This paper studies the grid-led price competition game in the power supply chain, in which the power grid as a leader decides the price of transmission and distribution, and generators determine the power grid price. The renewable energy power generator and the traditional energy power generator conduct a price competition game; on the other hand, the power grid and power generators conduct Stackelberg games. The authors analyze the power supply of single power generator and two power generators, respectively, and research on the situation that the renewable energy cannot be fully recharged when the actual power generation is insufficient. Findings The study finds that both renewable and traditional power grid prices decline as price sensitivity coefficient of demand and installed capacity of renewable energy generators increase. Power grid premium decreases as the price sensitivity coefficient of demand increases, but rises as the installed capacity of renewable energy generator increases. When there is a shortage of power, if the installed capacity of renewable energy is relatively small and price sensitivity coefficient of demand is relatively large, the grid purchases the power from power spot market and shares cost with renewable energy generators, leading to higher expected profits of the renewable energy generators. On the contrary, the renewable energy generators prefer to make up power shortage themselves. For the power grid, purchasing the power by the renewable energy generators when there is a power shortage can bring more utility to the power grid when the installed capacity of renewable energy is lower and the demand price sensitivity coefficient is higher. When the installed capacity of renewable energy is high and the price sensitivity coefficient of demand is moderate, or the installed capacity of renewable energy is moderate and the demand price sensitivity coefficient is high, a generator that simultaneously possesses two kinds of energy source will bring more utility to the power grid. If the installed capacity of renewable energy and the demand price sensitivity coefficient both are small or the installed capacity of renewable energy and the price sensitivity coefficient of demand both are large, the power grid prefers to purchase the power by itself when there is a power shortage. Practical implications The goal of our paper analysis is to explore the implications of the theoretical model and address the series of research questions regarding the impact of the renewable energy on the power supply chain. The results of this study have key implications for reality. This paper sheds light on the power supply chain operation mode selection, which can potentially be used for the renewable energy generators to choose their operating mode and can also help traditional energy generators and power grid enterprises maximize their utility. This paper also has some references for the government to formulate the corresponding renewable energy development policy. Originality/value This paper studies the power operation mode under the uncertainty of supply and demand, and compares the advantages and disadvantages of renewable energy generator that makes up the shortage or the power grid purchases the power from power spot market then shares cost with the renewable energy generator. This paper analyzes the power grid-led coordination problem in a power supply chain, compares and analyzes the price competition game model of single power generator and dual power generators, and compares the different risk preferences of power grid.

This paper examines the relationship between renewable energy (RE) generation, economic factors, infrastructure, and governance quality in ASEAN countries. Based on the Fixed Effects regression model on panel data spanning the years 2002–2021, results demonstrate that domestic capital investment, foreign direct investment, governance effectiveness, and crude oil price exhibit an inverse yet significant relationship with RE generation. An increase in those factors will lead to a decline in RE generation. Meanwhile, economic growth and infrastructure have a positive relationship, which implies that these factors act as stimulants for RE generation in the region. Hence, it is advisable to prioritise policies that foster economic growth, including offering tax breaks specifically for RE projects. Additionally, it’s crucial to streamline governance processes to facilitate infrastructure conducive to RE generation, along with investing in RE infrastructure. This could be achieved by establishing one-stop centres for consolidating permitting processes, which would streamline the often-bureaucratic process. However, given the extensive time period covered, future research should examine the short-term relationship between the variables to address any potential temporal trends between the factors and RE generation.

The Factor Proportions Model posits that international trade is contingent upon the relative abundance of factors of production, namely natural resources, capital, and labor. Countries endowed with mineral resources are inclined to export them to countries with higher demand but lower supply. However, geopolitical events disrupt the smooth transition of mineral-consuming economies towards sustainable renewable energy production. This study aims to investigate the interplay between Russian mineral exports and renewable energy generation, taking into account geopolitical risks, within both the global and Chinese contexts. The study covers monthly data from January 2011 to December 2021. Utilizing the cross-quantilogram approach, this study reveals a positive spillover effect of Russian mineral exports on global and Chinese renewable electricity production, across various time frames, including monthly, quarterly, bi-annual, and annual memories. Additionally, labor force's contribution plays a pivotal role in facilitating renewable energy production for both the global and Chinese contexts. Notably, externality factor, particularly geopolitical risks, exert a detrimental spillover effect on renewable energy generation for both the globe and China, although China's geopolitical risk events appear to be beneficial for its own renewable energy production in bullish and bearish states, across all memories. Russian geopolitical risks evince heterogeneous spillover effects on global renewable energy generation. To bolster the robustness of the findings obtained from the CQ approach, this study employs the partial cross-quantilogram (PCQ) approach. This research recommends the imperative of ensuring a secure supply of critical minerals and expediting the global energy revolution, while effectively mitigating geopolitical hazards, with the overarching goal of achieving a trajectory towards net-zero emissions.

This study examines the long-run and short-run of causal nexus between renewable energy generation, CO2 emissions, and economic growth in selected Commonwealth of Independent States (CIS), namely Azerbaijan, Russian Federation, Belarus, Kazakhstan, and Uzbekistan over the period from 2002M01 to 2020M12. The study uses the nonlinear autoregressive distributed lag (NARDL) model to examine the long-run and short-run asymmetric effects between selected variables under concern. The results of empirical model estimation suggested that renewable energy generation has a significant long-run positive effect on CO2 emissions and economic growth in the economies under study, except Kazakhstan. Indeed, renewable energy has an insignificant negative long-run effect on the economic growth in Kazakhstan. Our empirical results summarized that the short-run coefficients of renewable energy generation have a significant steadily positive effect on carbon emission and economic growth in all selected countries under study. Finally, results of the GIRF analysis provided that the innovation shocks оf renewable energy generation have a positive steady-state impact оn CO2 emissions in the economies of CIS countries. For the policy implication, energy policy must be designed with the development of the economy, the development of the environment, and the use of renewable energy sources in the countries in mind. The promotion of renewable energy sources benefits not only the environment but also the economic conditions of the countries. Thus, economic growth is essential to generate the necessary resources for the research and development of renewable energy technologies and related infrastructure.

ABSTRACTThis study explores how digitalization, through resident and non‐resident innovation initiatives, along with government effectiveness, affects the transition to renewable energy generation in five Advanced (Australia, Hong Kong, Japan, New Zealand and Singapore) and seven Emerging (China, India, Indonesia, Malaysia, Philippines, Thailand and Vietnam) Asian economies. The research uses annual data from 1985 to 2022 and applies several econometric methods to analyse the impact of these factors on renewable energy generation in a panel setup while also considering economic growth and human capital as key control variables. The findings reveal that residential innovation negatively impacts renewable energy generation in Advanced Asia but has a positive effect in Emerging Asia. Additionally, government effectiveness and non‐residential innovation hinder renewable energy generation in Emerging Asia while contributing positively in Advanced Asia. Economic growth and human capital show a positive association with renewable energy generation in both Advanced and Emerging Asian economies. These findings are robust to an alternative method used. Besides, additional robust results further indicate that artificial intelligence patents used as an alternative measure of digitalization hinder renewable energy generation in Emerging Asia and promote it in Advanced Asia. These findings provide valuable guidance for policymakers and stakeholders, highlighting the need for tailored strategies to drive sustainable energy transition in different economic contexts.

Price-based demand response (DR) can aid power grid management, but an uncoordinated response may lead to peak rebounds during low-price periods. This article proposes a community energy management system based on multiagent reinforcement learning. The scheme consists of a community aggregator that optimizes the total community electricity cost for multiple residential users. A home requires energy management for home appliances, electric vehicles, energy storage systems, and renewable energy generation. The appliance scheduling problem is decomposed into smaller sequential decision problems that are easier to solve. Renewable generation is predicted and used to mitigate the influence of energy generation uncertainty. As indicated in numerical analyses, the proposed approach can handle the uncertainty in renewable energy and leads to more economical energy usage relative to existing energy management methods. The method outperforms conventional algorithms, such as centralized mixed-integer nonlinear programming and genetic algorithm-based optimization, in terms of mitigating peak rebounds and addressing the uncertainty of renewable energy generation.

The current examination aims to explore the critical relationship of energy, in the form of electricity with economic growth of Indonesia. Contrary to traditional approach of assessing the impact of energy consumption, the present study analyzes the association from production point of view by assessing the impact of electricity production on economic development. In doing so, the current study has adopted the refined methodology of Auto-Regressive Distributed Lags (ARDL) bound testing approach to examine the dynamic relationship among renewable electricity generation, non-renewable electricity generation and economic growth with amplified understanding of the critical association to support the course of economic planning and policy making. The results of ARDL bound testing approach confirm that renewable electricity generation, non-renewable electricity generation and carbon dioxide emission are solid determinants of economic development in Indonesia. Moreover, the results avow that renewable electricity and non-renewable electricity generation have a useful and beneficial outcome on economic development in Indonesia

This study examines how renewable and non-renewable energy generation interacts with both to affect the ecological footprint in China during 1990-2019 by using FMOLS, DOLS, and CCR estimation techniques and ARDL simulation models to assess the impact of industrialization and urbanization on environmental sustainability based on the environmental Kuznets curve hypothesis model framework. Firstly, the findings verify the applicability and validity of the EKC hypothesis in China. Secondly, renewable energy generation, industrialization, and urbanization facilitate the reduction of ecological footprint and the improvement of environmental quality in the long run, while non-renewable energy generation increases the ecological footprint and leads to the intensification of ecological pollution. However, the short-term estimates give evidence that industrialization, urbanization, and renewable and non-renewable energy generation can all increase the ecological footprint, which is not conducive to ecological sustainability. Thus, from the perspective of ecological sustainability in China, our findings are important in that they provide clear directions for ecological policy formulation, and we also provide some targeted policy recommendations for them to promote sustainable development as a goal.

This paper explores the strategic behavior of power generators under green certificate trading policies, considering both renewable and conventional energy generators. Using game theory, we construct a Nash equilibrium model that incorporates the unit price of green certificates, the required quantity of certificates, and the cap on the quantity. By applying the Karush-Kuhn-Tucker conditions, we reform this Nash equilibrium problem as a mixed complementarity system, which can be solved by MATLAB software. Furthermore, we conduct sensitivity analysis and numerical tests on a number of important parameters. The results reveal that, under certain conditions, the unit price of green certificates does not affect the number obtained by renewable energy generators or purchased by conventional energy generators. However, as the required number of certificates for conventional energy generators increases, both the quantity of certificates that renewable generators obtained and conventional generators purchased increase proportionally. Additionally, the outcomes of limiting the quantity of green certificates awarded to renewable energy generators align with government regulations on the purchase requirements for conventional energy generators. This research provides new insights for power generators in ensuring financial viability and optimizing operations under green certificate trading policies. By enhancing carbon emission reduction capacity, these findings may contribute to the effective management of the electrical supply chain.

Environmental innovation is pivotal in tackling climate change by offering diverse and practical solutions to reduce carbon footprints, promote resource conservation, and enhance ecological sustainability. As anthropogenic activities continue to accelerate global environmental degradation, innovative solutions are imperative for mitigating the impacts of climate change and fostering sustainability. However, the effectiveness of these innovations is threatened by global uncertainties and rising income inequalities. Uncertainties in geopolitical landscape and economic disparities may impede the development and widespread adoption of eco-friendly technologies and practices. Given the above background, this study empirically investigates the influences of environmental innovation, world uncertainty and income inequality on renewable energy generation for a balanced panel of 58 countries between 1990 and 2020. The estimated models also control for the effects of globalisation and economic growth. After diagnosing for necessary panel diagnostic tests including cross-sectional dependence, heterogeneity, and panel unit-root, the Westerlund cointegration test confirms a significant long-run relationship between the variables of the study. Using panel Augmented Mean Group (AMG) estimation, the results reveal that while environmental innovation continues to promote the renewable energy generation, global uncertainty and income inequality hamper it. More importantly, the moderating effects of world uncertainty and income inequality reduce the favourable impact of environmental innovation on renewable energy generation. Besides, economic growth and globalisation continue to play critical roles in speeding up the quest for renewable energy. The PCSE estimation technique confirms the significance of these baseline findings. Potential policy implications are also discussed.

Purpose This study aims to explore the short- and long-run asymmetric link between carbon emission (CE), renewable energy generation (REG), renewable energy capacity (REC), renewable energy investment (REI) and energy demand (ED) to analyze the impact of positive and negative asymmetric shocks of carbon emissions. Design/methodology/approach The nonlinear autoregressive distributed lag (NARDL) model was used to capture the asymmetric effects of the independent variables REG, REC, REI and ED on the dependent variable CE from 1990 to 2024. Findings The findings suggest that all independent variables are associated with the CE in the long run. This relationship confirms that changes in REG, REC, REI and ED significantly impact the CE. The results indicate that positive shocks in renewable energy generation have a stronger impact on emission reduction than negative shocks have on increasing emissions. The short-run asymmetric value of REG is 1.371, which is positive and significant at a 1% level, indicating that changes in REG do not have a stagnant effect on CE. Research limitations/implications Firstly, the analysis focuses on aggregate renewable energy generation and does not differentiate between different types of renewables (e.g. solar, wind, hydro). Future studies could explore the individual effects of different renewable energy sources on emissions and additional variables such as energy prices and government subsidies for the clean energy investment. Practical implications The study has several policy and practical implications. First, policymakers should prioritize expanding renewable energy infrastructure, as the impact of increasing renewable energy generation is more pronounced in reducing emissions than the adverse effects of its reduction. Governments should design policies that encourage sustained investment in renewable energy to ensure long-term emission reductions. Originality/value The annual data on CE, REC, REG, REI and ED from the International Energy Agency and International Renewable Energy Agency for the period of 1990–2024 were used to incorporate carbon emissions during the Paris Agreement and the COVID-19 pandemic.

This study aims to analyse the dynamic relationship between renewable electricity generation and its determinants in Malaysia from 1980 to 2016. F-Bound test and VECM are applied. A dynamic long-run relationship exists among the variables use. Long-run elasticity of labour and non-renewable electricity generation on renewable electricity generation is positive elastic and negative elastic, respectively. The short-run elasticity of capital, GDP and financial development on renewable electricity generation is negative elastic, positive elastic and negative inelastic respectively. Also, long-run bidirectional causality between FD and renewable electricity generation, unidirectional causality running from capital, labour, non-renewable electricity generation, and GDP to renewable electricity generation is discovered. However, short-run unidirectional causality from capital and labour to renewable electricity generation and renewable electricity generation to FD is found. Accordingly, these findings highlight important messages to policymakers in the process of sustainable energy through the determinants influence the renewable electricity generation in Malaysia.