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This study analyzes the impact of global geopolitical changes on new/renewable energy (NRE) policies and their roles in enhancing national energy security, elevating international stature, and influencing the global energy market. Using game theory, it reveals how NRE policies promote technological innovation, diversify energy supply, and strengthen international collaboration, thus advancing the global energy system towards a low-carbon transition and improving international energy governance. NRE policies significantly enhance national energy security by reducing dependency on single energy sources, facilitate the global shift to low-carbon energy, and intensify international cooperation. The effectiveness of these policies in driving energy transformation is notable, and they are expected to remain crucial for global energy security and sustainable transition. Recommendations include strengthening the stability and security of energy supply chains through enhanced oversight, increasing investment in R&D and innovation to reduce costs, fostering international cooperation for better policy coordination, and implementing diversified energy policies to encourage the adoption of NRE. These measures will address challenges from global geopolitical dynamics and drive the global energy system towards sustainability and efficiency. [ABSTRACT FROM AUTHOR]

The carbon emissions of the power industry account for over 50% of China's total carbon emissions, so achieving carbon peak and carbon neutrality in the power sector is crucial. This study aims to simulate the impacts of three energy policies—carbon constraints, the development of a high proportion of renewable energy, and carbon trading—on China's energy transition, economic development, and the power sector's energy mix. Through the construction of a dynamic computable general equilibrium (CGE) model for China and its integration with the SWITCH-China electricity model, the impact of diverse energy policies on China's energy transition, economic progress, and the power mix within the electricity industry has been simulated. The integration of the SWITCH-China model can address the limitations of the CGE model in providing a detailed understanding of the specific intricacies of the electricity sector. The results indicate that increasing the stringency of carbon restrictions compels a reduction in fossil energy use, controlling the output of coal-fired power units, and thereby reducing carbon emissions. The development of a high proportion of renewable energy enhances the cleanliness of the power sector's generation structure, further promoting the national energy transition. Implementing a carbon trading policy, where the entire industry shares the burden of carbon reduction costs, can effectively mitigate the economic losses of the power sector. Finally, the policies to further enhance the implementation of carbon trading policies, strengthen effective governmental regulation, and escalate the deployment of renewable energy sources are recommended. [ABSTRACT FROM AUTHOR]

As the integration of renewable energy expands, effective energy system management becomes increasingly crucial. Distributed renewable generation microgrids offer green energy and resilience. Combining them with energy storage and a suitable energy management system (EMS) is essential due to the variability in renewable energy generation. Reinforcement learning (RL)-based EMSs have shown promising results in handling these complexities. However, concerns about policy robustness arise with the growing number of grid intermittent disruptions or disconnections from the main utility. This study investigates the resilience of RL-based EMSs to unforeseen grid disconnections when trained in grid-connected scenarios. Specifically, we evaluate the resilience of policies derived from advantage actor–critic (A2C) and proximal policy optimization (PPO) networks trained in both grid-connected and uncertain grid-connectivity scenarios. Stochastic models, incorporating solar energy and load uncertainties and utilizing real-world data, are employed in the simulation. Our findings indicate that grid-trained PPO and A2C excel in cost coverage, with PPO performing better. However, in isolated or uncertain connectivity scenarios, the demand coverage performance hierarchy shifts. The disruption-trained A2C model achieves the best demand coverage when islanded, whereas the grid-connected A2C network performs best in an uncertain grid connectivity scenario. This study enhances the understanding of the resilience of RL-based solutions using varied training methods and provides an analysis of the EMS policies generated. [ABSTRACT FROM AUTHOR]

Energy transformation in Poland, including the need to accelerate the shift away from hard coal and lignite in the power system, has been taking place in the face of the energy crisis. Ambitious climate and economic goals force the development of renewable energy sources, but they require legislative changes for the benefit of socially vulnerable consumers. This is important from the point of view of counteracting energy poverty. Energy transformation is not only a change in the fuel used, but most of all, the path and basis of low-carbon development that changes many socio-economic systems. The aim of this study is to link the development and environmental challenges in the studied subject matter with social challenges. The analyses show that it is necessary to strengthen the use of local energy potential and resources, and to activate local communities. The construction of nuclear power plants is also crucial. The results of the presented theoretical and empirical studies can be the basis for a revision of the energy policy in Poland in the area of the social dimension of the energy sector. [ABSTRACT FROM AUTHOR]