Multidimensional Assessment of Resilience in Integrated Energy Systems
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This research agenda outlines three interrelated studies aimed at holistically assessing the development of resilience-oriented integrated energy systems within the context of sustainable development initiatives, accounting for uncertainties in both planning and operations. Through the application of multi-dimensional methodologies, these studies examine and provide valuable insights to key stakeholders, including system operators and policymakers. Although each study addresses different research questions, they collectively contribute to the overarching objective of improving the resilience of integrated energy systems. First, to what extent do low-carbon energy policies impact the resilience enhancement of integrated energy systems, particularly in the form of networked microgrids? To address this issue, this study constructs resilience-oriented networked microgrid systems and develops a two-stage stochastic programming model to optimize system operations under power outage scenarios. A model comparison method is employed to analyze the results with and without the context of clean energy policies. The findings validate the contributions of integrated systems to resilience enhancement but reveal that low-carbon emissions policies may financially inhibit resilience planning by increasing costs for system operators. Nonetheless, an emissions abatement threshold can still be achieved with the constructed integrated network, allowing for dual benefits: maximizing emissions abatement and minimizing the emissions tax burden. Second, how does system configuration influence decision-making regarding the optimal capacity of energy storage systems in offshore wind farms? To answer this question, a sequential "planning + operational" modeling approach is adopted, which includes the agglomerative hierarchical clustering method, an optimal offshore wind farm network configuration algorithm, a stochastic system failure scenario generation method, and an optimization model for determining optimal energy storage capacity. The modeling results indicate that different offshore wind farm network configurations influence decisions regarding the capacity of the energy storage system. However, an optimal capacity can still be determined by analyzing capacity profiles under varying levels of wind turbine clustering. This study highlights the potential of energy storage systems in enhancing the resilience of independent renewable-based generation systems. It aims to provide guidance for system planners in developing economically feasible and resilient clean energy systems. Third, in the context of expanding clean energy generation capacity, how does electricity market operation affect the planning of resilient energy systems? This study examines the impact of renewable-based generation capacity expansion on post-disaster resilience performance and system operators' economic decisions regarding adjustments to electricity market operations, as prosumers' engagement in system operations increases. A simulation-optimization model-coupling approach is adopted to accurately capture post-disaster system performance and seamlessly link technical performance to cost considerations incurred during the degraded system operation period. By comparing operational costs under different renewable capacity expansion scenarios, the optimal electricity market operation mode can be determined. Furthermore, a novel multi-dimensional measurement metric is developed to evaluate system resilience performance by simultaneously incorporating both technical and non-technical factors within an integrated energy system. This study contributes to guiding system operators and policymakers in making reasonable and mutually beneficial decisions during the ongoing transition to sustainable energy systems.
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