Multi-Time Scale Coordinated Optimization of Energy Systems Under Flexible Load Response
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Since the development of society, people's demand for and use of energy have become increasingly diverse rather than remaining monotonous. Flexible load response serves as the core medium for integrating various energy sources. However, the operational performance of units within the energy system has not been ideal, and operating costs remain difficult to control. To address these challenges, this study investigates multi-time scale collaborative optimization of energy systems based on flexible load response, utilizing a combination of qualitative and quantitative methods. The research encompasses optimization architecture, optimization models, computational case studies, and validation. The results indicate that, during load response experiments, implementing an intra-day coordinated plan—specifically by further reducing thermal and electrical loads during peak hours—can significantly decrease the peak-valley difference. Additionally, in the cost comparison analysis, the operating cost was reduced by 1.47%, thereby addressing the shortcomings of traditional energy system coordination and optimization. Overall, the approach offers notable improvements both in economic performance and in system coordination and optimization, demonstrating considerable foresight.
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