Robust Optimization of Integrated Energy Systems Considering Demand Response and Photovoltaic Uncertainty

doi:10.11930/j.issn.1004-9649.201912126

Abstract

Abstract: Due to the photovoltaic integration and the electrical demand response, the operation uncertainty of energy system and the complexity of optimal dispatch of integrated energy system have been increased significantly. The integrated energy system based on multi-source information fusion can collect and process massive operation data in real time, effectively supporting the integrated energy system to achieve efficient and economic operation of the terminal energy supply system. On the basis of introducing an integrated energy system based on multi-source information fusion, a demand response model of the power load is constructed to describe the demand response characteristics of the shiftable load. Focusing on the uncertainty of photovoltaic output, the Latin hypercube sampling and K-means scenario reduction technology are used to generate a typical scenario set, in order to determine the uncertainty range of photovoltaic output. A typical equipment mathematical model of the integrated energy system is established. Considering the demand response of the power load, a robust optimization objective function of the economic operation of the integrated energy system is constructed and the robust optimization algorithm is used to solve the problem. The case simulation results show that while improving the system operation safety, the robust optimization increases the system operation cost. After considering the demand response, the operation economy of the regional integrated energy system is improved. The more users participate in demand response, the more obvious the economic improvement will be.

Key words: integrated energy, multi-source information fusion, uncertainty, robust optimization, demand response, multiple energy storage

ZHAI Jingjing, WU Xiaobei, FU Zhixin, ZHU Shaojie, LIU Haoming. Robust Optimization of Integrated Energy Systems Considering Demand Response and Photovoltaic Uncertainty[J]. Electric Power, 2020, 53(8): 9-18.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.201912126

https://www.electricpower.com.cn/EN/Y2020/V53/I8/9

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