Optimal configuration of multi energy flow system of electric heating and cooling air considering source load uncertainty

Jiawei Xing; Shumin Sun; Peng Yu; Yan Cheng; Yong Li; Shibai Wang; Yuejiao Wang; Sun Li; Di Wang; Qian Ai

doi:10.1117/12.2679572

18 July 2023 Optimal configuration of multi energy flow system of electric heating and cooling air considering source load uncertainty

Jiawei Xing, Shumin Sun, Peng Yu, Yan Cheng, Yong Li, Shibai Wang, Yuejiao Wang, Sun Li, Di Wang, Qian Ai

Author Affiliations +

Proceedings Volume 12722, Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023); 127220W (2023) https://doi.org/10.1117/12.2679572
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023), 2023, Hangzhou, China

Abstract

Multi energy flow coupling, such as electric heating and cooling, is an important feature of integrated energy system. Aiming at the uncertainty of source load caused by the deviation of wind and solar output prediction and load growth prediction in the optimal configuration of multi energy flow system, an optimal configuration method of electric heating and cooling multi energy flow system considering the uncertainty of source load is proposed. Firstly, the physical mechanism and characteristics of the key distributed energy equipment and energy supply network in the multi flow energy supply network of the energy hub are analyzed; The information gap decision theory is used to deal with the prediction deviation caused by the increase of electric heating and cooling air load in the model, and the conditional risk value theory is used to adjust the modeling scheme to assess the risk loss caused by the wind and solar power output prediction deviation. The example analysis shows the optimal allocation results of the deterministic model and the model taking into account uncertainty. The comparison with other optimal allocation methods verifies the effectiveness and superiority of the method in this paper. At the same time, it analyzes the impact of the changes in the avoidance coefficient and risk coefficient in the model on the model results and investment strategies, which proves that the model has the ability to quantify and evaluate the output uncertainty on both sides of the source load.

Citation Download Citation

Jiawei Xing, Shumin Sun, Peng Yu, Yan Cheng, Yong Li, Shibai Wang, Yuejiao Wang, Sun Li, Di Wang, and Qian Ai "Optimal configuration of multi energy flow system of electric heating and cooling air considering source load uncertainty", Proc. SPIE 12722, Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023), 127220W (18 July 2023); https://doi.org/10.1117/12.2679572

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KEYWORDS

Solar energy

Wind energy

Mathematical optimization

Information theory

Photovoltaics

Instrument modeling

Systems modeling

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