WCSE 2022 Spring
ISBN: 978-981-18-5852-9 DOI: 10.18178/wcse.2022.04.017

Day-ahead Optimal Scheduling of Integrated Energy Systems Considering Photovoltaic and Demand Response Uncertainties

Ronghua Zhang, Jianjie Li, Peng Li, Huacan Lv, Chengfu Wang

Abstract— The uncertainty of photovoltaic and demand response brings challenges to the optimal scheduling of integrated energy system (IES) in the market circumstances. In this paper, the uncertainty model of photovoltaic and demand response is firstly established. On this basis, an optimal scheduling strategy based on interval linear stochastic chance constrained programming is proposed. The uncertainty of renewable energy generation prediction is described by probability distribution function, and the uncertainty of load participating demand response is described by interval number. Thus, an interval linear stochastic chance constraint programming model is constructed, and the model is solved by Cplex solver. The proposed method is compared with the interval linear programming and stochastic chance constrained programming models used separately in IES. The results show that the proposed method has lower operating cost and less dependence on the prediction accuracy, and can improve the economy of IES while ensuring the safe operation of the system.

Index Terms— integrated energy system; uncertainty of source and load; day-ahead scheduling; interval linear stochastic chance constrained programming; demand response.

Ronghua Zhang
Binzhou Power Suply Company, State Grid Shandong Electric Power Company, China
Jianjie Li
Binzhou Power Suply Company, State Grid Shandong Electric Power Company, China
Peng Li
Binzhou Power Suply Company, State Grid Shandong Electric Power Company, China
Huacan Lv
School of Electrical Engineering, Shandong University, China
Chengfu Wang
School of Electrical Engineering, Shandong University, China

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Cite: Ronghua Zhang, Jianjie Li, Peng Li, Huacan Lv, Chengfu Wang, "Day-ahead Optimal Scheduling of Integrated Energy Systems Considering Photovoltaic and Demand Response Uncertainties," WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications, pp. 142-150, Sanya, China, April 15-18, 2022.