Hierarchical Progressive Optimization Algorithm for Day-Ahead Planning of Provincial Power Grid with Multiple Pumped Storage Power Stations

doi:10.11930/j.issn.1004-9649.202212044

Abstract

Abstract: The day-ahead planning of the provincial power grid considering the optimization of pumped-storage unit commitment can be expressed as a large-scale mixed-integer linear programming problem, which is difficult to solve directly. Hence, the main factors affecting the consumption of new energy, namely, network constraints and the system’s peak-shaving capacity constraints, are decoupled, and a hierarchical progressive model for day-ahead scheduling optimization is constructed. The model converts the original problem into large-scale linear programming and small-scale integer linear programming. The first layer of the model does not consider the optimization of the pumped-storage unit commitment. The output of the pumped storage power station is relaxed as a continuous variable, and the system network constraints are accurately modeled to minimize the sum of load shedding, wind and photovoltaic power discarding, and unit operating costs. Then, 96-point output curves of each unit in the system are preliminarily obtained. The second layer considers the optimization of the pumped-storage unit commitment. The maximum possible output of new energy units is based on the preliminary results of the first layer. The wind, photovoltaic, thermal power and conventional hydropower units are all equivalent to one unit separately. The optimized pumped-storage unit commitment is obtained without the consideration of network constraints. Finally, the determined pumped-storage unit commitment is brought back to the first layer for back substitution correction, and the 96-point output curve of each unit is calculated. The proposed model has been applied to a provincial power grid, and the correctness and practicability are verified by the actual operation data.

Key words: pumped storage, day-ahead plan, hierarchical optimization, coordinate and optimize dispatching, mixed-integer linear programming

ZHOU Yunhai, ZHANG Zhiying, XU Fei, GUO Qi, LIU Liande, JIA Qian. Hierarchical Progressive Optimization Algorithm for Day-Ahead Planning of Provincial Power Grid with Multiple Pumped Storage Power Stations[J]. Electric Power, 2023, 56(5): 41-50.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202212044

https://www.electricpower.com.cn/EN/Y2023/V56/I5/41

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