Optimization Scheduling Strategy for Hybrid Pumped-Storage Power Station Under Multi-Transaction Modes

Yueyao WANG , Xiaohe YAN , Nian LIU

›› 2024, Vol. 18 ›› Issue (5) : 51 -61.

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›› 2024, Vol. 18 ›› Issue (5) : 51 -61. DOI: 10.13648/j.cnki.issn1674-0629.2024.05.006
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Optimization Scheduling Strategy for Hybrid Pumped-Storage Power Station Under Multi-Transaction Modes

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Abstract

Under the "Dual Carbon" target, the hybrid pumped storage power station combining conventional hydropower with pumped storage functions is a new trend in hydropower generation. Developing rational scheduling strategies is a key challenge for hybrid pumped storage adaptation to the electricity market. Therefore, a multi-transaction operation mode suitable for hybrid pumped storage power station is proposed, and an internal collaborative control method for the station is proposed based on the characteristics of conventional hydropower and pumped-storage. The conventional hydropower part implements the peak-valley price mechanism, while the pumped storage part implements the two-part tariff mechanism, allowing the station to retain capacity price and participate in the spot market clearing. Based on this operating mode and regulation method, a bi-level optimization scheduling model is proposed to maximize power station profits and social welfare. Finally, the effectiveness of the proposed model is verified through case studies, and the results show that the proposed model is conducive to achieving the rational utilization of hydropower resources. Compared with different single transaction operation modes, the profit of power station increases by at least 1.2%.

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hybrid pumped-storage power station / optimize scheduling / spot market / two-part tariff

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Yueyao WANG,Xiaohe YAN,Nian LIU. Optimization Scheduling Strategy for Hybrid Pumped-Storage Power Station Under Multi-Transaction Modes. 2024, 18(5): 51-61 DOI:10.13648/j.cnki.issn1674-0629.2024.05.006

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Funding

the National Key Research and Development Program of China(2021YFB2400700)

the National Natural Science Foundation for Young Scientists of China(52107090)

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