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| Multi-station fusion power supply system to assist peak regulation strategy |
| DOI：DOI: 10.19783/j.cnki.pspc.191538 |
| Key Words:multi-station integration power supply area energy storage peak regulation self-discipline operation |
| Author Name | Affiliation | | CHEN Yan | Xingtai Power Supply Branch, State Grid Hebei Electric Power Co., Ltd., Xingtai 054001, China | | JIN Wei | Xingtai Power Supply Branch, State Grid Hebei Electric Power Co., Ltd., Xingtai 054001, China | | WANG Wenbin | Xingtai Power Supply Branch, State Grid Hebei Electric Power Co., Ltd., Xingtai 054001, China | | LI Huibin | Xingtai Power Supply Branch, State Grid Hebei Electric Power Co., Ltd., Xingtai 054001, China | | SHI Zhijie | Xingtai Power Supply Branch, State Grid Hebei Electric Power Co., Ltd., Xingtai 054001, China |
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| Abstract:Based on the idea of global coordination and regional autonomy, the regulation strategy of a multi-station integrated power supply system for assisting peak regulation and autonomous operation is proposed to meet the demand of power grid peak regulation and reserve capacity with large-scale interconnection of distributed generation. It builds relevant technical indicators such as peak regulation and standby to quantify the "self-discipline ability" that a power supply area should have. According to the demand of peak regulation in a power supply area, a variety of autonomous peak regulation control strategies for an energy storage station in the power supply area are proposed. In order to meet the standby demand of peak regulation in the main network and realize "self-regulated" operation in the power supply area, a self-regulated control strategy of energy storage peak regulation is combined to optimize the configuration. A capacity optimization configuration model of an energy storage station in the multi-station fusion power supply area is established. A robust optimization joint endpoint scenario screening method is used to construct a typical power supply region operation scenario and an intelligent optimization algorithm is used to solve the model. Finally, a typical implementation case of multi-station fusion is analyzed and the results prove the effectiveness of the proposed method.
This work is supported by National Natural Science Foundation of China (No. 51607153) and Science and Technology Project of Xingtai Power Supply Branch of State Grid Hebei Electric Power Co., Ltd. |
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