• 新型电力系统与综合能源 •

### 考虑源荷功率不确定性的海上风力发电多微网两阶段优化调度

1. 广东电网有限责任公司电力调度控制中心,广州 510060
• 收稿日期:2021-10-14 出版日期:2022-10-28 发布日期:2022-11-03
• 作者简介:陆秋瑜(1987-),女,博士,广西壮族自治区贵港市人,高级工程师,从事新能源消纳、储能技术、新能源与储能联合运行技术研究.电话(Tel.):020-85121001;E-mail: luqiuyu22@126.com.
• 基金资助:
南方电网公司科技项目资助(036000KK52190025(GDKJXM20198267)

### Two-Stage Optimal Schedule of Offshore Wind-Power-Integrated Multi-Microgrid Considering Uncertain Power of Sources and Loads

LU Qiuyu(), YU Zhen, YANG Yinguo, LI Li

1. Electric Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510060, China
• Received:2021-10-14 Online:2022-10-28 Published:2022-11-03

Abstract:

Considering the high-randomness and the low-economic-benefit characteristics of the offshore wind-power-integrated multi-microgrid, a two-stage optimal scheduling method considering the uncertain power of source and load is proposed to improve the operation profits of offshore wind-power-integrated multi-microgrid. The proposed two-stage optimal scheduling method consists of a day-ahead stage and an hour-ahead stage. In the day-ahead stage, the proposed method is based on the forecast data of the wind power and the load demand, which considers the distribution characteristics of the prediction errors. A stochastic optimization model is established to determine the unit committee of the diesel generators and the state-of-charge of the battery storages, so as to maximize the expected daily operation income. A deterministic optimization model is established based on the decisions from the day-ahead optimization relying on the hour-ahead forecast data of the wind power output and load demand. By optimizing the power of the diesel generators, wind turbines and battery energy storages, the operation income of each hour is maximized. Finally, a simulation model is established to verify the proposed method based on the prediction data of sources and loads in wind-power-integrated multi-microgrid. The simulation results show that compared with the conventional schedule strategies, the proposed two-stage optimal scheduling method can achieve a higher income and a higher overall consumption rate of the wind power.