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基于仿射鲁棒优化的多站融合协同优化调度
引用本文:张笑演,郭创新,金国胜,尹康,高亚栋,周盈. 基于仿射鲁棒优化的多站融合协同优化调度[J]. 现代电力, 2022, 39(4): 379-387. DOI: 10.19725/j.cnki.1007-2322.2021.0139
作者姓名:张笑演  郭创新  金国胜  尹康  高亚栋  周盈
作者单位:1.浙江大学电气工程学院,浙江省杭州市310027
摘    要:为解决新能源出力不确定性的多能电站(数据中心、电动汽车充电站、分布式光伏、风电、储能站)优化运行和收益分配问题,提出基于仿射鲁棒优化的多站融合协同优化策略。考虑数据中心与其余子系统分属不同运营商,对多站融合系统中各子系统进行建模,其中数据中心的负载具有可平移负荷的特性;通过盒式不确定集对风电和光伏出力的不确定性进行建模;以多站融合协同总收益最大化为目标函数,采用仿射鲁棒优化方法进行求解。提出了基于影子价格的能源站与数据中心站的收益分配方法。最后,通过仿真算例说明了所提模型的有效性和所提收益分配方法的合理性。

关 键 词:多站融合   数据中心   电动汽车   仿射鲁棒   优化调度
收稿时间:2021-05-03

Collaborative Optimal Dispatch of Multi-Station Integration Based on Affine Robust Optimization
Affiliation:1.College of Electrical Engineering, Zhejiang University, Hangzhou 310027, Zhejiang Province, China2.Zhejiang Huayun Electric Power Engineering Design & Consultation Co., Ltd, Hangzhou 310014, Zhejiang Province, China
Abstract:To cope with the optimal operation and income distribution of multi-energy power stations such as data centers, electric vehicle charging stations, distributed photovoltaic generation, wind power stations and energy storage stations accompanied with uncertain renewable energy output, an affine robust optimization-based a multi-station collaborative optimization strategy was proposed. Considering the fact that the data center and other subsystems belonged to different operators, the modeling for each subsystem of the multi-station integration system, in which the load in the data center possessed the characteristics of shifting load, was respectively conducted. By means of box uncertainty set, the modeling for the uncertainty of the output of wind power stations and the photovoltaic generation was carried out. Taking the maximum of total revenue from the multi-station fusion and coordination as objective function, the proposed models were solved by affine robust optimization method. A shadow price-based income distribution method for energy stations and data centers was proposed. Finally, the effectiveness of the proposed models and the reasonableness of the proposed income distribution method are verified by the results of simulation example.
Keywords:
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