ZHANG Xiaoyan, GUO Chuangxin, JIN Guosheng, YIN Kang, GAO Yadong, ZHOU Ying. Collaborative Optimal Dispatch of Multi-Station Integration Based on Affine Robust Optimization[J]. Modern Electric Power, 2022, 39(4): 379-387. DOI: 10.19725/j.cnki.1007-2322.2021.0139
Citation: ZHANG Xiaoyan, GUO Chuangxin, JIN Guosheng, YIN Kang, GAO Yadong, ZHOU Ying. Collaborative Optimal Dispatch of Multi-Station Integration Based on Affine Robust Optimization[J]. Modern Electric Power, 2022, 39(4): 379-387. DOI: 10.19725/j.cnki.1007-2322.2021.0139

Collaborative Optimal Dispatch of Multi-Station Integration Based on Affine Robust Optimization

  • 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.
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