Journal of Shandong University(Engineering Science) ›› 2020, Vol. 50 ›› Issue (4): 90-97.doi: 10.6040/j.issn.1672-3961.0.2019.341

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Bi-level planning of transmission network with solar-storage combination system based on learning theory

SUN Donglei1, ZHAO Long1, QIN Jingtao2*, HAN Xueshan2, YANG Ming2, WANG Mingqiang2   

  1. 1. Economic &
    Technology Research Institute, State Grid Shandong Electric Power Company, Jinan 250021, Shandong, China;
    2. Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education(Shandong Uniersity), Jinan 250061, Shandong, China
  • Published:2020-08-13

Abstract: In order to address the solar power output uncertainty in transmission network planning, a bi-level planning model of transmission network was proposed in which the solar-storage combination system was modeled by learning theory. In the lower level, the scheduled power of solar-storage combination system submitted to the large power system was optimized by maximizing the long-term profit of the solar-storage combination system and minimizing the uncertainty of the planned power. Substituting the planned power of the solar-storage combination system obtained by the lower layer optimization into the upper transmission network planning model, then we minimized the transmission line investment cost, power system operating cost, and solar-shedding cost. The modified IEEE-118 bus system experimental results verified that the solar-storage combination system could reduce the uncertainty of the planned power and enhanced the credibility of planning result. The Q-learning controller established in this paper had good online learning ability and could effectively guide the planned output of the solar-storage combination system after learning a large amount of data.

Key words: learning theory, Q learning algorithm, planning of transmission network, solar-storage combination system, uncertainty

CLC Number: 

  • TM71
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