1.Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China;2.Foshan Power Supply Bureau of Guangdong Power Grid Co., Ltd, Foshan 528000, China;3.School of Engineering, Cardiff University, Cardiff CF24 3AA, UK
This work is supported by National Natural Science Foundation of China-State Grid Joint Fund for Smart Grid (No. U1866207) and National Natural Science Foundation of China (No. 51807132).
Soft open points (SOPs), which have powerful capability of power flow control, can make positive contribution under normal operation and fault conditions of distribution network. The benefits both from the improvement of power supply reliability and operation economy should be taken into account at the planning stage. Planning model of SOPs is proposed in this paper considering the effect of connecting SOP on supply reliability and operation economy in distribution network. The fast-search and the method of finding density peaks clustering are used to aggregate the annual load data, and the typical operation scenarios in distribution network are generated to calculate the improvement cost of operation economy. The calculation method of branch failure rate based on related constraints is adopted, considering the influences of load rate of line current, node voltage and length of line on branch failure rate, the dynamic prediction failure set is generated to calculate the benefits of power supply reliability. A hybrid optimization algorithm, which combines the simulated annealing method with the second-order cone programming, is used to solve the planning model mentioned above. Finally, the effectiveness of the proposed planning model is verified by the modified PG&E 69-node test system. The results show that the SOP planning method facing reliability and economy in distribution network can effectively reduce the comprehensive cost of distribution network and maximize the investment benefits.
ZHAO Jinli,CHEN Hao,SONG Guanyu,et al.Planning Method of Soft Open Point in Distribution Network Considering Reliability Benefits[J].Automation of Electric Power Systems,2020,44(10):22-31.DOI:10.7500/AEPS20190715008Copy