Open AccessA SOP planning method for distribution network based on improved genetic algorithm considering EV integration
Author(s) -
Ziang Li,
Lu Zhang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1639/1/012007
Subject(s) - genetic algorithm , mathematical optimization , selection (genetic algorithm) , node (physics) , computer science , workload , electric power , algorithm , power (physics) , convergence (economics) , engineering , mathematics , physics , structural engineering , quantum mechanics , artificial intelligence , economics , economic growth , operating system
With the progress of electric vehicles, there comes a huge number of problems about cost inflation and workload increases in power distribution systems, which caused by the growing number of electric vehicles plugging. Hence, an optimal planning scheme of soft open point (SOP) considering the connection of electric vehicle to power distribution system is proposed. First of all, a SOP two-layer planning model for site selection and capacity determination was established to seek for site selection and capacity determination, so as to minimize the cost. The hybrid optimization algorithm composed of improved genetic algorithm and power flow algorithm was used to solve the problem. Further, the variation of voltage level, before and after the SOP connected to the distribution network, is also analyzed. Finally, the rationality and feasibility of the two-layer programming model of SOP site selection and constant capacity and the hybrid optimization algorithm composed of improved genetic algorithm and power flow algorithm are analyzed with IEEE 33 node example system, and the planning conclusion of effectively reducing the operating cost of the distribution system is obtained. After plugging in SOP according to the planning results, the node voltage value, the average per unit value and the performance of the distribution system are improved to a certain extent. Meanwhile, the operation efficiency, relative error and the convergence capacity according to the modified algorithm are superior to conventional algorithm.