采用改进粒子群算法的直流电网最优潮流控制

OPF Control of DC-Grid Using Improved PSO Algorithm

基于柔性直流输电技术的直流电网具有灵活安全的潮流控制能力,在大规模清洁能源发电、海洋群岛供电及新型城市电网构建等方面已成为最有效的技术手段之一。针对直流电网中的最优潮流问题,提出了一种基于模糊控制理论的自适应粒子群算法,以实现电网兼顾有功网损和电压质量的优化运行。首先利用模糊隶属度曲线将两目标转化为单一优化目标,引入当前步适应度为模糊控制器输入端动态调节粒子群算法中的控制参数,使其具更快的收敛性,再用改进的粒子群算法对六端直流电网潮流优化模型进行了求解。最后通过仿真算例验证了所提改进粒子群算法的有效性和可行性。

Able to control power flow flexibly and securely, VSC based DC grid has become one of the most valid approaches for large-scale renewable power generation, oceanic island power supply and new urban grid construction. To solve optimal power flow problem in DC grid, an adaptive particle swarm optimization（PSO） algorithm based on fuzzy control theory is proposed in this paper, and optimal operation considering both power loss and voltage quality is realized. Firstly, fuzzy membership curve is used to transform two objectives into one, and fitness value of last step is introduced as an input of fuzzy controller to adjust PSO controlling parameters dynamically. Then, the improved PSO algorithm is used to solve power flow model of a six-terminal DC grid. Finally, examples are simulated to verify effectiveness and feasibility of the proposed algorithm.