含混合型潮流控制器的风电并网系统潮流优化

Power Flow Optimization of Wind Power Integrated System With Hybrid Power Flow Controller

混合型潮流控制器(hybrid power flow controller,HPFC)可以有效解决风电并网系统中存在的支路潮流过载问题,且相较于统一潮流控制器成本更低。针对现有的HPFC潮流优化研究尚未计及支路潮流最大值约束和风电不确定性的问题,提出一种基于场景削减的含HPFC风电并网系统最优潮流模型。首先,建立HPFC的功率注入模型,并推导了注入功率表达式;其次,采用K均值算法削减风电、负荷概率场景,通过CH(+)指标选择最优场景集合;最后,建立兼顾发电机运行成本、系统网络损耗、正常运行及N-1故障下的支路负载率的多目标优化模型,采用多目标粒子群优化(multi-objective particle swarm optimization,MOPSO)算法进行求解,利用模糊满意度函数在Pareto解集中筛选出折衷解。在MATLAB中仿真验证所提方法的有效性,结果表明该方法可以计及风电不确定性,保证电网在不同场景下的安全经济运行。

Hybrid power flow controller(HPFC)is effective in branch power flow overload of wind power integrated system with lower cost compared with unified power flow controller(UPFC).Since the existing research of HPFC power flow optimization has not considered the branch power flow maximum constraint and wind power uncertainty,a new power flow optimization model based on scene reduction was proposed for wind power integrated system with HPFC.Power injection model of HPFC was established and corresponding injection power was derived.Then,K-means algorithm was used to reduce the probability scenes of wind power and load,and the optimal scene is selected by the CH(+)index.Besides,a multi-objective optimization model was established,which considers the generator operation cost,power loss of the system,branch load rate in normal operation and after N-1 contingencies.Multi-objective particle swarm optimization(MOPSO)algorithm was used to solve the model,and the selection of compromise solution in Pareto solution was realized by the fuzzy satisfaction function.The effectiveness of the proposed method was verified in MATLAB,and the results show that the method can fully consider the uncertainty of wind power and ensure the safe and economic operation of a power grid in different scenes.