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

Hybrid power flow controller (abbr. HPFC) is effective in branch power flow overload of wind power integrated system with lower cost compared with unified power flow controller (abbr. 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.