Reactive power optimization of hybrid AC/HVDC power system combining interior point algorithm and genetic algorithm

Abstract

In order to simplify the traditional method for calculating AC and DC power flow, we proposed an improved calculation method which uses the Gauss-Seidel iterative method to figure out power flow of the DC system by adjusting the transformer turns ratio to make the firing angle of the inverter run at the right range to solve the DC system, and then alternately iterating with AC power system. As genetic algorithm (GA) is suitable for handling discrete variables but easy to fall into local optimum and interior point algorithm is directional but not suitable for handing discrete variables, we proposed a hybrid algorithm to deal with the reactive power optimization model in the AC-DC system, which uses GA to solve a small number of discrete control variables in AC system and DC system control variables and uses interior point method to solve a large number of continuous control variables in AC system. The hybrid algorithm combines the advantages of two algorithms that can easily handle discrete variables and has a clear direction. Example simulation demonstrates that the algorithm has good convergence and fast operation speed.