Reactive power optimization strategy for power system based on improved genetic algorithm

This paper establishes a double-layer reactive power optimization model to address the increased network losses and voltage drops caused by the integration of large-scale renewable energy. The upper-layer model optimizes the capacity and installation locations of reactive power compensation devices, while the lower-layer model optimizes the reactive power compensation devices and renewable energy output. To solve the double-layer model with different types of variables, this paper proposes a hybrid crossover optimization algorithm to solve the variables based on their classification. Simulation results show that the proposed model and algorithm can effectively reduce operational costs, minimize voltage deviation, and improve system stability.