Multi-objective Reactive Power Optimization of a Distribution Network based on Improved Quantum-behaved Particle Swarm Optimization

Abstract

Background: Reactive power optimization (RPO) is crucial for distribution networks in the context of large-scale renewable distributed generation (RDG) access. Objective: To address the problems caused by the connection of RDG, an RPO model and an improved quantum-behaved particle swarm optimization (IQPSO) algorithm are proposed. Method: In this study, a dynamic S-type function is proposed as the objective function of the minimum active power loss, whereas an exponential function is proposed as the objective function of the minimum voltage deviation to establish an RPO objective function. The operating cost of distribution is considered as the third objective function. To address the RPO problem, a QPSO algorithm based on the ε-greedy strategy is proposed in this paper. ModifiedIEEE33 bus and IEEE69 bus systems were used to evaluate the proposed RPO method in simulations. Results: The simulation results reveal that the IQPSO algorithm obtains a better solution, and the proposed RPO model can considerably reduce active power loss, node voltage deviation, and distribution network operating costs. Conclusion: The RPO model and IQPSO algorithm proposed in this study provide a highperformance method to analyze and optimize reactive power management in distribution network.