A New Reactive Power optimization Method For Distribution Network with High Participation of Renewable Distributed Generation

A high proportion of renewable distributed generation (DG) is connected into the medium and high voltage distribution network system, and its output randomness and load fluctuations bring great difficulties to its optimal control. Aiming at the problems of node voltage quality reduction and system network loss increase caused by the output randomness and load fluctuation, so a new way of reactive power optimization for distribution network is raised. First, the mathematical model of the net load is analyzed and established to obtain the 24h net load power curve. The idea of pedigree clustering is used to process the net load power curve by time. Secondly, a multi-objective reactive power optimization model for distribution network is established, which takes the minimum of the system loss and node voltage deviatioen as the optimizing objectives, then use Self-Adjusted particle swarm optimization to solve the model. Finally, the feasibility of the proposed method is verified by an IEEE33 node system calculation example.