Research On Active Distribution Network Reactive Power Optimization Control Strategy Based On Zoning Control

The increasing penetration of distributed power sources brings many challenges to the optimal operation of distribution networks,and also provides new control means for system voltage and reactive power regulation.However,due to the high dispersion of existing distributed power sources,it is difficult to apply the traditional distribution network to the current highly dispersed distributed power source regulation,and a new control strategy for highly dispersed distributed power source distribution network needs to be studied.On the other hand,the highly dispersed distributed energy sources aggravate the voltage fluctuation of the distribution network,easily generate the overrun limit and deteriorate the system power quality.Therefore,how to solve the power quality problem of distribution network while coordinating the regulation and control strategies of distributed power sources and traditional compensation devices is an important research in today’s distribution network.In response to the above problems,an active distribution network zoning optimization control strategy is proposed.First,the output characteristics of the devices on the power measurement and load side of the active distribution network are modeled,the output curves of each device are derived from the output model of each device,and a scenario simulation analysis method is used to determine the actual output of wind power and PV.Secondly,the impact of distributed power supply access on distribution network voltage and network loss is modeled for distributed power supply access to the distribution network,and the equations for voltage deviation and network loss are derived to derive the impact of distributed power supply access on distribution network voltage and network loss.Based on the number,location and capacity of distributed power supply access to the distribution network,the corresponding simulation is built,and the impact of voltage and network loss under each factor is derived according to the simulation results,which lays a theoretical foundation for the subsequent selection of pivot point,area division and reactive power optimization comparison and verification.Again,an improved hierarchical K-means clustering partitioning method is designed for the distribution network partitioning problem.The algorithm determines the system pivot nodes based on the Newton-Raphson tide calculation equation.Then,the pivot nodes are identified as clusters of the K-means algorithm,the number of partitions needed is determined using the hierarchical clustering algorithm,and the Euclidean distance and contour coefficient are used as criteria for distribution network partitioning to complete the distribution network partitioning based on the improved hierarchical K-means clustering algorithm.The proposed partitioning strategy is simulated and analyzed with the IEEE-33 node system as an example,and the effectiveness and correctness of the partitioning is supported by the partitioning tree diagram and contour coefficients.Finally,an active distribution network reactive power optimization and cooperative control strategy is proposed to address the problems of poor coordination between distributed power sources and reactive power compensation devices and the fluctuating power output.The strategy first uses the hybrid weight method to assign weights to multiple objectives and then transforms them into single-objective optimization,and then uses the improved immune particle swarm algorithm to optimize and verify the distribution network system,and uses the optimization results to guide the cooperative control of voltage within the system area.The simulation results show that the scheme can achieve fast and smooth automatic voltage control in the area and improve power quality.The above study can provide a theoretical basis for the participation of distributed power sources in active distribution network reactive power optimization and cooperative control,and the effectiveness of the method is verified by simulation cases.The thesis includes 45 figures,11 tables and 83 references.