Research On Reactive Power Optimization And Loss Reduction Of Network Based On Data Mining Technology

Network reactive power optimization can effectively reduce the loss of network,improve the economic performance of network along with improve the quality of voltage and so on.Big data and data mining technology can fully explore the effective information in the network data,and optimize the model to solve.So the research of network reactive power optimization has the important theoretical significance and practical value.Based on the research of data mining algorithm,this paper establishes a reactive power optimization model of network,which combines support vector machine with genetic algorithm,applied to solve the reactive power optimization model.Through the detailed analysis of the selection of the optimization parameters,performance analysis and process realization,the effectiveness of the proposed algorithm is demonstrated by an example in Inner Mongolia.Through the analysis of reactive power optimization in network,in order to reduce the loss of the network,the paper establishes the reactive power optimization and loss reduction system of the power network.The system design,system structure and control strategy of the system are introduced in detail.The practical analysis shows that the control system is applicable and the control equipment is stable and reasonable,which can effectively reduce the loss of power network and improve the qualified rate of the voltage.