Reactive Power Optimization of PSO-DBN Based on IoT Technology

Abstract

AbstractWhen the large amount of Distributed Generations (DGs) are connected to the grid, the whole distributed power network lost line, and the voltage fluctuates are obvious. In recent years, the concepts of power Internet of Things (IoT)technology and energy Internet are proposed. Therefore, power grid technology has entered a new stage. The IoT technology is characterized by high bandwidth, high transmission rate, and low latency. In addition, with the collected data are increased, IoT becomes an effective way to improve the computing power of edge nodes in edge computing. In order to reduce network losses and voltage fluctuations, reactive power optimization is need to be implement in distribution network system. This paper proposes a distributed power voltage regulation strategy based on the particle swarm optimization and deep belief network (PSO-DBN) under the IoT. Firstly, IoT technology and characteristics are introduced, and the current research status of voltage regulation technology are analyzed in distribution network. Secondly, the weight of DBN is improved with PSO. Finally, the IEEE33 bus system is taken as a simulation case, the effects of daily reactive power optimization and the amount of historical data is analyzed. It is concluded that the method proposed in this paper has obvious effects on reducing voltage fluctuation and network loss. KeywordsDistributed generationIoTPSO-DBNReactive power optimization