Abstract:

Based on the concept of emission peak and carbon neutrality, the proportion of distributed generation in distribution network system is higher and higher, so it is of practical significance to explore DG for reactive power optimization of distribution network. Based on the economy and safety of distribution network, a comprehensive optimization model of distribution network considering DG reactive power output is proposed. BP neural network based on combined loss function is used to predict the wind power output curve, and the photovoltaic output curve is generated with the data of standard day. The participation of wind turbine and photovoltaic in reactive power optimization is considered. According to the structure of fan and photovoltaic unit, the upper and lower limits of reactive power output are obtained. In order to overcome the situation that particle swarm optimization algorithm is easy to fall into local optimal value, an improved particle swarm optimization algorithm is adopted. The example test results verify the influence of DG reactive power output on distribution network. The proposed model can further reduce loss and improve voltage quality, and realize the joint optimization of DG and static var compensator.

Key words: Distributed generation, reactive power optimization, improve particle swarm optimization, static var compensator