Optimal scheduling method of virtual power plant based on improved particle swarm algorithm

As the complexity of electricity consumption increases, the traditional distribution network is increasingly unable to cope with the complex distribution network load. In order to improve the economic efficiency of the distribution network, this paper proposes an active distribution network economic optimisation dispatching method based on an improved particle swarm algorithm for accessing virtual power plants. After combining the actual situation of a region, the combination of the types as well as the number of distributed power sources and energy storage systems within the virtual power plant is comprehensively considered. The IEEE33 node system is introduced for simulation analysis, and constraints are set and modelled according to active power, reactive power and load demand. By improving the particle swarm algorithm, the selection of inertia weight is optimised to control the scheduling of internal and external power output of the virtual power plant for the twenty-four hours of the day. At the same time, power is purchased from the upper grid in combination with the tariff, and finally the minimum daily operating cost of the distribution network is obtained. This method reduces costs by 11.4% compared to the non-optimised period. It also improves the speed of convergence and perfects the composition of the active distribution network.