Multi-objective Optimization Scheduling Model of Virtual Power Plants Considering Grid-connected Volatility
With the gradual increase in the penetration rate of distributed energy,the virtual power plant has become a key technology to solve the problem of large-scale development of renewable energy.To mitigate the impact of wind and photovoltaic power generation volatility on the stable operation of virtual power plants,a multi-objective optimization model for virtual power plants was constructed,taking into account wind and solar uncertainty and grid connection volatility.Firstly,wind turbines,photovoltaic units,energy storage devices,gas turbines,and demand response were integrated into a virtual power plant,and a scenario method combining Latin Hypercube Sampling and Manhattan probability distance reduction were used to model the uncertainty of wind and solar power output.Then,with the optimization objectives of minimizing the operating cost,minimizing grid fluctuation,and maximizing user satisfaction of the virtual power plant,a virtual power plant optimization scheduling model was established.Finally,the proposed model was verified through case analysis to achieve the optimal comprehensive benefits of virtual power plants.According to the research results,it provides a reference for virtual power plants to formulate a day ahead scheduling plan that takes into account their own and user interests.
virtual power plantgrid-connected volatilityuser satisfactiondemand responsemulti-objective optimization model
万方数据
维普
