Communication Reliability-based Scheduling Model And Method For A Virtual Power Plant Via Stochastic Programming

Virtual power plants(VPPs),which are supported by advanced measurement,communication networks,and big data processing technologies,have rapidly developed in various countries recently.However,huge meter data and limited spectrum resources have caused packet loss and delays in the communication process of VPPs.As more electric vehicles(EVs)are connected to the power grid,Packet loss and delays greatly reduces the utilization efficiency of VPPs for renewable energy and EVs.In order to solve the unreliable communication problem faced in the VPP scheduling process,the work done in this paper is as follows:An optimal scheduling model for VPPs is established under reliable communication.The model uses EVs as energy storage systems,taking into account the uncertainties of EV driving behavior and the battery degradation cost.Additionally,a two-stage scheduling method is proposed to improve the VPP economic benefits under the premise of following the day-ahead market and the balancing market trading rules.In the first stage,the stochastic optimization approach is adopted to determine the trading strategy of the VPP to maximize the expected profit of the VPP in the day-ahead market.In the second stage scheduling,the rolling horizon optimization method based on the communication data is used to minimize the deviation of the day-ahead scheduling strategy and actual output of the VPP with the minimum cost of power generation.The effect of communication reliability on the scheduling performance of VPPs is analyzed.A VPP communication network based on the cognitive radio technology is constructed.And the relationship between the communication time,the number of smart meters,the method of channel allocation and the average packet loss probability of the VPP is analyzed.Besides,the impact of packet loss on the short-term predictions of renewable energy output and driving characteristics of EVs is further analyzed.A real-time scenariobased optimization scheduling model is established considering packet loss probability.The scheduling strategy of the VPP under different imperfect communication scenarios was obtained via the proposed model.The law of the impact of the packet loss probability on the profit of the VPP and the battery degradation cost of the EV is discovered.An interactive optimization method for VPP communication and energy scheduling is proposed.A dynamic communication channel allocation strategy based on the driving characteristics of EVs for VPP is incorporated into the real-time scheduling model of the VPP.Hence,the optimal scheduling strategy for VPPs under unreliable communication is obtained.Simulations have been implemented to identify the effectiveness of the proposed method on reducing the average packet loss probability of the VPP communication network and improving the economic benefits of the VPP in the electricity market.In summary,this paper proposes an interactive optimization method for VPPs communication and energy scheduling,which reduces the impact of packet loss in communication networks on the scheduling performance of virtual power plants.The proposed method provides reference for the optimal scheduling in VPPs under unreliable communication condition.