Optimal Information Flow-Based Reliability Evaluation for Virtual Power Plants

A virtual power plant (VPP) relies on advanced information and communication technologies (ICTs) to manage massive demand-side resources. Conventional reliability evaluation methods, based on the optimal power flow model, however, cannot be used to evaluate the impacts of random communication failures or ICT component faults. Thus, this article proposes an optimal information flow (OIF)-based reliability evaluation method for a VPP. First, a Poisson point process-based communication reliability model is formulated for a heterogeneous communication network, consisting of WiFi, 4G, and 5G communication channels. Then, an OIF model is established, which not only can characterize the dynamic information flow of the VPP under normal state, but also can readjust the information flow to minimize the impacts when communication failures or ICT component faults happen. Furthermore, a layered greedy algorithm is proposed. The algorithm decomposes the OIF model into many small-scale subproblems and employs greedy rules to find approximation solutions effectively. Case studies are carried out on a VPP test system with 15,120 demand-side resources. Results demonstrate the effectiveness of the OIF model.