Data-driven evaluation for quantifying energy resilience in distribution systems with microgrids and P2P energy trading

Abstract

Electrical distribution systems (EDS) face the major issue of complete interruption of power when the supply end of the electrical grid encounters extreme events. The integration of distributed energy resources (DERs) at the residential level has opened the path to building energy resilience within these systems, enabling them to withstand such incidents at the load end. To further enhance energy resilience, peer-to-peer (P2P) energy trading networks could be established at the community level. While several researchers have developed models to implement energy trading in the P2P network with DERs, enabling prosumers to benefit from cost savings, the impact of both DERs and P2P energy trading on the system’s resilience has not been evaluated with a quantifiable measure. In this work, we propose a methodology introducing a quantifiable measure for evaluating energy resilience in electrical distribution systems with DERs and P2P energy trading by calculating the percolation threshold (PT) using complex networks for both univariate and multivariate data. We employ cooperative game theory to model P2P energy trading, ensuring that all prosumers participate rationally. We consider the formation of microgrids in a standard IEEE-123 node test feeder system integrated with renewable energy sources. The improvement in energy resilience with trading of energy in the P2P network is analyzed for the most resilient microgrid in the distribution system. The results demonstrate a 67.91% total cost benefit and a 25.07% improvement in the resilience of the microgrid due to the integration of DERs and P2P energy trading for a period of one year.