Reliability and Synergy Analysis of PDN Integrated with Wind Generation and EV-FCS Coupled Traffic Network

Deployment of EV Fast Charging Stations (FCSs) is increasing widely to tackle pollution, limited energy and range anxiety. Their presence in power distribution networks (PDNs) might lead to additional stress on system components, resulting in increased losses and voltage drops. Wind energy, as a green alternative, can mitigate these impacts but may also introduce operational issues such as reverse power flow and voltage rise. This study performs a synergistic analysis of FCS and wind-integrated PDN. Wind power variability is modelled using a Weibull distribution function, while estimates of spatial-temporal FCS charging demand modelled as exponential load are integrated into PDN via a queuing model and transportation surveys. The PDN's performance is determined by quantifying operation parameters and reliability indices. Further, the computation of reliability metrics is done by both analytical and Monte Carlo simulation methods to capture the deterministic and stochastic characteristics of the system's performance. A case study involving a customized IEEE 123-bus PDN linked with a 25-node traffic network is presented. Simulation results show that system behavior is significantly influenced by EV load levels, the degree of wind integration, PDN topology, and the time of day. Wind integration improves system reliability, while increased EV penetration degrades it. Notably, even with wind present, 60% of the annual energy demand remains unserved at a 100 % EV load level. To address this, solar energy is integrated using a kernel distribution function, which reduces the unserved energy to 55%. However, this improvement leads to 5.8% voltage deviations at certain buses, indicating the need for control measures by decision makers to strategically intervene and ensure voltage stability in scenarios with high renewable and EV loads.