The number of plug-in electric vehicles (PEV) increased significantly over the past few years and is expected to increase further in the next years due to environmental concerns and fossil fuel depletion. Distribution systems were not originally designed to accommodate this continuous prevalence of PEVs, challenging system planners to install parking lots (PLs) that support PEV charging. The literature has presented many studies for planning PLs, although it did not consider the vehicle-to-grid (V2G) contribution to improving system reliability. This paper proposes an optimal planning framework for allocating and sizing the PLs of PEVs incorporating V2G to improve the reliability of distribution systems. A combined probabilistic model of Markov Chain Monte Carlo simulation (MCMCS) and Monte Carlo simulation (MCS) is applied to capture the stochastic existence of PEVs in PLs. Reliability is evaluated based on a group of energy-oriented indices and the customer's annual cost of interruption. A comprehensive investigation is presented to test the proposed framework on a distribution system for gridto-vehicle (G2V) and V2G case studies. The results show the efficiency of the proposed framework in improving the reliability indices by 12% and reducing the customer cost of interruption by 10.06% while
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.