Optimal deployment and operations of public charging infrastructure for plug-in electric vehicle

Plug-in electric vehicles (PEVs) are vehicles whose battery packs can be recharged from power grids, and the electricity stored on board propels or contributes to propel the vehicles. PEVs include battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). Interests in PEVs have increased dramatically in recent years due to advances in battery technologies, rising prices of petroleum, and growing concern over environment issues. Many governments have incentive policies, such as offering purchase subsidies and deploying public charging infrastructure in convenient locations, to promote the deployment of PEVs.;Building public charging infrastructure has a profound impact and is typically associated with a high capital cost. To assist policy makers to optimize the investment, this dissertation is devoted to developing a hierarchical modeling framework where a strategic planning model captures interactions between a regional transportation network and power transmission grids to determine a budget allocation plan for public charging stations among metropolitan areas in the region while a tactic planning model considers the spatial distribution of PEVs and optimizes the locations and operations of charging stations in a metropolitan area.;More specifically, at the regional planning level, a static game-theoretic approach is applied to investigate interactions among the availability of public charging stations, destination choices of PEVs, and prices of electricity. The interactions lead to an equilibrium state that can be formulated into a convex mathematical program. We then examine how to allocate the public charging station budget among metropolitan areas in a particular region to maximize social welfare associated with the coupled transportation and power networks. For a particular metropolitan area, given the allocated budget limit, we consider the problem of how to determine the number, locations and types of charging stations within the budget limit. Assuming the locations and types of public charging stations are given, we first develop network equilibrium models with BEVs. Based on the proposed equilibrium models, station location plans are then optimized to maximize social welfare. Lastly, we investigate the operations of public charging stations with a focus on optimizing the prices of electricity at public charging stations.