Active Distribution System Reinforcement Planning With EV Charging Stations—Part I: Uncertainty Modeling and Problem Formulation

Abstract

Due to the associated uncertainties, the large-scale deployment of electric vehicles (EVs) and renewable distributed generation is a major challenge faced by the modern distribution systems. The first part of this two-paper series proposes a scenario-based stochastic model for the multistage joint reinforcement planning of the distribution systems and the electric vehicle charging stations (EVCSs). The historical EV charging demand is first determined using the Markovian analysis of EV driving patterns and charging demand. A scenario matrix, based on the heuristic moment matching method, is then generated to characterize the stochastic features and correlation among historical wind and photovoltaic generation, and conventional loads and EV demands. The scenario matrix is then utilized to formulate the expansion planning framework, aiming at the minimization of the investment and operational costs. The proposed expansion plan determines the optimal construction/reinforcement of substations, EVCSs, and feeders, in addition to the placement of wind and photovoltaic generators, and capacitor banks over the multi-stage planning horizon. In the second companion paper, the effectiveness and scalability of the proposed model is assessed through case studies in the 18-bus and the IEEE 123-bus distribution systems, respectively.