Evaluation of Accommodation Capability for Electric Vehicles of a Distribution System Considering Coordinated Charging Strategies

Abstract

In recent years, the ever-increasing charging demand of electric vehicles (EVs) imposes challenges on both power supply security and reliability in the distribution system. In this paper, an EV accommodation capability evaluation model of a distribution system, with high penetrations of flexible resources, is established. Firstly, according to the actual classifications of EVs and transportation rules, a Monte Carlo simulation is used to simulate the charging behaviors of EVs so as to obtain the relevant parameters of EV charging. Then, a coordinated charging optimization model for various types of EVs is proposed based on the charging characteristics of EVs. The presented model comprises a mixed-integer linear programming problem and a constrained optimization problem which are respectively solved by CPLEX (the Simplex method implemented in the • C programming language) and the particle swarm optimization (PSO) algorithm. Last of all, a real-life distribution system in the coastal areas of China is served for demonstrating the feasibility and efficiency of the proposed approach. Moreover, the impacts of flexible resources, distribution network zoning rules, and EV growth on the EV accommodation capability of a distribution system are also discussed.Energies 2019, 12, 3056 2 of 20 capability for EVs (ACE). At the same time, the optimized EV charging load (OECL) obtained by the coordinated charging strategies is also conducive to understanding the relationship between EV accommodation and charging load distribution.It is generally agreed that the problems of environmental pollution and energy security can be abated by increasing the penetration level of both EVs and flexible resources, such as a variety of distributed generations (DGs) and energy storage systems (ESSs). Flexible resources on the demand side will play a pivotal role in reducing load fluctuations in the distribution system [10]. Besides, better utilization of the flexible resources on both power supply and demand sides is one approach to increase the ACE. Joint optimal scheduling of flexible resources and EVs have been investigated by a number of researchers. Simultaneous provision of interruptible loads for flexible ramping products and demand relief are considered in Reference [11]. The impact of EVs and demand response (DR) on the flexibility of a microgrid are analyzed in Reference [12]. A multi-objective optimal scheduling method for a distribution network with the integration of numerous EVs is proposed in Reference [13].In terms of the ACE evaluation, there are mainly two types of methods. One method is to optimize the maximum ACE under the assumption of EV behaviors being guided by a smart charging strategy or a market mechanism. In Reference [14], a market mechanism that optimally allocates available charging capacity is proposed, considering the network stability and the EV owners' individual preferences. In Reference [15], a market-based multi-agent control mechanism that takes into account the distribution transformer and voltage constra...

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