Coordinated charging of Plug-In Electric Vehicles (PEVs) in residential distribution systems is a new concept currently being explored in the wake of smart grids. Utilities are exploring these options as there are concerns about potential stresses and network congestions that may occur with random and uncoordinated multiple domestic PEV charging activities. Such operations may lead to degraded power quality, poor voltage profiles, overloads in transformer and cables, increased power losses and overall a reduction in the reliability and economy of smart grids. Future smart grids communication network will play an important role in PEV operation because the battery chargers can be remotely coordinated by the utility and harnessed for storing surplus grid energy and reused to support the grid during peak times.Based on a recently proposed PEV charging algorithm, this paper focuses on the impact of coordinated charging on distribution transformer loading and performance. Simulation results are presented to explore the ability of the PEV coordination algorithm in reducing the stress on distribution transformers at different PEV penetration levels. The performance of various distribution transformers within the simulated smart grid is examined for a modified IEEE 23 kV distribution system connected to several low voltage residential networks populated with PEVs.Index Terms-Battery charging, plug-in electric vehicles, transformers and smart grids.
Participation of plug-in electric vehicles (PEVs) is expected to grow in emerging smart grids. A strategy to overcome potential grid overloading caused by large penetrations of PEVs is to optimize their battery charge-rates to fully explore grid capacity and maximize the customer satisfaction for all PEV owners. This paper proposes an online dynamically optimized algorithm for optimal variable charge-rate scheduling of PEVs based on coordinated aggregated particle swarm optimization (CAPSO). The online algorithm is updated at regular intervals of Δt=5min to maximize the customers' satisfactions for all PEV owners based on their requested plug-out times, requested battery state of charges (SOC Req ) and willingness to pay the higher charging energy prices. The algorithm also ensures that the distribution transformer is not overloaded while grid losses and node voltage deviations are minimized. Simulation results for uncoordinated PEV charging as well as CAPSO with fixed charge-rate coordination (FCC) and variable charge-rate coordination (VCC) strategies are compared for a 449-node network with different levels of PEV penetrations. The key contributions are optimal VCC of PEVs considering battery modeling, chargers' efficiencies and customer satisfaction based on requested plug-out times, driving pattern, desired final SOCs and their interest to pay for energy at a higher rate.
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