Abstract
A distributed electric vehicle (EV) charging scheduling strategy with transactive energy (TE) management is presented in this paper to deal with technical issues in distribution network operation and discuss the economic benefits of EV charging. At an individual EV level, EV owners propose bids to actively participate in the distribution system operation. At the node level, an electric vehicle aggregator (EVA) optimally allocates the available charging power to meet EV charging requirements and cost benefits. At the distribution network level, a distribution system operator (DSO) integrates an electricity price market clearing mechanism with the optimal power flow (OPF) technique to ensure the reliability of the distribution network. Moreover, a distributed algorithm is discussed for solving the EV charging problem with transactive energy management (TEM). The clearing electricity price is achieved through a negotiation process between the DSO and EVAs using the alternating direction method of multipliers (ADMM). The presented EV charging scheduling with TEM is tested on a modified IEEE 33-bus distribution network scenario with 230 EV charging loads. The simulation results demonstrate the effectiveness of the TE-based EV charging scheduling system.
Highlights
In recent years, the market share of electric vehicles has rapidly increased
These results show that transactive energy (TE)-based electric vehicle (EV) charging management can avoid load congestion and improve grid performance
The results show that transactive energy management (TEM) can reduce about 39.55% cost for 230 EVs through a clearing price
Summary
The market share of electric vehicles has rapidly increased. It is estimated that global electric vehicle sales will reach a total of 22 million by 2025 [1]. Large-scale EV charging may cause significant impacts on the distribution network compared with conventional building loads These works [16,17] have addressed distribution power network operation with the OPF technique, but lack price mechanism analysis. The research towards applying truly transactive energy management, including the economic benefits of market or price mechanisms and the optimal operation of the distribution network, to large-scale EV charging scheduling, is still to be widely explored. In this algorithm, EV charging scheduling and clearing electricity prices are determined through a negotiation process among DSOs and EVAs. EVAs ensure that EV charging requirements and charging cost economics are met, and DSOs guarantee the distribution network operation stability with OPF.
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