1. China Power Conversion and Control Engineering Technology Research Center(Hunan University), Changsha 410082, China;2. Longgang Entry Exit Inspection and Quarantine Bureau, Shenzhen 518100, China
Considering the stochastic charging behaviors of electric vehicles(EVs), a software simulation is conducted to simulate the driving patterns of users. Based on the virtual battery aggregation model, a novel double-layer charging control strategy for EV is developed. By synthesizing the strength of the two mainstream control strategies, i. e. centralized control strategy and decentralized control strategy, the charging control is divided into two levels with different optimal objectives. For the upper control layer, the global interests are taken into consideration, and peak load, node voltage and overall electricity cost are adopted as the global optimal objectives. For the bottom layer, in order to consider the high penetrations of EVs, the scalable and flexible alternating direction method of multipliers(ADMM)algorithm is deployed, which blends the benefits of dual decomposition and augmented Lagrangian methods to solve the optimal problem. To verify the effectiveness of the proposed method, four scenarios are simulated and their effects on node voltage, line load, and daily load curve are compared and analyzed. The results indicate that under the proposed charging control strategy, higher node voltage, lower line load and smoother load curve can be achieved.
[1] | HE Xi, TU Chunming, WANG Lili, et al. Double-layer Charging Strategy for Electric Vehicles Considering Users' Driving Patterns[J]. Automation of Electric Power Systems,2018,42(3):64-69. DOI:10.7500/AEPS20170731005 |