Multi-objective optimization strategy for distribution network considering V2G-enabled electric vehicles in building integrated energy system

• Main Authors: Zhao Huang, Baling Fang, Jin Deng
• Format: Article
• Language: English
• Published: SpringerOpen 2020-01-01
• Series: Protection and Control of Modern Power Systems
• Subjects: Distribution network; Electric vehicles; Multi-objective optimization; Coordinated dispatch; Advanced genetic algorithm
• Online Access: https://doi.org/10.1186/s41601-020-0154-0

Abstract Based on the large-scale penetration of electric vehicles (EV) into the building cluster, a multi-objective optimal strategy considering the coordinated dispatch of EV is proposed, for improving the safe and economical operation problems of distribution network. The system power loss and node voltage excursion can be effectively reduced, by taking measures of time-of-use (TOU) price mechanism bonded with the reactive compensation of energy storage devices. Firstly, the coordinate charging/discharging load model for EV has been established, to obtain a narrowed gap between load peak and valley. Next, a multi-objective optimization model of the distribution grid is also defined, and the active power loss and node voltage fluctuation are chosen to be the objective function. For improving the efficiency of optimization process, an advanced genetic algorithm associated with elite preservation policy is used. Finally, reactive compensation capacity supplied by capacitor banks is dynamically determined according to the varying building loads. The proposed strategy is demonstrated on the IEEE 33-node test case, and the simulation results show that the power supply pressure can be obviously relieved by introducing the coordinated charging/discharging behavior of EV; in the meantime, via reasonable planning of the compensation capacitor, the remarkably lower active power loss and voltage excursion can be realized, ensuring the safe and economical operation of the distribution system.