Decentralized stochastic programming for optimal vehicle‐to‐grid operation in smart grid with renewable generation. Issue 4 (21st January 2021)

• Record Type: Journal Article
• Authors: Wang, Yue; Liang, Hao; Dinavahi, Venkata
• Is Part Of: IET renewable power generation. Volume 15:Issue 4(2021)
• Page Start: 746
• Page End: 757
• Publication Date: 2021-01-21
• Subjects: Optimisation techniques -- Power system management, operation and economics -- Distribution networks -- Energy resources -- Solar power stations and photovoltaic power systems -- Other power stations and plants -- Transportation -- Optimisation techniques -- Power engineering computing -- Distributed power generation; Renewable energy sources -- Periodicals; 333.79405
• DOI: 10.1049/rpg2.12064
• Languages: English
• ISSNs: 1752-1416

Abstract

Abstract: This paper presents a decentralized stochastic programming operation scheme for a vehicle‐to‐grid system in a smart grid, which includes a series of equipment with random power generation and demands. For households with electric devices, renewable solar power generation, energy storage systems and electric vehicles, we consider utility operating expenses, including power loss and energy consumption cost as the objective function. For customers, we consider the cost of electricity, including battery degradation. To investigate the uncertainty of the devices, a bottom‐up approach is proposed to develop a random device usage model for analyzing customers' uncertain behaviour. Besides, a random renewable power generation model and an electric vehicle random driving model are implemented. The proposed approach is implemented with OpenMP to simulate the decentralized process on a multi‐core CPU while reducing the computational burden. A case study based on the IEEE 33‐bus distribution system with different scenarios is used to evaluate the performance of the proposed approach. The simulation results show that by introducing an optimal household operation schedule, the expense of distribution system utility company can be reduced in which both customers and operators can benefit from the optimization of the system schedules.