Open AccessDecentralized stochastic programming for optimal vehicle‐to‐grid operation in smart grid with renewable generation
Author(s) -
Wang Yue,
Liang Hao,
Dinavahi Venkata
Publication year - 2021
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/rpg2.12064
Subject(s) - schedule , computer science , renewable energy , grid , smart grid , stochastic programming , electric vehicle , electricity , electric power system , mathematical optimization , automotive engineering , reliability engineering , power (physics) , engineering , electrical engineering , physics , geometry , mathematics , quantum mechanics , operating system
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.