Energy management considering simultaneous presence of demand responses and electric vehicles in smart industrial grids. (June 2021)

• Record Type: Journal Article
• Authors: Azimi, Zahra; Hooshmand, Rahmat-Allah; Soleymani, Soodabeh
• Is Part Of: Sustainable energy technologies and assessments. Volume 45(2021)
• Publication Date: 2021-06
• Subjects: Industrial virtual power plant -- Stochastic energy management -- Demand response programs -- Electric vehicles -- Mixed integer non-linear programming; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2021.101127
• Languages: English
• ISSNs: 2213-1388

Abstract

Highlights: A method for programming IVPPs considering synchronous presence of DR programs and EVs is presented. The stochastic energy management system is presented to maximize the profits accrued on IVPP. IVPP consists of wind power plants, photovoltaics, DRs, and EVs. The uncertainties in wind and solar power, the day-ahead market and the spot market price, the entry and exit times as well as the initial charge levels of the EVs are considered. In the proposed method, the best program for each IVPP is determined based on DR programs. Abstract: Due to a growing trend in electricity consumption and limitations in expanding the capacity of power plants, the issue of privatizing and restructuring the electricity industry has come to the fore. In this regard, with the emergence of competitive markets, drawing upon responsive programs and electric vehicles in planning smart networks has become an intense topic of research. This paper presents a new method for programming industrial virtual power plants (IVPP) considering synchronous presence of demand response programs and electric vehicles. The proposed algorithm aims at maximizing the proceeds from industrial networks through demand response planning and managing the energy consumption of electrical vehicles. The algorithm is implemented in Zone 2 of the modified version of the IEEE Reliability Test System. The simulation results show that the presence of electric vehicles in the parked position will increase the storage capacity of the IVPPs, whereupon the consumption load on IVPPs is reduced. Using demand response programs in this regard and selecting the best program for each IVPP at different times of the day cuts back on both network operating costs and high consumption peaks, whereby an improvement in the efficiency of electric vehicles parking schemes is obtained.