A fuzzy chance-constrained program for unit commitment problem considering demand response, electric vehicle and wind power. (February 2015)

• Record Type: Journal Article
• Authors: Zhang, Ning; Hu, Zhaoguang; Han, Xue; Zhang, Jian; Zhou, Yuhui
• Is Part Of: International journal of electrical power & energy systems. Volume 65(2015:Feb.)
• Page Start: 201
• Page End: 209
• Publication Date: 2015-02
• Subjects: Fuzzy chance-constrained program -- Unit commitment -- Demand response -- Electric vehicle -- Vehicle-to-grid -- Wind power; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2014.10.005
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: We propose a novel unit commitment model considering wind power, DR and EV. DR and EV can relieve the time mismatch between wind power and load demand. DR and EV are able to act as reserve against the uncertainty of wind power. A fuzzy chance constrained program is utilized to deal with the uncertainty. A modified PSO algorithm has been used to solve the problem. Abstract: As a form of renewable and low-carbon energy resource, wind power is anticipated to play an essential role in the future energy structure. Whereas, its features of time mismatch with power demand and uncertainty pose barriers for the power system to utilize it effectively. Hence, a novel unit commitment model is proposed in this paper considering demand response and electric vehicles, which can promote the exploitation of wind power. On the one hand, demand response and electric vehicles have the feasibility to change the load demand curve to solve the mismatch problem. On the other hand, they can serve as reserve for wind power. To deal with the unit commitment problem, authors use a fuzzy chance-constrained program that takes into account the wind power forecasting errors. The numerical study shows that the model can promote the utilization of wind power evidently, making the power system operation more eco-friendly and economical.