Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm. (1st February 2017)

• Record Type: Journal Article
• Authors: Wang, Wenxiao; Li, Chaoshun; Liao, Xiang; Qin, Hui
• Is Part Of: Applied energy. Volume 187(2017)
• Page Start: 612
• Page End: 626
• Publication Date: 2017-02-01
• Subjects: Unit commitment -- Wind power -- Photovoltaic power -- Binary artificial sheep algorithm -- Scenario analysis -- Pumped hydro-energy system; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2016.11.085
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: The UC problem consisting of RE uncertainty and PHES has been studied. The Binary sheep algorithm has been proposed to solve the UC problem. Impact of RE uncertainties is comprehensively analysed by a new evaluation method. Influence of PHES on the UC problem is quantitatively evaluated. Abstract: Wind power and photovoltaic power, two types of renewable energy (RE), have made large inroads into the power system. In this paper, we study a unit commitment (UC) problem that considers the uncertainty in RE and pumped hydro-energy storage (PHES). To improve the optimisation performance for this problem, we propose a novel heuristic algorithm called the Binary Artificial Sheep Algorithm (BASA) that is based on the social behaviour of sheep flock. To evaluate the effect of the uncertainty of RE, a scenario evaluation method is defined to assess quantitatively the stability and economy of the UC results with respect to different levels of RE forecasting errors. In addition, we investigate and analyse the effect of PHES on the UC problem. Three UC test systems with different RE and PHES combinations are used to verify the feasibility and effectiveness of the proposed BASA as well as its performance. The proposed BASA performed better than traditional fundamental metaheuristics in solving UC problems. Our results also demonstrated that the equivalent load fluctuation and operating costs of the thermal units will increase significantly with an increase in RE power forecast error, but the PHES can effectively counterbalance this adverse effect.