A bi-level risk-constrained offering strategy of a wind power producer considering demand side resources. (January 2019)

• Record Type: Journal Article
• Authors: Rashidizadeh-Kermani, Homa; Vahedipour-Dahraie, Mostafa; Shafie-khah, Miadreza; Catalão, João P.S.
• Is Part Of: International journal of electrical power & energy systems. Volume 104(2019)
• Page Start: 562
• Page End: 574
• Publication Date: 2019-01
• Subjects: Demand response -- Electric vehicle -- Offering strategy -- Risk-constrained -- Wind power producer; 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.2018.07.038
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A stochastic decision making problem for a wind power producer in the electricity markets is proposed. The bidding strategy considers demand response and electric vehicle aggregators. The problem is formulated as a stochastic bi-level programming model with conflict objectives. Conditional value at risk is applied to the proposed model. The proposed model is evaluated on a realistic case study and the impacts are investigated. Abstract: This paper proposes a stochastic decision making problem for a wind power producer (WPP) in the day-ahead (DA) and balancing markets. In this problem, bidding strategy of the WPP in a competitive electricity market and also its participation to supply demand response (DR) and electric vehicle (EV) aggregators is determined to achieve the maximum profit. In this model, DR and EV aggregators are able to choose the most competitive WPP in such a way that their energy payments be minimized in the scheduling horizon. Therefore, the problem is formulated as a stochastic bi-level programming model with conflict objectives of the WPP and the aggregators. Moreover, owing to the uncertainties associated with market prices, offered prices by rival WPPs, demand of DR and EV aggregators, conditional value at risk (CVaR) is applied to the proposed model. The attained stochastic bi-level problem is transformed to a linear stochastic single level problem with equilibrium constraints using Karush–Kuhn–Tucker (KKT) optimality conditions. The proposed model is evaluated on a realistic case study and the impacts of risk-averse behavior and demand response participants on the decision making problem of the WPP are investigated. Numerical results indicate that with increasing DR participants of 0%, 60% and 100%, CVaR of WPP increases 33.81%, 40.79% and 46.99%, respectively. This means that if the loads are more responsive, the WPP tries to control the profit variability due to the uncertainties of loads.