Stochastic Risk-Constrained Decision-making Approach for a Retailer in a Competitive Environment with Flexible Demand Side Resources

Homa Rashidizadeh-Kermani, Mostafa Vahedipour-Dahraie, Amjad Anvari-Moghaddam, Josep M. Guerrero

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

21 Citationer (Scopus)
276 Downloads (Pure)

Abstract

This paper presents a risk-averse stochastic bi-level programming approach to solve decision-making of a retailer in a competitive market under uncertainties. The retailer decides the level of involvement in day-ahead (DA) and regulation markets by making an optimal bidding strategy with the goal of expected profit maximization. Uncertainties associated with DA prices, up/down regulation market prices, customers’ demand and rival retailers’ behaviors are tackled through a stochastic programming model. In the proposed model responsive loads and electric vehicles (EVs) track the real-time prices and choose the proper retailer to minimize their payments in the competitive trading floor. The obtained nonlinear stochastic model is transformed into an equivalent linear single-level program by replacing the lower-level problem with its Karush–Kuhn–Tucker optimality conditions and using duality theory. Finally, the proposed methodology is evaluated by applying to a realistic case study and the results demonstrate the effectiveness of the proposed framework.
OriginalsprogEngelsk
Artikelnummere2719
TidsskriftInternational Transactions on Electrical Energy Systems
Vol/bind29
Udgave nummer2
Antal sider23
ISSN1430-144X
DOI
StatusUdgivet - feb. 2019

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