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Medium-term retailer's planning and participation strategy considering electricity market uncertainties
by
Kharrati, Saeed
, Ehsan, Mehdi
, Kazemi, Mostafa
in
Clients
/ Decision theory
/ forward contracting
/ information-gap decision theory
/ Markets
/ Mathematical programming
/ Nonlinear programming
/ Optimization
/ price uncertainty
/ price-quota curve
/ Pricing
/ retailer's planning
/ Uncertainty
2016
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Medium-term retailer's planning and participation strategy considering electricity market uncertainties
by
Kharrati, Saeed
, Ehsan, Mehdi
, Kazemi, Mostafa
in
Clients
/ Decision theory
/ forward contracting
/ information-gap decision theory
/ Markets
/ Mathematical programming
/ Nonlinear programming
/ Optimization
/ price uncertainty
/ price-quota curve
/ Pricing
/ retailer's planning
/ Uncertainty
2016
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Do you wish to request the book?
Medium-term retailer's planning and participation strategy considering electricity market uncertainties
by
Kharrati, Saeed
, Ehsan, Mehdi
, Kazemi, Mostafa
in
Clients
/ Decision theory
/ forward contracting
/ information-gap decision theory
/ Markets
/ Mathematical programming
/ Nonlinear programming
/ Optimization
/ price uncertainty
/ price-quota curve
/ Pricing
/ retailer's planning
/ Uncertainty
2016
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Medium-term retailer's planning and participation strategy considering electricity market uncertainties
Journal Article
Medium-term retailer's planning and participation strategy considering electricity market uncertainties
2016
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Overview
Summary This paper presents a risk‐constrained programming approach to solve a retailer's medium‐term planning problem. A retailer tries to maximize its profit via determining the optimal price offered to the customers as well as optimal strategy of participating in futures and pool markets. The uncertainty of pool prices is modeled by an envelope‐bound information‐gap model. Another source of uncertainty in this problem is the clients' demand, which is considered via a scenario generation method. The proposed method is formulated as a bi‐level stochastic programming problem based on the information‐gap decision theory. The Karush–Kuhn–Tucker optimality conditions are used to convert the bi‐level problem into a single‐level robust optimization problem. The performance of the proposed method is demonstrated using a case study of the New England market, and results are discussed. Copyright © 2015 John Wiley & Sons, Ltd.
Publisher
Blackwell Publishing Ltd,John Wiley & Sons, Inc
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