Robust bidding and offering strategies of electricity retailer under multi-tariff pricing

In this paper, an electricity retailer seeks to determine selling price for end-user consumers under fixed pricing (FP), time-of-use pricing (TOU) and real-time pricing (RTP). Furthermore, in order to provide power exchange between the retailer and the power market, bidding and offering curves shoul...

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Bibliographic Details
Published in:Energy economics Vol. 68; pp. 359 - 372
Main Authors: Nojavan, Sayyad, Zare, Kazem, Mohammadi-Ivatloo, Behnam
Format: Journal Article
Language:English
Published: Kidlington Elsevier B.V 01.10.2017
Elsevier Science Ltd
Subjects:
Case studies
Climatic conditions
Consumers
Customers
Electric rates
Electricity
Electricity consumption
Energy economics
Fixed prices
Fixed pricing
Integer programming
Linear programming
Markets
Modelling
Optimization
Power
Prices
Real time
Retailer
Robust optimization approach
Robustness
Stochastic models
Tariffs
Time of use electricity pricing
Time-of-use pricing and real-time pricing
Uncertainty
Upper bounds
Retailer
Robust optimization approach
Fixed pricing
Time-of-use pricing and real-time pricing
ISSN:0140-9883, 1873-6181
Online Access:Get full text
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Summary:In this paper, an electricity retailer seeks to determine selling price for end-user consumers under fixed pricing (FP), time-of-use pricing (TOU) and real-time pricing (RTP). Furthermore, in order to provide power exchange between the retailer and the power market, bidding and offering curves should be prepared to bid and offer to the day-ahead market. Therefore, this paper proposes a robust optimization approach (ROA) to obtain optimal bidding and offering strategies for the retailer. To achieve this, ROA is used for uncertainty modeling of power market prices in which the minimum and maximum limits of prices are considered for uncertainty modeling. Lower and upper bounds of price is consecutively subdivided into sequentially nested subintervals which allows formulating robust mixed-integer linear programming (RMIP) problem. The proposed RMIP model helps retailer to select a robust decision in the presence of market price uncertainty. Furthermore, the bidding and offering curves of the retailer are obtained from sufficient data through solving these problems. Meanwhile, the uncertainty of customers demand and variable climate condition are modeled based on stochastic programming. To validate the proposed robust optimization model, three case studies are evaluated and the results are compared. •Optimal selling price is determined by retailer in the smart grid environment.•Fixed, time-of-use and real-time pricing are determined for selling to customers.•Robust optimization based optimal bidding and offering strategy of retailer is proposed.
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ISSN:0140-9883
1873-6181
DOI:10.1016/j.eneco.2017.10.027