Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6859243 | International Journal of Electrical Power & Energy Systems | 2018 | 11 Pages |
Abstract
Electricity retailers desire to specify the energy acquisition strategy and selling prices in a way that maximize the expected profit, and convince consumers to choose them as the energy provider. Reducing selling price decreases retailers' income, and vice versa. Moreover, the higher selling price increases clients' switching probability to rivals that reduces the retailer's expected income. Therefore, the retailer faces a tradeoff between selling prices and clients' consumption. Additionally, fluctuations of wholesale prices, random demand, unexpected failures of self-generation facilities, and risk of rivals' strategies are other difficulties faced by retailers, and these uncertainty resources affect their profits. This paper presents a fuzzy Information Gap Decision Theory (IGDT) based framework for electricity retailers to specify the energy acquisition strategy. Uncertainty of wholesale price is modeled via unknown bounded intervals. Additionally, the Point Estimate Method (PEM) is proposed to cope with the uncertainty of rivals' strategies. Clients' reaction to retail-selling prices is incorporated into the proposed framework via fuzzy numbers. In order to model the availability of generating units, a novel scheduling framework considering the repair time for failed units, in addition to repair cost and forced outage rate (FOR) is presented in this research. Finally, IGDT methodology is applied to determine the retailer's energy acquisition strategy based on financial risk preferences. Performance of proposed model is evaluated via a case study, and the numerical results are discussed.
Related Topics
Physical Sciences and Engineering
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Artificial Intelligence
Authors
Meysam Khojasteh, Shahram Jadid,