Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6859491 | International Journal of Electrical Power & Energy Systems | 2018 | 12 Pages |
Abstract
For a generation company trading in an electricity market, efficient control of the financial risks and robustness is as vital as maximizing profit. A robust approach is preferred since the generation company can obtain an optimal self-schedule considering price volatility as a source of uncertainty. The goal of this paper is to implement and compare different robust approaches such as robust optimization methods with different uncertainty sets, conditional value-at-risk based stochastic programming, and information gap decision theory for self-scheduling of generation companies. Moreover, all robust methods are applied to test cases with different price behaviors in the long-run to demonstrate the performance and features of each method. Finally, the different self-scheduling strategies based on the price data and the generation company's desired robustness level are proposed.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Behdad Vatani, Badrul Chowdhury, Shahab Dehghan, Nima Amjady,