Nodal-based ant colony optimization for profit maximization of gencos in a distributed cluster model

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Abstract

In the deregulated electricity market, each generating company has to maximize its own profit by committing to a suitable generation schedule termed profit-based unit commitment (PBUC). This article proposes a nodal ant colony optimization (NACO) solution to the PBUC problem. This method has better convergence characteristics in obtaining an optimum solution. The proposed approach uses a cluster of computers performing parallel operations in a distributed environment for obtaining the PBUC solution. The time complexity and the solution quality, with respect to the number of processors in the cluster, are thoroughly tested. The method has been applied to systems of up to 120 units, and the results show that the proposed NACO in a distributed cluster consistently outperforms the other methods that are available in the literature. © 2013 Taylor and Francis Group, LLC.

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Columbus, C. C., & Simon, S. P. (2013). Nodal-based ant colony optimization for profit maximization of gencos in a distributed cluster model. Applied Artificial Intelligence, 27(2), 86–103. https://doi.org/10.1080/08839514.2013.760404

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