This paper describes an open access transmission method for maximizing profits in a power system. The proposed method is based on the Nash bargaining game for power flow analysis in which each transaction and its optimal price are determined to optimize the interests of individual parties. Transmission losses are considered by the proposed method, and test cases and results are discussed to present the merits of the proposed method.
This article presents a new, improved particle swarm optimization algorithm with a selection operator for the solution of the combined heat and power economic dispatch problem. In this technique, starting with a large swarm of particles, only those particles whose fitness is above the scaled average fitness are selected in successive iterations, using a selection factor that is adjustable depending on the nature of the problem. The method is illustrated using a test case. The result compares favorably with other particle swarm optimization variants and other existing non-conventional methods.
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