When electrical power systems are restructured managers look for satisfying several objectives that include: the working cost minimization and the profit for the unit commitment problems maximization. Power generating companies that comply with the two above mentioned objectives are able to provide good quality and reliable power at a cheaper cost. The individual power producers, schedule their generating units in such a way that they gain maximum profit. This is known as Profit Based Unit Commitment (PBUC). The target of this proposed work is to obtain an optimum generating schedule of the Power Generating Companies (GENCO’s) and maximize the profit of power generating companies when the system is under various constraints like forecasted demand, minimum start-up /shutdown time, spot price, forecasted reserve and ramp rate limits. In order to address this problem, a new meta-heuristic approach called Elephant Herding Optimization (EHO) algorithm is presented. The method may help to solve the complex PBUC problems in the deregulated open market. The effectiveness of projected EHO is tested on various systems with various market conditions. The comparison of the test results with other optimization methods are presented and discussed taking into account their convergence characteristics, solution superiority and reliability.
Deregulation, Elephant herding optimization, Profit based unit commitment.
Sundar RAVICHANDRAN, Manoharan SUBRAMANIAN, "Profit Maximization of GENCO’s Using an Elephant Herding Optimization Algorithm", Studies in Informatics and Control, ISSN 1220-1766, vol. 29(1), pp. 131-140, 2020. https://doi.org/10.24846/v29i1y202013
All articles published by Studies in Informatics and Control (SIC) are published in accordance with the terms and conditions of the Creative Commons Attribution License (CC BY-NC-SA 4.0).