A HYBRID LR-FA TECHNIQUE TO OPTIMIZE THE PROFIT FUNCTION OF GENCOS IN A RESTRUCTURED POWER SYSTEM

Rampriya B. Perumal, Mahadevan Krishnan, and Kannan Subramanian

Keywords

Dynamic programming, evolutionary programming, generation companies, genetic algorithm, independent system operator, firefly algorithm, profitbased unit commitment

Abstract

Profit-based unit commitment (PBUC) in deregulated power system has a different objective, i.e., to maximize its profit. But, in traditional Unit commitment (UC), the objective is to minimize its total operating cost. Also, in PBUC, there is no obligation to serve/meet the demand, whereas in traditional UC, the demand must be met. This paper presents a solution for PBUC by the use of Lagrangian relaxation (LR) and firefly algorithm (FA). The solution of PBUC is to determine the ON/OFF schedule of generating units, their power output, spinning reserve generations of generation companies (GENCOs) taking part in the competition. The algorithm is tested for a test system with 10-units 24-h data and the simulations are carried out using MATLAB. The resultant schedule evidently maximizes the profit and this can be extended to “n number of generating units.

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