Binary fireworks algorithm for profit based unit commitment (PBUC) problem

• Published in: International journal of electrical power & energy systems 2016-12, Vol.83, p.270-282
• Main Authors: Srikanth Reddy, K., Panwar, Lokesh Kumar, Kumar, Rajesh, Panigrahi, B.K.
• Format: Article
• Language: English
• Subjects: Binary fireworks algorithm (BFWA); Constrained optimization; Day ahead market (DAM); Deregulated market; Independent power producer (IPP); Profit base unit commitment (PBUC)
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2016.04.005

•Binary fireworks algorithm for solving PBUC is developed.•Application of BFWA to small and large scale test systems is demonstrated.•Various test cases are simulated.•Comparative analysis with existing classical and heuristic approaches. The deregulation of electricity markets has transformed the unit commitment and economic dispatch problem in power systems from cost minimization approach to profit maximization approach in which generation company (GENCO)/independent power producer (IPP) would schedule the available generators to maximize the profit for the forecasted prices in day ahead market (DAM). The PBUC is a highly complex optimization problem with equal, in equal and bound constraints which allocates scheduling of thermal generators in energy and reserve markets with no obligation to load and reserve satisfaction. The quality of the solution is important in deciding the commitment status and there by affecting profit incurred by GENCO/IPPs. This paper proposes a binary coded fireworks algorithm through mimicking spectacular display of glorious fireworks explosion in sky. In deregulated market GENCO/IPP has the freedom to schedule its generators in one or more market(s) based on the profit. The proposed algorithm is tested on thermal unit system for different participation scenarios namely with and without reserve market participation. Results demonstrate the superiority of the proposed algorithm in solving PBUC compared to some existing benchmark algorithms in terms of profit and number of iterations.