A solution to unit commitment problem using fire works algorithm. (May 2016)

• Record Type: Journal Article
• Authors: Saravanan, B.; Kumar, C.; Kothari, D.P.
• Is Part Of: International journal of electrical power & energy systems. Volume 77(2016:May)
• Page Start: 221
• Page End: 227
• Publication Date: 2016-05
• Subjects: Swarm intelligence -- Prohibited operating zone -- Unit commitment -- Evolutionary programming -- Spinning reserve -- Fireworks algorithm; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2015.11.030
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: UC problem was solved using FWA. Objective of the problem is to minimize the fuel cost of a generator. Prohibited operating zone of generator was included in the constraint. Easy to modify and use the same algorithm in smart grid Environment. Abstract: This paper presents a new approach using swarm intelligence algorithm called Fireworks Algorithm applied to determine Unit Commitment and generation cost (UC) by considering prohibited operating zones. Inspired by the swarm behaviour of fireworks, an algorithm based on the explosion (search) process and the mechanisms of keeping the diversity of sparks has been developed to minimize the total generation cost over a given scheduled time period and to give the most cost-effective combination of generating units to meet forecasted load and reserve requirements, while adhering to generator and transmission constraints. The primary focus is to achieve better optimization while incorporating a large and often complicated set of constraints like generation limits, meeting the load demand, spinning reserves, minimum up/down time and including more realistic constraints, such as considering the restricted/prohibited operating zones of a generator. The generating units have certain ranges where operation is restricted based upon physical limitations of machine components or instability, e.g., due to steam valve or vibration in shaft bearings. Therefore, prohibited operating zones as a prominent constraint must be considered. In this paper the incorporating of complicated constraints of an optimization problem into the objective function is not considered by neglecting the penalty term. Numerical simulations have been carried out on 10 – unit 24 – hour system.