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A solution to unit commitment problem using fire works algorithm

delete2016-05-01
delete28
PRE
AI
B
B. Saravanan *
C
C. Kumar
D
D. P. Kothari
DOI:10.1016/j.ijepes.2015.11.030delete
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摘要

摘要

En 中文
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. (C) 2015 Elsevier Ltd. All rights reserved.
Keyword:
Swarm intelligence
Prohibited operating zone
Unit commitment
Evolutionary programming
Spinning reserve
Fireworks algorithm
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期刊

I
International Journal of Electrical Power and Energy Systems
IF:
5
论文数:
1.1W
被引数:
3.1W

机构

V
vit vellore
学者数:
4.5K
论文数: 4.6K
被引数: 0
B
Bannari Amman Institute of Technology
学者数:
747
论文数: 712
被引数: 6
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