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Binary Grey Wolf Optimizer for large scale unit commitment problem

delete2018-02-01
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PRE
AI
L
Lokesh Kumar Panwar *
S
Srikanth Reddy Konda
A
Ashu Verma
B
Bijaya Ketan Panigrahi
R
Rajesh Kumar
DOI:10.1016/j.swevo.2017.08.002delete
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Abstract

Abstract

En 中文
The unit commitment problem belongs to the class of complex large scale, hard bound and constrained optimization problem involving operational planning of power system generation assets. This paper presents a heuristic binary approach to solve unit commitment problem (UC). The proposed approach applies Binary Grey Wolf Optimizer (BGWO) to determine the commitment schedule of UC problem. The grey wolf optimizer belongs to the class of bio-inspired heuristic optimization approaches and mimics the hierarchical and hunting principles of grey wolves. The binarization of GWO is owing to the UC problem characteristic binary/discrete search space. The binary string representation of BGWO is analogous to the commitment and de-committed status of thermal units constrained by minimum up/down times. Two models of Binary Grey Wolf Optimizer are presented to solve UC problem. The first approach includes upfront binarization of wolf update process towards the global best solution (s) followed by crossover operation. While, the second approach estimates continuous valued update of wolves towards global best solution(s) followed by sigmoid transformation The Lambda Iteration method to solve the convex economic load dispatch (ELD) problem. The constraint handling is carried out using the heuristic adjustment procedure. The BGWO models are experimented extensively using various well known illustrations from literature. In addition, the numerical experiments are also carried out for different circumstances of power system operation. The solution quality of BGWO are compared to existing classical as well as heuristic approaches to solve UC problem. The simulation results demonstrate the superior performance of BGWO in solving UC problem for small, medium and large scale systems successfully compared to other well established heuristic and binary approaches.
Keywords:
Unit CoMmitment Problem
Heuristics
Binary Grey Wolf Optimizer (BGWO)
Constrained Optimization
Power system optimization

Journal

Swarm and Evolutionary Computation cover
Swarm and Evolutionary Computation
IF:
8.5
Papers:
2.2K
Citations:
1.0W

Organization

I
indian institute of technology (iit) - delhi
Scholars:
0
Papers: 123
Citations: 0
I
indian institute of technology system (iit system)
Scholars:
9.5W
Papers: 9.9W
Citations: 4.6K
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