Publication: Lagrangian relaxation combined with differential evolution algorithm for unit commitment problem
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Issued Date
2014
Resource Type
File Type
application/pdf
Other identifier(s)
2-s2.0-84946688588
Rights Holder(s)
Scopus
Bibliographic Citation
19th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2014. (2014)
Suggested Citation
Sum-Im T. Lagrangian relaxation combined with differential evolution algorithm for unit commitment problem. 19th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2014. (2014). doi:10.1109/ETFA.2014.7005111 Retrieved from: https://hdl.handle.net/20.500.14740/7232
Author(s)
Abstract
In this paper, a technique of combining Lagrangian relaxation (LR) with a differential evolution algorithm (DEA) method (LR-DEA) is proposed for solving unit commitment (UC) problem of thermal power plants. The merits of DEA method are parallel search and optimization capabilities. The unit commitment problem is formulated as the minimization of a performance index, which is sum of objectives (fuel cost, start-up cost) and several equality and inequality constraints (power balance, generator limits, spinning reserve, minimum up/down time). The efficiency and effectiveness of the proposed technique is initially demonstrated via the analysis of 10-unit test system. A detailed comparative study among the conventional LR, genetic algorithm (GA), evolutionary programming (EP), a hybrid of Lagrangian relaxation and genetic algorithm (LRGA), ant colony search algorithm (ACSA), and the proposed method is presented. From the experimental results, the proposed method has high accuracy of solution achievement, stable convergence characteristics, simple implementation and satisfactory computational time. © 2014 IEEE.
Subject(s)
Algorithms
Ant colony optimization
Computer programming
Constraint theory
Factory automation
Genetic algorithms
Lagrange multipliers
Optimization
Scheduling
Thermoelectric power plants
Ant colony search algorithms
Differential evolution algorithms
LaGrangian relaxation
Lagrangian relaxations
Optimization capabilities
Power generation scheduling
Unit commitment problem
Unit-commitment
Evolutionary algorithms
Ant colony optimization
Computer programming
Constraint theory
Factory automation
Genetic algorithms
Lagrange multipliers
Optimization
Scheduling
Thermoelectric power plants
Ant colony search algorithms
Differential evolution algorithms
LaGrangian relaxation
Lagrangian relaxations
Optimization capabilities
Power generation scheduling
Unit commitment problem
Unit-commitment
Evolutionary algorithms