Parallel Multi-Objective Genetic Algorithm for Short-Term Economic Environmental Hydrothermal Scheduling

With the increasingly serious energy crisis and environmental pollution, the short-term economic environmental hydrothermal scheduling (SEEHTS) problem is becoming more and more important in modern electrical power systems. In order to handle the SEEHTS problem efficiently, the parallel multi-object...

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Bibliographic Details
Published in:Energies (Basel) 2017, Vol.10 (2), p.163-163
Main Authors: Feng, Zhong-Kai, Niu, Wen-Jing, Zhou, Jian-Zhong, Cheng, Chun-Tian, Qin, Hui, Jiang, Zhi-Qiang
Format: Article
Language:English
Subjects:
Algorithms
Computation
Computer applications
constraint handling method
economic environmental hydrothermal scheduling
Economics
Electric power
Electric power systems
Genetic algorithms
Handles
Hydrothermal systems
Mathematical models
multi-objective genetic algorithm
multi-objective optimization
Multiple objective analysis
parallel computing
Scheduling
Subpopulations
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Summary:With the increasingly serious energy crisis and environmental pollution, the short-term economic environmental hydrothermal scheduling (SEEHTS) problem is becoming more and more important in modern electrical power systems. In order to handle the SEEHTS problem efficiently, the parallel multi-objective genetic algorithm (PMOGA) is proposed in the paper. Based on the Fork/Join parallel framework, PMOGA divides the whole population of individuals into several subpopulations which will evolve in different cores simultaneously. In this way, PMOGA can avoid the wastage of computational resources and increase the population diversity. Moreover, the constraint handling technique is used to handle the complex constraints in SEEHTS, and a selection strategy based on constraint violation is also employed to ensure the convergence speed and solution feasibility. The results from a hydrothermal system in different cases indicate that PMOGA can make the utmost of system resources to significantly improve the computing efficiency and solution quality. Moreover, PMOGA has competitive performance in SEEHTS when compared with several other methods reported in the previous literature, providing a new approach for the operation of hydrothermal systems.
ISSN:1996-1073
1996-1073
DOI:10.3390/en10020163