Optimization of unit commitment using parallel structures of genetic algorithm

Hong Tzer Yang, Pai Chuan Yang, Ching Lien Huang

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

This paper proposes an innovative genetic algorithm (GA) approach to solving the thermal unit commitment (UC) problem using a constraint satisfaction technique. Minimum up-time and down-time constraints on the generating units are embedded in the delicately designed binary strings to represent the on-off states of the units. Ramp rate constraints on the units being started up or shut down are tackled in the economic dispatch subprogram by limiting the associated maximum available capacities for generating. Violations of the other constraints are considered by integrating penalty factors into the cost function. The developed algorithm is further paralleled on an 8-processor transputer network, processors of which are arranged in master-slave and dual-direction ring structures, respectively. The proposed approach is tested on the simple 4 thermal units system and the practical Taiwan Power system of 38 thermal units. Speed-up and efficiency for each structure with different number of processors are compared to those of the sequential GA approach. The proposed approach is shown to be well amenable to parallel implementation.

Original languageEnglish
Pages577-582
Number of pages6
Publication statusPublished - 1995 Dec 1
EventProceedings of the 1995 International Conference on Energy Management and Power Delivery, EMPD'95. Part 1 (of 2) - Singapore, Singapore
Duration: 1995 Nov 211995 Nov 23

Other

OtherProceedings of the 1995 International Conference on Energy Management and Power Delivery, EMPD'95. Part 1 (of 2)
CitySingapore, Singapore
Period95-11-2195-11-23

Fingerprint

Genetic algorithms
Transputers
Cost functions
Economics
Hot Temperature

All Science Journal Classification (ASJC) codes

  • Energy(all)
  • Engineering(all)

Cite this

Yang, H. T., Yang, P. C., & Huang, C. L. (1995). Optimization of unit commitment using parallel structures of genetic algorithm. 577-582. Paper presented at Proceedings of the 1995 International Conference on Energy Management and Power Delivery, EMPD'95. Part 1 (of 2), Singapore, Singapore, .
Yang, Hong Tzer ; Yang, Pai Chuan ; Huang, Ching Lien. / Optimization of unit commitment using parallel structures of genetic algorithm. Paper presented at Proceedings of the 1995 International Conference on Energy Management and Power Delivery, EMPD'95. Part 1 (of 2), Singapore, Singapore, .6 p.
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abstract = "This paper proposes an innovative genetic algorithm (GA) approach to solving the thermal unit commitment (UC) problem using a constraint satisfaction technique. Minimum up-time and down-time constraints on the generating units are embedded in the delicately designed binary strings to represent the on-off states of the units. Ramp rate constraints on the units being started up or shut down are tackled in the economic dispatch subprogram by limiting the associated maximum available capacities for generating. Violations of the other constraints are considered by integrating penalty factors into the cost function. The developed algorithm is further paralleled on an 8-processor transputer network, processors of which are arranged in master-slave and dual-direction ring structures, respectively. The proposed approach is tested on the simple 4 thermal units system and the practical Taiwan Power system of 38 thermal units. Speed-up and efficiency for each structure with different number of processors are compared to those of the sequential GA approach. The proposed approach is shown to be well amenable to parallel implementation.",
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year = "1995",
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Yang, HT, Yang, PC & Huang, CL 1995, 'Optimization of unit commitment using parallel structures of genetic algorithm', Paper presented at Proceedings of the 1995 International Conference on Energy Management and Power Delivery, EMPD'95. Part 1 (of 2), Singapore, Singapore, 95-11-21 - 95-11-23 pp. 577-582.

Optimization of unit commitment using parallel structures of genetic algorithm. / Yang, Hong Tzer; Yang, Pai Chuan; Huang, Ching Lien.

1995. 577-582 Paper presented at Proceedings of the 1995 International Conference on Energy Management and Power Delivery, EMPD'95. Part 1 (of 2), Singapore, Singapore, .

Research output: Contribution to conferencePaper

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N2 - This paper proposes an innovative genetic algorithm (GA) approach to solving the thermal unit commitment (UC) problem using a constraint satisfaction technique. Minimum up-time and down-time constraints on the generating units are embedded in the delicately designed binary strings to represent the on-off states of the units. Ramp rate constraints on the units being started up or shut down are tackled in the economic dispatch subprogram by limiting the associated maximum available capacities for generating. Violations of the other constraints are considered by integrating penalty factors into the cost function. The developed algorithm is further paralleled on an 8-processor transputer network, processors of which are arranged in master-slave and dual-direction ring structures, respectively. The proposed approach is tested on the simple 4 thermal units system and the practical Taiwan Power system of 38 thermal units. Speed-up and efficiency for each structure with different number of processors are compared to those of the sequential GA approach. The proposed approach is shown to be well amenable to parallel implementation.

AB - This paper proposes an innovative genetic algorithm (GA) approach to solving the thermal unit commitment (UC) problem using a constraint satisfaction technique. Minimum up-time and down-time constraints on the generating units are embedded in the delicately designed binary strings to represent the on-off states of the units. Ramp rate constraints on the units being started up or shut down are tackled in the economic dispatch subprogram by limiting the associated maximum available capacities for generating. Violations of the other constraints are considered by integrating penalty factors into the cost function. The developed algorithm is further paralleled on an 8-processor transputer network, processors of which are arranged in master-slave and dual-direction ring structures, respectively. The proposed approach is tested on the simple 4 thermal units system and the practical Taiwan Power system of 38 thermal units. Speed-up and efficiency for each structure with different number of processors are compared to those of the sequential GA approach. The proposed approach is shown to be well amenable to parallel implementation.

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Yang HT, Yang PC, Huang CL. Optimization of unit commitment using parallel structures of genetic algorithm. 1995. Paper presented at Proceedings of the 1995 International Conference on Energy Management and Power Delivery, EMPD'95. Part 1 (of 2), Singapore, Singapore, .