Dynamic Economic Load Dispatch Using GAMS

This study addresses dynamic economic load dispatch, a critical and complex problem in power systems that aims to minimize fuel costs for the efficient operation of power systems. To solve this problem, GAMS software was used, known for its high solution capability, ease of application, fast computation time, and ability to achieve optimal results in handling complex problems. The model was developed for two different test systems, consisting of 5 and 10 generating units. Constraints such as generator capacity, demand and ramp rate were incorporated into the solution. According to the analysis results, the total fuel cost for the 5-unit system was $40,121, while for the 10-unit system it was $2,422,246. The results show a clear advantage in daily fuel costs compared to methods like GA, DE-SQP, PSOSQP, and PSOCS. Specifically, the GAMS approach achieves an annual total fuel cost saving of approximately $1,460,000 for the 5-unit system and $28,400,000 for the 10-unit system.

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Publication Details

Published
2024-12-04
DOI
https://doi.org/10.1109/gec61857.2024.10881582
Primary Topic
Scheduling and Optimization Algorithms
Type
article
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article

Dynamic Economic Load Dispatch Using GAMS

Cenk Andiç, Belgin Emre Türkay, Esra Aydın
Scheduling and Optimization Algorithms
article

Dynamic Economic Load Dispatch Using GAMS

Cenk Andiç, Belgin Emre Türkay, Esra Aydın
article en

Abstract

This study addresses dynamic economic load dispatch, a critical and complex problem in power systems that aims to minimize fuel costs for the efficient operation of power systems. To solve this problem, GAMS software was used, known for its high solution capability, ease of application, fast computation time, and ability to achieve optimal results in handling complex problems. The model was developed for two different test systems, consisting of 5 and 10 generating units. Constraints such as generator capacity, demand and ramp rate were incorporated into the solution. According to the analysis results, the total fuel cost for the 5-unit system was $40,121, while for the 10-unit system it was $2,422,246. The results show a clear advantage in daily fuel costs compared to methods like GA, DE-SQP, PSOSQP, and PSOCS. Specifically, the GAMS approach achieves an annual total fuel cost saving of approximately $1,460,000 for the 5-unit system and $28,400,000 for the 10-unit system.

Istanbul Technical University (TR)
Decent work and economic growth
Openalex Percentile: Top 59%
Scheduling and Optimization Algorithms
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