Optimal Thermal Unit Commitment Solution integrating Renewable Energy with Generator Outage
The increasing concern of global climate changes, the promotion of renewable energy sources, primarily wind generation, is a welcome move to reduce the pollutant emissions from conventional power plants. Integration of wind power generation with the existing power network is an emerging research fie...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Iran University of Science and Technology
2017-06-01
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| Series: | Iranian Journal of Electrical and Electronic Engineering |
| Subjects: | |
| Online Access: | http://ijeee.iust.ac.ir/browse.php?a_code=A-10-2080-1&slc_lang=en&sid=1 |
| Summary: | The increasing concern of global climate changes, the promotion of renewable energy sources, primarily wind generation, is a welcome move to reduce the pollutant emissions from conventional power plants. Integration of wind power generation with the existing power network is an emerging research field. This paper presents a meta-heuristic algorithm based approach to determine the feasible dispatch solution for wind integrated thermal power system. The Unit Commitment (UC) process aims to identify the best feasible generation scheme of the committed units such that the overall generation cost is reduced, when subjected to a variety of constraints at each time interval. As the UC formulation involves many variables and system and operational constraints, identifying the best solution is still a research task. Nowadays, it is inevitable to include power system reliability issues in operation strategy. The generator failure and malfunction are the prime influencing factor for reliability issues hence they have considered in UC formulation of wind integrated thermal power system. The modern evolutionary algorithm known as Grey Wolf Optimization (GWO) algorithm is applied to solve the intended UC problem. The potential of the GWO algorithm is validated by the standard test systems. Besides, the ramp rate limits are also incorporated in the UC formulation. The simulation results reveal that the GWO algorithm has the capability of obtaining economical resolutions with good solution quality. |
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| ISSN: | 1735-2827 2383-3890 |