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:: Volume 1, Issue 2 (Fall 2023) ::
3 2023, 1(2): 1001-1012 Back to browse issues page
Forecasting the maximum power that can be produced by gas power plants Using the optimal model based on genetic algorithm
Hossein Samsami , Alireza Samsami
Saba Power Plant Operation and Repair Company - Soltanieh Combined Cycle Power Plant
Abstract:   (191 Views)
The importance of electrical energy and its increasing use on the one hand and the existence of limited primary resources in its production on the other hand, have made planning for the optimal use of electricity networks and power plant production management very important. One of the important parameters in planning the production of power plant units is knowing the production capacity of these units and predicting the current capacity of the power plants so that the entry and exit of the units and how to operate them can be managed based on that. This research has considered the gas power plants that are widely used in the country and are installed and operated in large numbers and has presented a model to predict their momentary base load. In the following, the optimization method based on the genetic algorithm was used to determine the parameters of this model and its ability to predict the instantaneous capacity of Soltanieh Zanjan power plant units was evaluated. The obtained results and its comparison with the previous methods show the high capability and appropriate accuracy of the stated method in predicting the instantaneous base load of gas power plants.
Keywords: Gas power plant, maximum power that can be produced, model, optimization
Full-Text [PDF 1353 kb]   (27 Downloads)    
Type of Study: Research | Subject: General
Received: 2022/10/18 | Accepted: 2022/12/1 | Published: 2022/12/1
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Samsami H, Samsami A. Forecasting the maximum power that can be produced by gas power plants Using the optimal model based on genetic algorithm. 3 2023; 1 (2) :1001-1012
URL: http://ijoem.ir/article-1-31-en.html


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Volume 1, Issue 2 (Fall 2023) Back to browse issues page
Journal of Energy Markets Research Journal of Energy Markets Research
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