Mixed Integer Nonlinear Programming-Based Unit Commitment of Conventional Thermal Generators Using Hybrid Evolutionary Algorithms
Unit Commitment (UC) discusses the optimized generation resources (to turn on economical generators and turn off expensive generators),which are subjected to satisfy all the operational constraints. The operational constraints such as load balancing, security maximization, minimum up and down time,...
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| Format: | Article |
| Language: | English |
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Sir Syed University of Engineering and Technology, Karachi.
2024-04-01
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| Series: | Sir Syed University Research Journal of Engineering and Technology |
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| Online Access: | http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/577 |
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| author | Syed Arslan Ali Shah Noor Hussain Mugheri Riaz Hussain Memon Aamir Ali Bhatti Muhammad Usman Keerio |
| author_facet | Syed Arslan Ali Shah Noor Hussain Mugheri Riaz Hussain Memon Aamir Ali Bhatti Muhammad Usman Keerio |
| author_sort | Syed Arslan Ali Shah |
| collection | DOAJ |
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Unit Commitment (UC) discusses the optimized generation resources (to turn on economical generators and turn off expensive generators),which are subjected to satisfy all the operational constraints. The operational constraints such as load balancing, security maximization, minimum up and down time, spinning reserve, and ramp up and down constraints are difficult to satisfy. Although, UC is a cost minimization problem that is realized by committing less expensive units while satisfying the corresponding constraints, and dispatching the committed units economically. The UC problem is an np-hard Mixed Integer Nonlinear Problem (MINLP). Therefore, in this paper, hybrid EA based
on a Genetic Algorithm (GA) has been applied to find the optimal solution to the UC problem. Moreover, during the search process, it is very difficult to discard infeasible solutions in EAs. Hence, the Genetic Algorithm (GA) is integrated with the feasibility rule constraint handling technique to emphasize feasible solutions. IEEE RTS Eleven Thermal Generator Standard Test system is used to validate the performance of proposed methods. For the validation and the superiority of the proposed algorithm, simulation results are compared with the classical Lagrangian Relaxation (LR) methods. Results show that the proposed method can find the global optimal solution to the UC problem which is subjected to satisfy all the operational constraints.
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| format | Article |
| id | doaj-art-a4429bb59dfa453dae752bb83b6b3a9c |
| institution | Matheson Library |
| issn | 1997-0641 2415-2048 |
| language | English |
| publishDate | 2024-04-01 |
| publisher | Sir Syed University of Engineering and Technology, Karachi. |
| record_format | Article |
| series | Sir Syed University Research Journal of Engineering and Technology |
| spelling | doaj-art-a4429bb59dfa453dae752bb83b6b3a9c2025-06-27T08:43:30ZengSir Syed University of Engineering and Technology, Karachi.Sir Syed University Research Journal of Engineering and Technology1997-06412415-20482024-04-0114110.33317/ssurj.577Mixed Integer Nonlinear Programming-Based Unit Commitment of Conventional Thermal Generators Using Hybrid Evolutionary AlgorithmsSyed Arslan Ali Shah0Noor Hussain Mugheri1Riaz Hussain Memon2Aamir Ali BhattiMuhammad Usman KeerioQuaid-e-Awam University of Engineering Science and TechnologyQuaid-e-Awam University of Engineering Science and TechnologyQuaid-e-Awam University of Engineering Science and Technology Unit Commitment (UC) discusses the optimized generation resources (to turn on economical generators and turn off expensive generators),which are subjected to satisfy all the operational constraints. The operational constraints such as load balancing, security maximization, minimum up and down time, spinning reserve, and ramp up and down constraints are difficult to satisfy. Although, UC is a cost minimization problem that is realized by committing less expensive units while satisfying the corresponding constraints, and dispatching the committed units economically. The UC problem is an np-hard Mixed Integer Nonlinear Problem (MINLP). Therefore, in this paper, hybrid EA based on a Genetic Algorithm (GA) has been applied to find the optimal solution to the UC problem. Moreover, during the search process, it is very difficult to discard infeasible solutions in EAs. Hence, the Genetic Algorithm (GA) is integrated with the feasibility rule constraint handling technique to emphasize feasible solutions. IEEE RTS Eleven Thermal Generator Standard Test system is used to validate the performance of proposed methods. For the validation and the superiority of the proposed algorithm, simulation results are compared with the classical Lagrangian Relaxation (LR) methods. Results show that the proposed method can find the global optimal solution to the UC problem which is subjected to satisfy all the operational constraints. http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/577evolutionary algorithmsunit commitmentConstraint Handling TechniquesEconomic Dispatch,Mixed Integer |
| spellingShingle | Syed Arslan Ali Shah Noor Hussain Mugheri Riaz Hussain Memon Aamir Ali Bhatti Muhammad Usman Keerio Mixed Integer Nonlinear Programming-Based Unit Commitment of Conventional Thermal Generators Using Hybrid Evolutionary Algorithms Sir Syed University Research Journal of Engineering and Technology evolutionary algorithms unit commitment Constraint Handling Techniques Economic Dispatch, Mixed Integer |
| title | Mixed Integer Nonlinear Programming-Based Unit Commitment of Conventional Thermal Generators Using Hybrid Evolutionary Algorithms |
| title_full | Mixed Integer Nonlinear Programming-Based Unit Commitment of Conventional Thermal Generators Using Hybrid Evolutionary Algorithms |
| title_fullStr | Mixed Integer Nonlinear Programming-Based Unit Commitment of Conventional Thermal Generators Using Hybrid Evolutionary Algorithms |
| title_full_unstemmed | Mixed Integer Nonlinear Programming-Based Unit Commitment of Conventional Thermal Generators Using Hybrid Evolutionary Algorithms |
| title_short | Mixed Integer Nonlinear Programming-Based Unit Commitment of Conventional Thermal Generators Using Hybrid Evolutionary Algorithms |
| title_sort | mixed integer nonlinear programming based unit commitment of conventional thermal generators using hybrid evolutionary algorithms |
| topic | evolutionary algorithms unit commitment Constraint Handling Techniques Economic Dispatch, Mixed Integer |
| url | http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/577 |
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