Towards load frequency management in thermal power systems using an improved open-source development model algorithm

Maintaining a balance between generated and consumed power is crucial for the efficient operation of interconnected power grids. This paper focuses on the issue of load frequency management in thermal power systems. We present a metaheuristic approach to address this problem, leveraging the advantag...

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Vydané v:Evolutionary intelligence Ročník 18; číslo 1; s. 9
Hlavní autori: Khezri, Edris, Rezaeipanah, Amin, Hassanzadeh, Hiwa, Majidpour, Jafar
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2025
Springer Nature B.V
Predmet:
Accuracy
Applications of Mathematics
Artificial Intelligence
Bioinformatics
Cloud computing
Control
Costs
Deep learning
Efficiency
Electrical loads
Energy consumption
Engineering
Exploitation
Genetic algorithms
Heuristic methods
Mathematical and Computational Engineering
Mechatronics
Optimization
Optimization techniques
Performance evaluation
Research Paper
Response time
Robotics
Scheduling
Statistical Physics and Dynamical Systems
Systems stability
Thermoelectricity
Workloads
Thermal power systems
Load frequency
Metaheuristics
Genetic algorithm
Open-source development model algorithm
ISSN:1864-5909, 1864-5917
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Shrnutí:Maintaining a balance between generated and consumed power is crucial for the efficient operation of interconnected power grids. This paper focuses on the issue of load frequency management in thermal power systems. We present a metaheuristic approach to address this problem, leveraging the advantages of metaheuristic algorithms in solving complex optimization problems. Our approach is based on an improved Open-source Development model algorithm (ODMA). The proposed method, referred to as ODMA-GA, integrates ODMA with a Genetic algorithm (GA) to configure a hybrid optimization technique. This combination allows for the effective exploitation and exploration of the search space, leading to high-quality solutions. We evaluate the performance of ODMA-GA using several benchmark functions with varying scenarios. The results demonstrate that ODMA-GA outperforms its peer metaheuristic algorithms, showcasing superior optimization capabilities. This promising performance suggests that ODMA-GA offers an effective solution for the challenging task of load frequency management in thermal power systems, ensuring stable and efficient operation. Specifically, the finding shows that our method improves the frequency change area and tie-line power change by 2.3% compared to the best existing method.
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ISSN:1864-5909
1864-5917
DOI:10.1007/s12065-024-00986-9