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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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A novel hybrid algorithm based on improved marine predators algorithm and equilibrium optimizer for parameter
Ziyuan Liang1, Zhenlei Wang2,1, Ali Wagdy Mohamed3
1Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China.
Heliyon
|October 17, 2024
Summary
A new hybrid algorithm, IMPAEO, enhances solar photovoltaic (PV) model parameter extraction. This method improves accuracy and reliability for PV system simulations, offering a better alternative for researchers.
Area of Science:
- Renewable Energy Systems
- Computational Intelligence
- Electrical Engineering
Background:
- Accurate parameter extraction is vital for solar photovoltaic (PV) system simulation and control.
- Existing optimization algorithms often lack the required accuracy and reliability for PV model parameter extraction.
- Shortcomings in current methods necessitate the development of more robust and efficient parameter extraction techniques.
Purpose of the Study:
- To propose a novel hybrid optimization algorithm, IMPAEO, for enhanced parameter extraction in solar PV systems.
- To improve the accuracy, reliability, and convergence speed of parameter extraction for PV models.
- To provide a more effective alternative to existing methods for PV system analysis and evaluation.
Main Methods:
- Developed the Improved Marine Predators Algorithm with Equilibrium Optimizer (IMPAEO) by integrating elite opposition-based learning, adaptive weight coefficients, and EO operator.
- Incorporated the Linear Population Size Reduction (LPSR) technique to dynamically optimize population size and enhance search performance.
- Validated the IMPAEO algorithm using the CEC2017 benchmark test suite and applied it to extract parameters for single diode, double diode, and various PV modules.
Main Results:
- The IMPAEO algorithm demonstrated superior performance compared to other algorithms in terms of solution quality and convergence speed.
- Comparative analysis confirmed significant advantages of IMPAEO in algorithm stability for PV model parameter extraction.
- Validation on benchmark functions and diverse PV models confirmed the effectiveness and reliability of the proposed IMPAEO.
Conclusions:
- The proposed IMPAEO algorithm is an efficient and reliable method for parameter extraction in solar PV models.
- IMPAEO offers a promising alternative for researchers and engineers working with solar PV systems.
- The hybrid approach effectively balances global exploration and local exploitation, leading to improved solution quality and faster convergence.
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