RIME optimization with dynamic multi-dimensional random mechanism and Nelder-Mead simplex for photovoltaic parameter
Yuanping Zheng1, Fangjun Kuang2,3, Ali Asghar Heidari4
1Department of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, 325035, China.
A new DNMRIME algorithm enhances solar photovoltaic parameter extraction. It shows superior performance compared to 14 other algorithms, improving accuracy and efficiency in real-world conditions.
Area of Science:
- Renewable Energy Engineering
- Computational Intelligence
- Optimization Algorithms
Background:
- Extracting solar photovoltaic cell parameters is crucial but complex due to various influencing factors.
- Metaheuristic algorithms (MAs) offer potential solutions, but enhancements are needed for improved accuracy and convergence.
Purpose of the Study:
- To introduce an enhanced Rime Optimization Algorithm (RIME) called DNMRIME for improved photovoltaic parameter extraction.
- To evaluate the performance and practical applicability of DNMRIME in solar energy applications.
Main Methods:
- Developed DNMRIME by integrating the dynamic multi-dimensional random mechanism (DMRM) with the Nelder-Mead simplex (NMs) method.
- Conducted qualitative analysis and ablation studies on CEC 2017 benchmark functions.
- Compared DNMRIME against 14 established MAs using Wilcoxon signed rank test.
Main Results:
- DNMRIME demonstrated superior performance, ranking first among 14 compared MAs.
- Achieved low Root Mean Square Error (RMSE) values for single, double, and triple diode models.
- Successfully extracted parameters under varying environmental conditions, with simulation data closely matching actual data.
Conclusions:
- DNMRIME, incorporating DMRM and NMs, offers significant improvements in convergence accuracy and optimization capabilities.
- The algorithm proves efficient and practical for photovoltaic parameter extraction, outperforming existing methods.
- Highlights the potential value of DNMRIME for advancing solar energy technology.
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