使用动态多维随机机制和纳尔德-米德简单的光伏参数估计的RIME优化
Yuanping Zheng1, Fangjun Kuang2,3, Ali Asghar Heidari4
1Department of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, 325035, China.
一个新的DNMRIME算法增强了太阳能光伏的参数提取. 与其他14个算法相比,它表现出卓越的性能,在现实条件下提高了准确性和效率.
科学领域:
- 可再生能源工程可再生能源工程
- 计算智能是一种计算智能.
- 优化算法 优化算法
背景情况:
- 提取太阳能光伏电池参数至关重要,但由于各种影响因素而复杂.
- 听算法 (MAs) 提供了潜在的解决方案,但为了提高准确性和融合性,需要进行改进.
研究的目的:
- 引入一个称为DNMRIME的增强的Rime优化算法 (RIME),用于改进光伏参数提取.
- 评估DNMRIME在太阳能应用中的性能和实际应用.
主要方法:
- 通过将动态多维随机机制 (DMRM) 与Nelder-Mead简单 (NMs) 方法集成,开发了DNMRIME.
- 对CEC 2017基准函数进行了定性分析和废除研究.
- 用威尔科克森签名等级测试将DNMRIME与14个已建立的MA进行比较.
主要成果:
- DNMRIME表现出卓越的性能,在14个比较的MA中排名第一.
- 在单,双和三重二极管模型中实现了低的根平均平方误差 (RMSE) 值.
- 在不同的环境条件下成功提取参数,模拟数据与实际数据密切匹配.
结论:
- 结合了DMRM和NM的DNMRIME,在融合精度和优化能力方面提供了显著的改进.
- 该算法被证明是光伏参数提取的高效和实用,优于现有方法.
- 强调DNMRIME在推进太阳能技术方面的潜在价值.
更多相关视频
10:36Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
Published on: November 3, 2023
14:01Making Record-efficiency SnS Solar Cells by Thermal Evaporation and Atomic Layer Deposition
Published on: May 22, 2015
相关概念视频
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Maxwell-Boltzmann Distribution: Problem Solving
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
Response Surface Methodology
The process of RSM involves several key steps:
Ampere-Maxwell's Law: Problem-Solving
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...
Fast Decoupled and DC Powerflow
