环境随机相互作用的 rime优化与纳尔德-米德简单对光伏模型的参数估计
Jinge Shi1, Yi Chen1, Ali Asghar Heidari2
1Institute of Big Data and Information Technology, Wenzhou University, Wenzhou, 325035, China.
Scientific reports
|July 8, 2024
概括
这项研究介绍了ERINMRIME,这是优化太阳能电池参数的改进算法. ERINMRIME提高了光伏模型参数计算的准确性,这对于有效的太阳能转换至关重要.
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.
- 材料科学 材料科学 材料科学
背景情况:
- 太阳能是重要的清洁能源来源,太阳能电池将阳光转化为电力.
- 对于光伏 (PV) 模型来说,准确的参数计算是必不可少的,但具有挑战性.
- 现有的优化算法可能会与局部优化和勘探效率作斗争.
研究的目的:
- 引入一个改进的 rime 优化算法 (ERINMRIME),用于精确的 PV 模型参数估计.
- 为了提高全球和本地搜索优化问题的能力.
- 评估ERINMRIME在不同条件下的各种光伏模型上的性能.
主要方法:
- 通过将Nelder-Mead简体 (NMs) 和环境随机交互 (ERI) 策略与RIME算法集成,开发了ERINMRIME.
- 将ERINMRIME应用于单二极管模型 (SDM),双二极管模型 (DDM),三二极管模型 (TDM) 和光伏模块模型.
- 将ERINMRIME的性能与原来的RIME和其他9个改进的经典算法进行了比较.
主要成果:
- 与RIME相比,ERINMRIME显著减少了SDM,DDM,TDM和PV模块模型的根平均平方误差 (RMSE),分别为46.23%,59.32%,61.49%和23.95%.
- ERINMRIME与其他九个改进的经典算法相比,表现出优越的性能.
- 该算法在商业光伏模型的不同辐射和温度条件下保持了高性能.
结论:
- ERINMRIME是一种高效和强大的算法,用于优化光伏模型参数.
- 纳米和ERI战略的整合增强了本地和全球搜索能力.
- 在太阳能电池应用中,ERINMRIME显示了准确的参数识别的巨大潜力.
相关概念视频
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
48
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
48
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
454
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
454
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
68
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
68
Parametric Survival Analysis: Weibull and Exponential Methods
406
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
406
Pharmacokinetic Models: Comparison and Selection Criterion
66
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
66
Calibration Curves: Linear Least Squares
1.3K
A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
For data that follow a straight line, the standard method for fitting is the linear...
1.3K


