基于先进的软计算优化技术,增强了PVWPS的操作
Mahmoud M Elymany1, Mohamed A Enany2, Hamid Metwally1
1Electrical Power and Machines Department, Faculty of Engineering, Zagazig University, Zagazig, 44519, Egypt.
Scientific reports
|November 28, 2024
概括
三个软计算算法,大猩猩部队,蜂蜜和蛇,增强光伏水系统. 这些方法优化了功率输出和效率,优于传统控制.
科学领域:
- 可再生能源系统可再生能源系统
- 软件计算应用程序 软件计算应用
- 优化算法 优化算法
背景情况:
- 光伏水系统 (PVWPS) 需要高效的优化以获得最大的性能.
- 像扰动和观察 (P&O) 和增量导电 (IC) 这样的传统控制方法在PVWPS效率方面存在局限性.
研究的目的:
- 介绍和评估三种软计算 (SC) 优化算法:大猩猩部队算法 (GTO),蜂蜜虫算法 (HBA) 和蛇算法 (SAO) 对于PVWPS.
- 通过最大限度地提高光伏阵列输出功率 (PPV) 和直流电机效率 (η) 来提高PVWPS的效率,从而优化水流速 (Q).
主要方法:
- 开发用于PVWPS的SC优化算法 (GTO,HBA,SAO).
- 分析建模用于预测考虑太阳辐射 (G) 和环境温度 (T) 的buck-boost转换器的最佳工作周期 (Dop).
- 适应性神经模糊推理系统 (ANFIS) 的 MATLAB 模拟,为拟议的系统进行训练.
主要成果:
- 在使用SC优化器的分析模型和模拟模型之间观察到强烈的趋同.
- 神经模糊系统与SC优化器相结合,比P&O和IC方法表现出更高的性能.
- 在发动机效率 (η),光伏输出功率 (PPV),水流率 (Q) 和响应时间方面注意到了显著的改进.
结论:
- 提出的SC优化算法 (GTO,HBA,SAO) 有效地提高了PVWPS的性能.
- 与SC优化器集成ANFIS为PVWPS提供了优越的控制策略,与传统方法相比.
- 这项研究验证了先进软计算技术在优化可再生能源系统中的有效性.
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