استفاده از مدل وینر-همرشتاین بهینه شده با الگوریتم ژنتیک در شناسایی سیستم فتوولتائیک
ایمان سهرابی مقدم چافجیری
1
(
دانشکده فنی و مهندسی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران
)
علیرضا آزادبر
2
(
دانشکده مهندسی هسته ای، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران
)
عباس قدیمی
3
(
دانشکده فنی و مهندسی، دانشگاه آزاد اسلامی واحد لاهیجان ، لاهیجان ، ایران
)
سید جواد موسوی
4
(
دانشکده فیزیک، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران
)
کلید واژه: شناسایی سیستم, مدل وینر-همرشتاین, سیستم فتوولتائیک, الگوریتم ژنتیک.,
چکیده مقاله :
شناسایی سیستم روشی برای شناسایی یا اندازه‌گیری مدل ریاضی یک سیستم با اندازه‌گیری ورودی‌ها و خروجی‌های سیستم است. در این مقاله رویکرد الگوریتم ژنتیک (GA) را برای مدل‌سازی سیستم‌های فتوولتائیک (PV) با ساختار وینر-هامرشتاین اعمال می‌کنیم. سیستم‌های دینامیکی غیرخطی دارای هر دو عنصر پویا (عناصر ذخیره انرژی) هستند و در این نوع سیستم‌ها بین برخی از متغیرها روابط غیرخطی وجود دارد. اگر در چنین سیستم هایی بتوان فرض کرد که قطعات دینامیکی و قطعات غیرخطی قابل تفکیک هستند، می توان آنها را با ساختارهای مدل های بلوک گرا مدل کرد. این نوع مدل ها از ترکیب بلوک(های) دینامیکی خطی و بلوک(های) غیرخطی استاتیکی تشکیل شده اند. این رویکرد به تخمین یک سیستم فتوولتائیک (PV) بر اساس داده‌های مشاهده‌شده مربوط می‌شود. ورودی و خروجی غیرخطی به ترتیب از داده های تابش و جریان خروجی DC سیستم واقعی گرفته شده است. نتایج شبیه‌سازی اثربخشی و استحکام مدل پیشنهادی را با استفاده از الگوریتم ژنتیک نشان داد. نتایج شبیه سازی مقدار MSE 0.000774 را برای عملکرد عادی سیستم PV و 0.009863 را برای اثر سایه بین نرخ اطلاعات تخمینی و مرجع نشان می دهد.
چکیده انگلیسی :
System identification is a method of identification or measuring a mathematical model of a system by measuring the inputs and outputs of the system. In this paper we apply the Genetic Algorithm (GA) approach to model a photovoltaic (PV) systems with a Wiener-Hammerstein structure. Non-linear dynamic systems have both dynamic elements (energy storage elements) and in these types of systems there are non-linear relationships between some variables. If in such systems it can be assumed that dynamic parts and non-linear parts are separable, they can be modeled with the structures of block-oriented models. These types of models are composed of a combination of linear dynamic block(s) and static nonlinear block(s). This approach is concerned with the estimation of a photovoltaic (PV) system based on observed data. The nonlinear input and output are taken from the irradiance and DC output current data of the real system, respectively. The simulation results revealed the effectiveness and robustness of the proposed model using a genetic algorithm. The simulation results show an MSE value of 0.000774 for normal operation of the PV system and 0.009863 for the shading effect between the estimated and reference information rates.
شناسایی سیستم فتوولتائیک در شرایط عملیاتی نرمال و سایه
استفاده از مدل بلوکگرا
استفاده از مدل وینر- همرشتاین بهینه شده با الگوریتم ژنتیک
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