کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5450796 1513068 2017 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A meta-heuristic firefly algorithm based smart control strategy and analysis of a grid connected hybrid photovoltaic/wind distributed generation system
ترجمه فارسی عنوان
یک الگوریتم کنترل هوشمند مبتنی بر الگوریتم فراشناختی و تجزیه و تحلیل یک سیستم نسل توزیع شده فتوولتائیک / باد ترکیبی متصل به شبکه
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
Dynamic model for the main system components, namely, wind energy conversion system (WECS), PV energy conversion system (PVECS) and control for PVECS and the power electronics devices are addressed in this paper. The overall control strategy for grid connected hybrid wind/PV distributed generation system has also been presented. Different energy sources in the system are integrated through a DC bus into the utility grid. Based on the dynamic component models, a simulation model for the hybrid distributed generation system connected with utility grid has been developed using MATLAB/Simulink. Hybrid system comprises of Wind Turbine (WT) and solar Photovoltaic (SPV). For control the voltage and frequency at PCC Firefly based controller is used. Performance of several controllers such as Proportional Integral (PI), and Proportional Integral Derivatives (PID) are evaluated to control the frequency of the system. The controller gains are simultaneously optimized by powerful meta-heuristic firefly algorithm. Comparison of the dynamic responses reveals better performance of the PID controller. Here, it has been observed that the values of gain designed by firefly algorithm are robust which is verified and validated by case studies. Investigations reveal that the FA is successfully applied for simulation studies and it has been carried out to verify the controller and system performance under different scenarios which reveals that overall control strategy are robust and perform well.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Solar Energy - Volume 150, 1 July 2017, Pages 265-274
نویسندگان
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