عنوان
پدید آورنده
موضوع
رده
کتابخانه
محل استقرار
شماره کتابشناسی ملی
شماره
TL48670
زبان اثر
زبان متن نوشتاري يا گفتاري و مانند آن
انگلیسی
عنوان و نام پديدآور
عنوان اصلي
Controller parameter optimization for photovoltaic system using metaheuristic algorithm
نام عام مواد
[Thesis]
نام نخستين پديدآور
Rahila Naseeha Abul Kalaam
نام ساير پديدآوران
Muyeen, S. M.
وضعیت نشر و پخش و غیره
نام ناشر، پخش کننده و غيره
The Petroleum Institute (United Arab Emirates)
تاریخ نشرو بخش و غیره
2015
مشخصات ظاهری
نام خاص و کميت اثر
133
يادداشت کلی
متن يادداشت
Committee members: Al Durra, Ahmed; Al Sayari, Naji; Beig, Abdul Rahiman; Harid, Noureddine
یادداشتهای مربوط به نشر، بخش و غیره
متن يادداشت
Place of publication: United States, Ann Arbor; ISBN=978-1-339-52784-0
یادداشتهای مربوط به پایان نامه ها
جزئيات پايان نامه و نوع درجه آن
M.S.
نظم درجات
Electrical Engineering
کسي که مدرک را اعطا کرده
The Petroleum Institute (United Arab Emirates)
امتياز متن
2015
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
In recent years, the demand of renewable energy is rising rapidly, especially on photovoltaic (PV) power. The grid integration issues of photovoltaic power should be handled carefully. In grid-connected PV system, grid-tied inverter plays an important role in normal and fault ride-through operations. The cascaded control is widely used for controlling the grid tied-inverter. The tuning of four PI controllers in cascaded control of grid-tied PV inverter along with another PI controller in maximizing output power is very cumbersome when the system is difficult to express in terms of a mathematical model due to the system nonlinearity. In this thesis, an attempt is made to design the parameters of all PI controllers of a grid-tied PV system which works well in different types of grid-fault conditions. Utilizing two metaheuristic algorithms namely Bacteria Foraging Optimization (BFO) and Cuckoo Search (CS), the complete optimization process is splitted into two phases: the first part is designing the cost function and for this purpose initially Response Surface Methodology (RSM) is used. RSM is a statistical tool which helps to give a response between variables and factors. The cost function from RSM is the response recovery time after a fault. As RSM has its own limitations of high computational time and statistical behavior in this study RSM is replaced later by Artificial Neural Network (ANN) to derive the cost function. Another reason of using ANN is to reduce the number of design experiments required to develop the fitness function. The second part of the study is to apply BFO & CS to the cost function to minimize the fault recovery time. An extensive comparative study is done for RSM-BFO, ANN-BFO, RSM-CS, and ANN-CS. The optimization results obtained from proposed methods are also compared with standard genetic algorithm. The PV panel, boost converter, inverter, and distribution system along with the controllers are modeled using PSCAD/EMTDC. Transient performance of the PI controllers with optimum design values is evaluated under different symmetrical and unsymmetrical grid fault conditions. Finally, the best optimization method is recommended for grid-tied PV system.
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Alternative Energy; Electrical engineering
اصطلاحهای موضوعی کنترل نشده
اصطلاح موضوعی
Applied sciences;Bacteria foraging optimization algorithm;Controller parameter optimization;Cuckoo search algorithm;Photovoltaic system
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )
مستند نام اشخاص تاييد نشده
Al Jahwari, Dawood Sulaiman
نام شخص - ( مسئولیت معنوی درجه دوم )
مستند نام اشخاص تاييد نشده
Muyeen, S. M.
شناسه افزوده (تنالگان)
تقسيم فرعي
Electrical Engineering
مستند نام تنالگان تاييد نشده
The Petroleum Institute (United Arab Emirates)
شماره دستیابی
شماره بازیابی
1771907949; 10027586
دسترسی و محل الکترونیکی
نام الکترونيکي
مطالعه متن کتاب وضعیت انتشار
فرمت انتشار
p
اطلاعات رکورد کتابشناسی
نوع ماده
[Thesis]
کد کاربرگه
276903
اطلاعات دسترسی رکورد
سطح دسترسي
a
تكميل شده
Y
