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تحليل الاضطراب لتوربينة الرياح المربوطة مع منظومة القدرة == Disturbance Analysis of A Wind Turbine Connected With Power System
اسم المؤلف:
احمد نجم عبد الامير
اسم المشرف:
كنعان علي جلال
الموضوع العام:
هندسة الكهرباء والالكترون والاتصالات
السنة:
2014
الموضوع الدقيق:
هندسة الكهرباء - قدرة ومكائن
الدرجة:
ماجستير
الجامعة:
الجامعة التكنولوجية - قسم الهندسة الكهربائية
اللغة:
الانكليزية
مكان الجامعة:
بغداد
الصفحات الاولى:
📎 34T497 - p.pdf
المستخلص:
نظرا لزيادة الطلب على الطاقة في السنوات الاخيرة نتيجة للتوسع السكاني والصناعي ولتقليل التلوث الناتج من الوقود التقليدي والحفاظ على البيئة مما دعت الحاجة الى استخدام مصادر بديلة للطاقة, والتي يجب ان تمتاز بعدة ميزات اهمها انها صديقة للبيئة وغير قابلة للنفا | According to increasing the demand for energy in recent years as a result of the expansion of the population and to reduce pollution from conventional fuels, the need arises to find alternative sources of energy which must be characterized by several features, most important of which is friendly to the environment and sustainable. In this work, the effect of different types of disturbances on the performance of fixed speed of wind turbine generator type Squirrel Cage Induction Generator (SCIG) connected to the power system has been investigated, because it has features which make the best choice in some cases, despite the less efficiency compared with other types of generators. Also, this work aims to study and analysis the effect of (STATCOM) on the wind turbine generators because of its advantages in improving voltage stability of the grid and improving the quality of the productive power. The proposed work is performed using MATLAB/Simulink. The intelligent systems have been used to obtain the best performance in terms of extracting more power from wind energy as well as increase the stability of system in situations of disturbances and the results obtained have been compared with conventional control systems.Three types of controllers are proposed in this work; the first controller is the Proportional - Integral (PI) based on classical trial and error method, the second controller is PI - controller based on Particle Swarm Optimization (PSO) technique for optimal tuning (gain) to improve the performance of the system. The results obtained proved that the PI - controller based on Particle Swarm Optimization (PSO) technique is better than based on trial and error method. The third controller is (Nonlinear Auto regressive - Moving Average) NARMA - L2 based on (PSO). Finally, the results of the proposed controllers show that NARMA - L2 controller is more effective on the stabilization and improves the performance of the system compared with PI - PSO controller
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