طراحی همزمان پارامترهای PSS و SVC با استفاده از روش کوانتوم بهبود یافته جهت ارتقای پایداری سیستم قدرت چند ماشینه
محورهای موضوعی : انرژی های تجدیدپذیرامیر کاظمی زهرانی 1 , معین پرستگاری 2
1 - کارشناس ارشد - دانشکده فنی مهندسی، واحد خمینیشهر، دانشگاه آزاد اسلامی، خمینیشهر، ایران
2 - گروه بازار برق،پرشین دانش،اصفهان،ایران
کلید واژه: پایداری, SVC, الگوریتم تکاملی کوانتوم, PSS,
چکیده مقاله :
امروزه با توجه به اهمیت ارتقای عملکرد سیستم قدرت از دیدگاه کیفیت توان و پایداری استفاده از ادوات FACTS در شبکه های قدرت، و هماهنگ سازی این ادوات با پایدار سازهای سیستم قدرت مورد توجه قرار گرفته است. با توجه به این مسأله، در این مقاله مسأله طراحی هماهنگ پارامترهای PSS و SVC در سیستم های قدرت چند ماشینه معرفی گردیده و با روش کوانتوم حل گردیده است. با وجود این که PSS برای میراسازی نوسانات سیگنال کوچک سیستم قدرت طراحی می شود، این وسیله برای میراسازی نوسانات سیگنال بزرگ باید با سایر تجهیزات از جمله SVC به صورت هماهنگ طراحی می شود. لذا برای پایداری بهتر سیستم قدرت در این مقاله پارامترهای PSS و SVC به صورت هماهنگ با استفاده از الگوریتم QEA به دست آمده است. روش بین ارائه شده برای تععین پارامترهای PSS و SVC بر روی سیستم های چهار ماشینه کندور و 39 باس NEW ENGLAND تعیین گردیده است. نتایج شبیه سازی مؤید برتری روش پیشنهادی نسبت به روش های الگوریتم بهینه ساری ازدحام ذرات و الگویتم بهینه سازی غذایابی باکتریا می باشد.
As to the importance of power system performance in terms of quality, and stability, through flexible AC transmission system (FACTS) devices in power networks and coordinating these devices through power system stabilizers (PSSs) has gained a great acceptance. Accordingly, the problem of coordinated design of PSS and static var compensator (SVC) parameters in multi-machine power systems is introduced and solved through the improved quantum method. In previous studies PSS is designed for damping small-signal oscillations of the power system. To damp large-signal oscillations, PSS should be designed in accordance with other devices like SVC. Therefore to reach overall stability of power system, the Quantum-inspired Evolutionary Algorithm is applied here to determine PSS parameters and SVC in a coordinated manner. This proposed method is applied in determining PSS parameters and SVC of Kundur’s four-machine power systems and the New England 39-bus system. Simulation results reveal the effective performance of this proposed method in comparison with Particle Swarm Optimization (PSO) and Bacteria Foraging Optimization (BFO) methods.
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