ارزیابی وجود رزونانس در تخصیص بهینه بانک‌های خازنی در شبکه‌های توزیع بر مبنای الگوریتم بهینه‌سازی MSPS
محورهای موضوعی : مهندسی برق و کامپیوتر
مسعود ايوبي
1
(دانشگاه اصفهان)
رحمت‌الله هوشمند
2
(دانشگاه اصفهان)
مهدی ترابيان اصفهاني
3
(دانشگاه اشرفي اصفهاني)
کلید واژه: الگوريتم MSPSOجايابي خازن‌هارزونانسفازی‌سازیهارمونيک,
چکیده مقاله :
یکی از مهم‌ترین مشکلات موجود در شبکه‌های قدرت، وجود رزونانس در نقاطی از شبکه می‌باشد که باعث افزایش ناخواسته ولتاژ و جریان و بروز خسارت به تجهیزات مي‌شود. با توجه به این که با نصب بانک خازنی در شبکه، مشخصه فرکانسی سیستم تغییر کرده و امکان رزونانس افزایش می‌آید، لازم است این نکته در تخصیص خازن‌ها در شبکه در نظر گرفته شود. در اين مقاله، شاخص جدیدی برای ارزیابی وجود رزونانس ارائه شده و با استفاده از شاخص رزونانس پیشنهادی، روش جديدي براي جايابي بهینه خازن‌ها در محيط هارمونيکي ارائه مي‌شود. در روش پیشنهادی، ابتدا از آناليز حساسيت استفاده شده تا شینه‌هايي که بيشترين تأثير را بر تلفات و افت ولتاژ شبکه دارند، کانديد خازن‌گذاري شوند. پس از آن، خازن‌گذاري بر اساس سطوح بار مختلف و با استفاده از تابع شايستگي معرفي‌شده انجام مي‌شود. در تابع شايستگي، از توابع عضويت فازي مربوط به صرفه‌جويي اقتصادي، انحراف ولتاژ، THD و قيد رزونانس استفاده شده است. روش پيشنهادي با الگوريتم MSPSO، در شبکه 18شینه IEEE پياده‌سازي شده است. نتايج به دست آمده، کارامدي اين روش را در مقايسه با روش‌هاي ديگر نشان مي‌دهد.
One of the most important problems in power networks is the presence of resonance at some of the buses which leads to an unwanted increase in voltage and current and damage to equipment. Since with installing a capacitor bank in the network, frequency characteristic of the system is changed and resonance is increased, it is necessary to consider this point in allocation of capacitors in the network. In this paper, a new index for evaluating the resonance is presented. Applying the proposed resonance index, a new two-step method for optimal placement of capacitors in a harmonic system is provided. In the first step, a sensitivity analysis is used, then in the second step, the objective function considering technical constraints is optimized using a fuzzy technique. The proposed method is implemented with the MSPSO algorithm on the IEEE 18-bus network. The results show the efficiency of this method in comparison with other methods.
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