جبران‌سازي بهينه و همزمان توان‌هاي اكتيو و راكتيو در سيستمهاي قدرت با استفاده از خودروهاي برقي متصل به شبكه
محورهای موضوعی : مهندسی برق و کامپیوتر
فرزان رشیدی
1
(دانشگاه هرمزگان)
حسن فشکي فراهاني
2
(دانشگاه آزاد اسلامي واحد آشتیان)
کلید واژه: الگوريتم بهينه‌سازي اجتماع ذرات جبران‌سازي توان راكتيو خودروهاي برقی قابل اتصال به شبکه,
چکیده مقاله :
خودروهاي برقی قابل اتصال به شبکه در كنار مسئله كاهش آلودگي، داراي قابليت‌هايي براي كمك‌رساني به سيستمهاي قدرت مي‌باشند. يکي از مهم‌ترين اين قابليت‌ها پاسخگويي به نياز شبکه جهت توليد توان‌هاي اکتيو و راکتيو است. در اين مقاله با توجه به قيود شبکه، ملاحظات فني و قيمت‌هاي پيشنهادي بازار، يک چارچوب نظري جهت اختصاص ظرفيت اين خودروها ارائه شده است. بدين منظور تابع هدفي با رويکرد حداقل‌سازي هزينه‌هاي پرداختي توسط بهره‌بردار مستقل شبکه توزيع يا DSO به توليدکنندگان هر يک از توان‌هاي اکتيو و راکتيو پيشنهاد شده است. با توجه به اين که مسأله مورد نظر در قالب يک مسأله بهينه‌سازي است، براي حل آن نيز از الگوريتم بهينه‌سازي اجتماع ذرات استفاده شده است. همچنين به منظور تسريع در فرايند بهينه‌سازي و جلوگيري از گيرافتادن الگوريتم در بهينه‌هاي محلي، راهکارهاي ابتکاري جديدي به الگوريتم اضافه شده است. در اين قالب پيشنهادي، خودروها براي توليد توان‌هاي اکتيو و راکتيو با ژنراتور رقابت مي‌کنند. کارایي روش پيشنهادي بر روي يک فيدر شبکه ولتاژ پايين با 134 مشترک و با حضور منابع توليد توان‌هاي اکتيو و راکتيو مورد ارزيابي قرار گرفته و ميزان توليد و هزينه‌هاي پرداختي براي هر يک از توليدکنندگان تعيين شده است
Plug in electric vehicles besides environment pollution reduction can help power system operation. One of the most important capabilities of them is providing activeand reactive power. This paper considers grid constraints, technical concerns and market price and proposes a framework to allocate the PEV capacity such that operational cost paid by distribution system operator (DSO) to power provider of active and reactive power is minimized. For this purpose, an objective function is defined that includes the payment for each power provider. This objective function is minimized based on particle swarm optimization subject to grid and vehicles constraints. In this framework, the PEVs compete with generator to produce active and reactive power. In order to accelerate the optimization process and prevent the algorithm from being trapped in local optima, new heuristic approaches are included to the original PSO algorithm. To evaluate the effectiveness of the propose method, it is implemented on the low voltage with 134 customer and including the other power providers and the amount of each participants production and payment cost to each component is determined.
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