روش نوین مدل‌سازی و پاسخ‌یابی بهینه مطلق برنامه‌ریزی توسعه شبکه انتقال با لحاظ شرایط پیشامد
محورهای موضوعی : مهندسی برق و کامپیوترابوالفضل ناطقی 1 , حسین سیفی 2 * , محمدکاظم شیخ‌الاسلامی 3 , محمدصادق سپاسیان 4
1 - دانشگاه تربیت مدرس
2 - دانشگاه تربیت مدرس
3 - دانشگاه تربیت مدرس
4 - دانشگاه شهید بهشتی
کلید واژه: روش‌های مدل‌سازی MILP MINLP و NLP وقوع پیشامد روش حل BARON,
چکیده مقاله :
برنامه‌ریزی توسعه شبکه انتقال، یکی از مهم‌ترین بخش‌های برنامه‌ریزی توسعه شبکه برق می‌باشد. تا کنون روش‌های مختلفی جهت انجام این برنامه‌ریزی مورد استفاده قرار گرفته‌اند تا بتوانند بهترین حالت توسعه شبکه انتقال را ارائه دهند. در این مقاله، روش‌های برنامه‌ریزی خطی ترکیبی عدد- صحیح (MILP) و برنامه‌ریزی غیر خطی ترکیبی عدد- صحیح (MINLP) جهت انجام مطالعات برنامه‌ریزی توسعه شبکه انتقال مورد استفاده قرار گرفته و روش جدید برنامه‌ریزی غیر خطی (NLP) با حذف عدد صحیح به‌عنوان روشی جدید معرفی گشته است. همچنین در انجام مسأله برنامه‌ریزی، حالات مختلف وقوع پیشامد نیز در حل مسأله وارد شده است كه در مطالعات گذشته، اين مهم صورت نگرفته بود. برای حل مسأله، ترکیب‌های مختلفی از توابع هدف شامل هزینه توسعه، هزینه بهره‌برداری و هزینه تلفات مورد توجه قرار گرفته و نتایج حالات مختلف با یکدیگر مقایسه شده‌اند. برای بررسی امکان دسترسی به نقطه بهینه مطلق در مسأله حاضر، روش حل BARON به‌عنوان روش حل مناسب مورد استفاده قرار گرفته است. روش‌های ارائه‌شده بر روی شبکه نمونه 6شینه گارور و شبکه 118شینه IEEE اعمال شده است. نتایج به‌دست آمده، نشان‌دهنده امکان دسترسی به نقطه بهینه مطلق با دقت و سرعت بالا با استفاده از روش‌های مدل‌سازی MINLP و NLP است. همچنین مشاهده می‌شود که با در نظرگیری حالات وقوع پیشامد، نتایج توسعه شبکه، دقیق‌تر و صحیح‌تر خواهد بود.
ts cause different neural responses containing a regular firing, or a long latency before firing with or without a leading spike. In this paper, the firing behavior of DCN pyramidal cells is simulated first Transmission Expansion Planning (TEP) is an important issue of power system planning studies. In literature, different methods are investigated to achieve good solutions for TEP. This paper uses Mixed Integer Linear Programming (MILP) and Mixed Integer Nonlinear Programming (MINLP) methods to study TEP. It also presents a new NLP model in which the integer variables are omitted. Moreover, the models are properly modified so that contingency conditions are also observed. Different combinations of cost functions such as the expansion cost, the operation cost and the cost of the losses are considered and compared. To reach a global optimum solution, BARON solver is applied. The proposed algorithm is applied on Garver 6-bus and IEEE-118 bus test systems. It is shown that modeling the problem by MINLP and NLP methods, in combination with a proper solver, can result in a quick optimum solution.
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