نوع مقاله : مقاله پژوهشی - کاربردی

نویسندگان

1 گروه مهندسی برق، موسسه آموزش عالی آیندگان، تنکابن، ایران

2 مرکز آموزش عالی سما سیاهکل ، دانشگاه آزاداسلامی واحد لاهیجان

چکیده

   هدف از برنامه‌ریزی توسعه شبکه انتقال (TEP)، یافتن خطوط موردنیاز شبکه با کمترین هزینه سرمایه‌گذاری است؛ بطوریکه با رعایت شاخص‌هایی امنیتی سیستم، بار آینده به شکلی اقتصادی تامین گردد. با توجه به عدم قطعیت بار، تولیدات پراکنده بادی، منابع پاسخگو به بار و رقابتی شدن بازار برنامه‌ریزی توسعه شبکه انتقال با چالش‌هایی مواجه شده است که ازاین‌رو نیاز به ارائه مدل‌های جدید، بیش از پیش احساس می‌گردد. در این مقاله یک مدل TEP چندهدفه با در نظرگیری هزینه‌های سرمایه‌گذاری، عملکرد و منابع پاسخگو به بار به همراه یک شاخص جهت تعیین امنیت سیستم ارائه می‌شود. این توابع هدف، برای به دست آوردن یک مجموعه راه‌حل‌های غیر غالب، بر اساس اولویت‌های اپراتور(هزینه یا ریسک)، با استفاده از الگوریتم تکاملی قدرت پارتو مبتنی بر روش بهینه‌سازی چندهدفه اجتماع ذرات (SPEA2-MOPSO) بهینه می‌گردند. نتایج این تحقیق بر روی شبکه 24 باسه IEEE-RTS آزمایش گردیده است و روش پیشنهاد با روش‌های MOPSO و MOEA/D مقایسه می‌شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Multi-Purpose Transmission expansion planning in Smart Grids Considering the resources responsible for load and security of the system

نویسندگان [English]

  • Mohammad Saberi 1
  • Mehdi Hatef 2

1 Department of Electrical Engineering, Ayandegan Institute of Higher Education, Iran

2 Sama Siyahkal vocational training center, Islamic Azad University, Lahijan branch, Siahkal, Iran

چکیده [English]

The purpose of Transmission expansion planning (TEP) is to find the required network lines with the lowest investment cost So that the future burden will be provided economically by observing the system security indicators. Due to the uncertainty of the load, Distributed wind power and Responsive resources to load and competitive markets for Transmission expansion planning, Faced with challenges that require new models to be felt more than ever. In this paper, a multi-objective TEP model is presented taking into account investment costs, Responsive resources to load, along with an index for determining system security. These target functions are optimized for obtaining a non-dominant solution set based on operator priorities (cost or risk), using pareto power evolutionary algorithms based on multi-objective particle pool optimization (SPEA2-MOPSO). The proposed model is numerically verified on the modified IEEE RTS 24- bus and 118-bus systems. According to the simulation results, the proposed model can provide information regarding variants of risks and coordinate the optimum planning and DR solutions.

کلیدواژه‌ها [English]

  • Transmission expansion planning
  • Responsive resources to load
  • multi-objective evolutionary algorithm
  • Wind farms
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