کنترل و مدیریت زمان واقعی ریزشبکه با منابع تولید پراکنده و با استفاده از مدل جامع پیل سوختی غشای تبادل پروتون

نوع مقاله : علمی-پژوهشی

نویسندگان

1 دانشجوی دکتری تخصصی، دانشکده مهندسی برق و کامپیوتر، دانشگاه تبریز، تبریز، ایران

2 استاد، دانشکده مهندسی برق و کامپیوتر، دانشگاه تبریز، تبریز، ایران

چکیده

در این مقاله، یک روش کنترلی زمان واقعی برای کنترل و مدیریت ریزشبکه‌ی متصل به شبکه دارای پیل سوختی، پنل‌های فتوولتائیک به عنوان منابع پراکنده و باتری (سیستم ذخیره‌سازی انرژی) پیشنهاد شده است. این روش کنترلی بر اساس کنترل پیش‌بین مبتنی بر مدل، مدلسازی شده و از الگوریتم بهینه‌سازی ازدحام ذرات برای بهینه‌سازی استفاده شده است. کنترل پیش‌بین امکان استفاده از داده‌های بدست آمده بر اساس شبیه‌سازی عملکرد ریزشبکه به عنوان داده‌های پیش‌بینی شده در هر نمونه را فراهم می‌کند. با استفاده از این داده‌های پیش‌بینی شده و داده‌های دریافتی از اندازه‌گیری‌های لحظه‌ای، کنترل ریزشبکه به صورت زمان واقعی انجام می‌شود. هدف از این روش، کنترل و مدیریت یکپارچه ریزشبکه، کاهش تغییرات در وضعیت شارژ باتری و سطح هیدروژن پیل سوختی است که باعث کاهش استفاده بی‌رویه از باتری و پیل سوختی و استهلاک باتری و پیل سوختی می‌شود. همچنین، استفاده از توان الکتریکی تولیدی توسط منابع تولید پراکنده و پیل سوختی با هدف کاهش خرید انرژی الکتریکی از شبکه اصلی و استفاده از باتری برای کاهش نوسانات در توان پیل سوختی می‌باشد که در نتایج شبیه‌سازی این اهداف بررسی شده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Real-time Control and Management of a Microgrid, with Dispersed Generation Resources, Utilizing a Integrated Proton Exchange Membrane Fuel Cell Model

نویسندگان [English]

  • S. Roudnil 1
  • S. Ghassem Zadeh 2
1 Electrical and Computer Engineering Faculty - Power Department, University of Tabriz, Tabriz, Iran.
2 Electrical and Computer Engineering Faculty - Power Department, University of Tabriz, Tabriz, Iran.
چکیده [English]

In this paper, a real-time control method is proposed for the energy management of a grid-connected microgrid including fuel cell, photovoltaic panels (PV) as distributed energy resources (DERs), and battery as energy storage system (ESS). The control method is based on model predictive control (MPC) and optimized using the particle swarm optimization (PSO) algorithm. By modeling the control method, predictive data obtained from simulating microgrid performance at each instance are utilized. Real-time microgrid control is then performed by combining these predicted data with real-time measurements. The purpose of this control method is to achieve integrated management of the microgrid and reduce changes in the battery’s state of charge (SoC) and fuel cell’s level of hydrogen (LoH). This reduction helps minimize excessive usage of the battery and fuel cell, thus reducing their depreciation. Moreover, the proposed control method enables PV and fuel cell to supply most of the required demand, with excess electric power being sold to the main grid. Additionally, the battery functions to absorbs power fluctuations, as demonstrated in the simulation results investigating these objectives.

کلیدواژه‌ها [English]

  • Fuel cell (FC)
  • Integrated fuel cell model
  • Real-time microgrid management
  • Fuel cell with distributed generation resources
  • Model predictive control and fuel cell

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