یک روش برنامه‌ریزی ﺧﻄﯽ ﺗﺼﺎدﻓﯽ دومرحله‌ای جهت مدیریت انرژی منابع و ذخیره‌سازهای ریزشبکه با در نظر گرفتن برنامه قیمت‌گذاری واقعی با استفاده از الگوریتم بهینه‌سازی ازدحام سالپ
محورهای موضوعی : مهندسی برق و کامپیوتر
محسن صرامی
1
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مجيد معظمي
2
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,
غضنفر شاهقلیان
3
1 - دانشگاه آزاد اسلامی واحد نجف آباد،دانشکده مهندسی برق
2 - دانشگاه آزاد اسلامی واحد نجف آباد،دانشکده مهندسی برق
3 - دانشگاه آزاد اسلامی واحد نجف آباد،دانشکده مهندسی برق
کلید واژه: الگوریتم سالپ, انرژی‌های تجدیدپذیر, بازار برق, بهره‌برداری بهینه, ریزشبکه, ذخیره‌سازی انرژی,
چکیده مقاله :
یکپارچه‌سازی منابع تجدیدپذیر به منظور تأمین بار محلی باعث به وجود آمدن مفهومی به نام ریزشبکه شده است. با ورود گسترده ریزشبکه‌ها، مدیریت انرژی و بهره‌برداری از سیستم و منابع در شرایط بازار برق از وظایف مهم مدیریت بهره‌برداری ریزشبکه است. در این مقاله مسئله بهره‌برداری ریزشبکه با در نظر گرفتن مسایل اقتصادی، فنی و همچنین با در نظر گرفتن عدم قطعیت‌های مربوط به بار مصرفی، سرعت باد و تابش خورشید در شرایط بازار برق مدل‌سازی شده است. یکی از مباحث مهم در شرایط بازار برق بحث مشارکت واحدها در شرایط قیمت واقعی است. بر این اساس چهارچوبی به منظور بهره‌برداری ﺑﻬﯿﻨﻪ و ﻣﺼﺮف اﻧﺮژی بارهای کنترل‌پذیر در ﺷﺮاﯾﻂ بهره‌برداری یکپارچه از منابع انرژی توزیع‌شده دارای عدم قطعیت، از دﯾﺪﮔﺎه مصرف‌کننده اراﺋﻪ می‌شود. مسئله بهینه‌سازی مورد نظر به صورت ﯾﮏ مسئله برنامه‌ریزی ﺧﻄﯽ ﺗﺼﺎدﻓﯽ دومرحله‌ای، با هدف کمینه‌سازی هزینه بهره‌برداری ریزشبکه و ﻫﺰﯾﻨﻪ ﻣﻮرد اﻧﺘﻈﺎر ﭘﺮداﺧﺘﯽ مصرف‌کننده و ﺑﺎ در ﻧﻈﺮ ﮔﺮﻓﺘﻦ ﻧﯿﺎز مصرف‌کننده ﺑﻪ ﺑﺮﺧﯽ از بارهای کنترل‌پذیر ﺧﻮد در بازه‌های زﻣﺎﻧﯽ مورد نظر او و محدودیت‌های بارها و ﻧﯿﺰ محدودیت‌های اعمال‌شده از ﺟﺎﻧﺐ ﺷﺮﮐﺖ ﺑﺮق ﻣﺪل می‌شود که با استفاده از الگوریتم بهینه‌سازی ازدحام سالپ حل می‌گردد. ﺑﺮای مدل‌سازی ﺑﺎزار ﺑﺮق خرده‌فروشی، تعرفه‌های RTP و IBR مورد استفاده ﻗﺮار می‌گیرد ﺗﺎ ﻫﻢ ﻧﻮﺳﺎﻧﺎت ﻗﯿﻤﺖ عمده‌فروشی ﺑﻬﺘﺮ ﻣﻨﻌﮑﺲ ﺷﻮد و ﻫﻢ از هم‌زمانی ﻣﺼﺮف ﺟﻠﻮﮔﯿﺮی گردد. در این روش ﻗﯿﻤﺖ به جای ﻣﺸﺨﺺﺑﻮدن در ﮐﻞ دوره برنامه‌ریزی، ﺗﻨﻬﺎ در ﺗﻌﺪاد ﻣﺤﺪودی از ﺳﺎﻋﺎت آﯾﻨﺪه، از ﺟﺎﻧﺐ خرده‌فروش ﺑﻪ مصرف‌کننده اﻋﻼم می‌شود. در اﯾﻦ ﺷﺮاﯾﻂ ﻫﺮ ﮔﻮﻧﻪ زمان‌بندی ﺑﺎرﻫﺎی کنترل‌پذیر ﻧﯿﺎزﻣﻨﺪ پیش‌بینی ﻗﯿﻤﺖ اﺳﺖ و اﯾﻦ در ﺣﺎﻟﯽ اﺳﺖ ﮐﻪ پیش‌بینی ﻗﯿﻤﺖ، ﻋﺪم قطعیت‌هایی را ﺑﻪ ﻫﻤﺮاه ﺧﻮاﻫﺪ داﺷﺖ. اﯾﻦ عدم قطعیت ﺑﺎ ﺗﻮﻟﯿﺪ ﺳﻨﺎرﯾﻮﻫﺎﯾﯽ ﺑﺮای ﻣﺘﻐﯿﺮ ﺗﺼﺎدﻓﯽ ﻗﯿﻤﺖ آﯾﻨﺪه ﺑﺎ اﺳﺘﻔﺎده از روش مونت‌کارلو، مدل‌سازی می‌شود. روش پیشنهادی با استفاده از نرم‌افزار MATLAB شبیه‌سازی و توانایی آن نشان داده شده است.
Integrating renewable resources to provide local load has created a concept called microgrid. With the widespread introduction of microgrids, energy management and system utilization and resources in the electricity market are important tasks of microgrid management. In this paper, the problem of microgrid utilization is modeled taking into account economic, technical and uncertainties related to power consumption, wind speed and solar radiation in electricity market conditions. One of the most important issues in the electricity market is the discussion of the participation of units in real price conditions. In this paper, a framework for the exploitation of electricity and the consumption of controllable loads through integrated utilization of distributed energy sources of uncertainty is presented from a consumer perspective. The optimization problem is a two-step stochastic linear programming that minimized the cost of microgrid operation and expected cost of consumers considering the consumer’s requirement for controllable loads in the desire time interval and distribution company constraints that solved by using Salp swarm optimization algorithm. RBT and IBR tariffs are employed for modeling retail power market for better reflection of wholesale price volatility and avoid of the concurrent use of consumers. In this method price announced to the consumers by retailers only is limited specific later hours instead of the entire operation period. In this condition any timing of controllable loads need to price forecasting, while this forecasting have some uncertainties. These uncertainties are modeled using Monte Carlo method for stochastic price variable scenario generation. MATLAB software is employed for simulation and verification of the proposed method.
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