برنامه‌ریزی توسعه یک ریز شبکه در حضور عدم قطعیت‌های بار، قیمت برق در بازار و منابع تجدیدپذیر
محورهای موضوعی : مهندسی برق قدرت
1 - گروه مهندسی برق، واحد کرمانشاه، دانشگاه آزاد اسلامی، کرمانشاه، ایران
کلید واژه: باتری, بهینه‌سازی در سیستم قدرت, توسعه ریز شبکه, عدم قطعیت, عمق تخلیه باتری,
چکیده مقاله :
دلیل نگرانی‌های حاصل از سوخت‌های فسیلی توسعه ریز شبکه‌ها در حضور باتری‌های ذخیره‌ساز انرژی الکتریکی توجه زیادی را به خود جلب کرده است. ریز شبکه‌ها با استفاده از باتری‌ها می‌توانند انرژی را در زمان‌های اوج تولید ذخیره و در زمان‌های اوج مصرف به شبکه تزریق کنند که این امر باعث بهبود پایداری و قابلیت اطمینان سیستم می‌شود. باتری‌ها به مدیریت بار و کاهش تلفات کمک می‌کنند و امکان استفاده بهینه از منابع تجدیدپذیر را فراهم می‌آورند. برای تضمین عملکرد اقتصادی ریز شبکه‌ها، ضروری است که اندازه‌گیری ذخیره‌سازی انرژی باتری به‌صورت بهینه انجام شود. عواملی که تأثیر قابل‌توجهی بر دقت و کارایی نتایج اندازه‌گیری ذخیره‌سازی انرژی باتری دارند، معمولاً لحاظ نمی‌شوند. این عوامل شامل مجموعه‌ای از ویژگی‌ها برای فنّاوری‌های مختلف، تأثیر عمق تخلیه و تعداد چرخه‌های شارژ/دشارژ بر کاهش کیفیت ذخیره‌سازی انرژی باتری و هماهنگی حالت‌های بهره‌برداری ریز شبکه هستند. در این مقاله مدلی برای اندازه‌گیری ذخیره‌سازی انرژی باتری در کاربردهای ریز شبکه ارائه می‌دهد که عوامل کلیدی از جمله اندازه، نوع فنّاوری، تعداد و حداکثر عمق تخلیه بهینه برای ذخیره‌سازی انرژی باتری را در حضور عدم قطعیت‌های منابع تجدیدپذیر و بار الکتریکی را در نظر می‌گیرد. برای بررسی عدم قطعیت‌ها از ابزار مونت‌کارلو استفاده شده است. مدل به‌کاررفته یک مدل خطی آمیخته عدد صحیح است. همچنین، رابطه غیرخطی بین عمق تخلیه ذخیره‌سازی انرژی باتری و چرخه عمر آن با به‌کارگیری رویکرد خطی‌سازی قطعه‌ای مدل‌سازی شده است. نتایج نشان می‌دهد که مدل مورد استفاده قادر است اندازه، نوع فنّاوری، تعداد و حداکثر عمق تخلیه بهینه ذخیره‌سازی انرژی باتری را تعیین کند.
The concerns arising from fossil fuels have drawn significant attention to the development of microgrids with the presence of energy storage batteries. Microgrids, utilizing batteries, can store energy during peak production times and inject it into the grid during peak consumption periods, thereby enhancing the stability and reliability of the system. Additionally, batteries assist in load management and reduce energy losses, enabling optimal use of renewable resources. To ensure the economic performance of microgrids, optimizing the measurement of battery energy storage is essential. Factors significantly impacting the accuracy and efficiency of battery energy storage measurement results are often overlooked. These factors include a range of characteristics for different technologies, the effects of depth of discharge, the number of charge/discharge cycles on the degradation of battery energy storage quality, and the coordination of microgrid operating modes. This paper presents a model for measuring battery energy storage in microgrid applications that considers key factors such as size, technology type, number, and optimal maximum depth of discharge in the presence of uncertainties related to renewable resources and electrical load. Monte Carlo simulation is employed to analyze these uncertainties. The model used is a mixed-integer linear programming model. Furthermore, the nonlinear relationship between the depth of discharge of battery energy storage and its cycle life is modeled using a piecewise linearization approach. The results indicate that the proposed model can effectively determine the size, technology type, number, and optimal maximum depth of discharge for battery energy storage.
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