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تحلیل یکپارچۀ کاربردهای پیشرفتۀ هوش مصنوعی در سیستمهای انرژی مدرن | ||
| فصلنامه سیستم های انرژی پایدار | ||
| دوره 5، شماره 2، فروردین 1405، صفحه 297-327 اصل مقاله (2.14 M) | ||
| نوع مقاله: مروری | ||
| شناسه دیجیتال (DOI): 10.22059/ses.2025.402633.1185 | ||
| نویسندگان | ||
| امیرعلی سیف الدین* 1؛ محمدحسین قلی زاده2؛ محمدعلی اله ربی شیرازی3 | ||
| 1دانشیار، دانشکدۀ مهندسی انرژی و منابع پایدار، رئیس مؤسسۀ فناوریهای نرم، دانشکدگان علوم و فناوریهای میانرشتهای، دانشگاه تهران، تهران، ایران | ||
| 2دانشجوی کارشناسی ارشد مهندسی سیستمهای انرژی، دانشکدۀ مهندسی انرژی و منابع پایدار، دانشکدگان علوم و فناوریهای میانرشتهای، دانشگاه تهران، تهران، ایران | ||
| 3دانشجوی دکتری مهندسی سیستمهای انرژی، دانشکدۀ مهندسی انرژی و منابع پایدار، دانشکدگان علوم و فناوریهای میانرشتهای، دانشگاه تهران، تهران، ایران | ||
| چکیده | ||
| صنعت انرژی در آستانۀ تحول بنیادین است و سامانههای قدرت به زیستبومهای رایانشی ـ فیزیکی پیچیده تبدیل شدهاند که در آن بازارهای دیجیتال، زیرساختهای فیزیکی و منابع بینبخشی مانند آب به طور عمیق درهمتنیدهاند. مدیریت این پیچیدگی به گذار از ابزارهای سنتی به هوشمندی یکپارچه و خودگردان نیاز دارد. هدف مقالۀ حاضر، ارائۀ تحلیلی جامع از نقش هوش مصنوعی به عنوان فناوری توانمندساز نسل آیندۀ سیستمهای انرژی است. مقالۀ پیش رو، بر قابلیتهای کلیدی هوش مصنوعی شامل پیشبینی و تشخیص خطا، یادگیری الگوهای پیچیده، بهینهسازی عملکرد سیستمها و پشتیبانی از تصمیمگیری خودگردان در سامانههای انرژی متمرکز است. چارچوب تحلیلی ارائهشده بر چهار رکن بنیادین تمرکز دارد: (۱) هوشمندسازی بازار انرژی از طریق تجارت الگوریتمی و سازوکارهای غیرمتمرکز؛ (۲) ارتقای تابآوری شبکه با تشخیص و بازیابی سریع خطا؛ (۳) بهینهسازی عملکرد شبکه از طریق مدیریت خودکار کیفیت توان؛ (۴) افزایش پایداری سیستمی با بهینهسازی پیوند آب ـ انرژی. نوآوری این پژوهش در یکپارچهسازی این چهار حوزه و ارائۀ دیدگاهی چندلایه است که تعامل میان ابعاد اقتصادی، فنی، عملیاتی و زیستمحیطی را تحلیل میکند. یافتهها نشان میدهد هوش مصنوعی در حال شکلدهی به یک پارادایم مدیریتی یکپارچه است که از الگوریتمهای یادگیری تقویتی و شبکههای خودترمیم تا بهینهسازی مقاوم برای منابع تجدیدپذیر را شامل میشود. کاربرد هوش مصنوعی موجب بهبود کیفیت توان، افزایش طول عمر داراییها، تسهیل مدیریت پیوند آب ـ انرژی و تقویت تابآوری شبکه میشود. با اینحال، چالشهایی نظیر امنیت سایبری، اعتمادپذیری و شکاف شبیهسازی ـ واقعیت باقی است. | ||
| کلیدواژهها | ||
| هوش مصنوعی؛ سیستم های انرژی هوشمند؛ تابآوری شبکه؛ تجارت الگوریتمی انرژی؛ بهینه سازی پیوند آب انرژی | ||
| عنوان مقاله [English] | ||
| Integrated analysis of advanced applications of artificial intelligence (AI) in modern energy systems | ||
| نویسندگان [English] | ||
| Amirali Saifoddin1؛ Mohammad Hossein Gholizadeh2؛ Mohammadali Allahrabbi Shirazi3 | ||
| 1Associate Professor, School of Energy Engineering and Sustainable Resources, Head of the Institute of Soft Technologies, College of Interdisciplinary Sciences and Technologies, University of Tehran, Tehran, Iran | ||
| 2Master's Student in Energy Systems Engineering, School of Energy Engineering and Sustainable Resources, College of Interdisciplinary Sciences and Technologies, University of Tehran, Tehran, Iran | ||
| 3PhD Candidate in Energy Systems Engineering, School of Energy Engineering and Sustainable Resources, College of Interdisciplinary Sciences and Technologies, University of Tehran, Tehran, Iran | ||
| چکیده [English] | ||
| The energy industry is on the verge of a fundamental transformation, with power systems evolving into complex computational-physical ecosystems where digital markets, physical infrastructure, and cross-sector resources such as water are intricately intertwined. Managing this complexity requires moving from traditional tools to integrated and autonomous intelligence. This paper aims to provide a comprehensive analysis of the role of artificial intelligence as an enabling technology for the next generation of energy systems. In this review, key capabilities of artificial intelligence include fault prediction and detection, complex patterns, optimization of system performance, and support for decision-making in energy systems themselves. The analysis presented is based on four fundamental pillars of intelligence: (1) building energy markets through algorithmic trading and decentralized mechanisms, (2) enhancing grid resilience through rapid fault detection and recovery, (3) optimizing grid performance through power quality automation, and (4) enhancing system stability by optimizing the water-energy nexus. The innovation of this research lies in integrating these four domains and providing a multi-layered perspective that analyzes economic, technical, operational, and environmental aspects of enterprises. The findings show that artificial intelligence is shaping an integrated management paradigm that ranges from reinforcement algorithms and self-healing networks to robust optimization for renewable resources. The application of artificial intelligence improves power quality, extends asset lifetime, manages the water-energy nexus, and enhances grid resilience. However, challenges such as cybersecurity, reliability, and the simulation-reality gap remain. | ||
| کلیدواژهها [English] | ||
| Artificial Intelligence, Smart Energy Systems, Grid Resilience, Algorithmic Energy Trading, Energy-Water Nexus Optimization | ||
| مراجع | ||
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