Artificial Intelligence Enabled Computational Methods for Smart Grid Forecast and Dispatch

Li, Yuanzheng, Zhao, Yong, Wu, Lei

  • 出版商: Springer
  • 出版日期: 2024-05-07
  • 售價: $6,260
  • 貴賓價: 9.5$5,947
  • 語言: 英文
  • 頁數: 260
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9819908019
  • ISBN-13: 9789819908011
  • 相關分類: 人工智慧
  • 海外代購書籍(需單獨結帳)

相關主題

商品描述

With the increasing penetration of renewable energy and distributed energy resources, smart grid is facing great challenges, which could be divided into two categories. On the one hand, the endogenous uncertainties of renewable energy and electricity load lead to great difficulties in smart grid forecast. On the other hand, massive electric devices as well as their complex constraint relationships bring about significant difficulties in smart grid dispatch.

Owe to the rapid development of artificial intelligence in recent years, several artificial intelligence enabled computational methods have been successfully applied in the smart grid and achieved good performances. Therefore, this book is concerned with the research on the key issues of artificial intelligence enabled computational methods for smart grid forecast and dispatch, which consist of three main parts.

(1) Introduction for smart grid forecast and dispatch, in inclusion of reviewing previous contribution of various research methods as well as their drawbacks to analyze characteristics of smart grid forecast and dispatch.

(2) Artificial intelligence enabled computational methods for smart grid forecast problems, which are devoted to present the recent approaches of deep learning and machine learning as well as their successful applications in smart grid forecast.

(3) Artificial intelligence enabled computational methods for smart grid dispatch problems, consisting of edge-cutting intelligent decision-making approaches, which help determine the optimal solution of smart grid dispatch.

The book is useful for university researchers, engineers, and graduate students in electrical engineering and computer science who wish to learn the core principles, methods, algorithms, and applications of artificial intelligence enabled computational methods.

商品描述(中文翻譯)

隨著可再生能源和分散能源資源的普及,智慧電網面臨著巨大的挑戰,可以分為兩個類別。一方面,可再生能源和電力負載的內在不確定性導致智慧電網預測面臨巨大困難。另一方面,大量的電力設備以及它們之間複雜的約束關係給智慧電網調度帶來了重大困難。

由於人工智慧近年來的快速發展,一些基於人工智慧的計算方法已成功應用於智慧電網並取得良好的表現。因此,本書關注於人工智慧啟用的計算方法在智慧電網預測和調度中的關鍵問題的研究,包括三個主要部分。

(1) 智慧電網預測和調度的介紹,包括回顧各種研究方法的先前貢獻以及它們的缺點,以分析智慧電網預測和調度的特點。

(2) 人工智慧啟用的計算方法用於智慧電網預測問題,致力於介紹深度學習和機器學習的最新方法以及它們在智慧電網預測中的成功應用。

(3) 人工智慧啟用的計算方法用於智慧電網調度問題,包括尖端的智能決策方法,有助於確定智慧電網調度的最優解。

本書對於希望學習人工智慧啟用的計算方法的核心原理、方法、算法和應用的電氣工程和計算機科學的大學研究人員、工程師和研究生非常有用。

作者簡介

Yuanzheng Li received the M.S. degree in electrical engineering from the Huazhong University of Science and Technology, Wuhan, China, in 2011 and the Ph.D. degree in electrical engineering from the South China University of Technology, Guangzhou, China, in 2015. He was a visiting Ph.D. student in the Department of Electrical and Electronics Engineering, University of Liverpool, UK, during January to December 2014. After obtaining the Ph.D. degree, he went to Nanyang Technical University, Singapore, and was a research fellow in School of Electrical and Electronics Engineering from June 2016 to December 2017. Currently, Dr. Li is an associate professor in School of Artificial Intelligence and Automation, Huazhong University of Science and Technology.

He is also a core member of the Future Power Grid Research Institute, which is supported by STATE GRID Corporation of China. His research interests include artificial intelligence and its application in smart grid, deeplearning, reinforcement learning, optimal power system/microgrid dispatch and decision making, stochastic optimization considering large-scale integration of renewable energy into the power system and multi-objective optimization. He has authored or coauthored several peer-reviewed papers in international journals, including more than 40 IEEE Transactions papers. Some of the papers have been selected as Feature Article, ESI Highly Cited Paper, Best Conference Award, Highly Cited Journal Paper, etc. He is the associate editor of IEEE Transactions on Intelligent Vehicles and IET Renewable Power Generation.

Yong Zhao received the M.S. degree and Ph.D. degree in system engineering from the Huazhong University of Science and Technology, Wuhan, China, in 1992 and 1996, respectively. He was then a postdoc in mechanical engineering during 1996 to 1998. He was promoted as an associate professor and a full professor in School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, in 1998 and 2000, respectively. He was a visiting scholar in the Department of System Engineering, University of Oxford, UK, during 2005 to 2006.

Currently, he is the vice director of Future Power Grid Research Institute, which is supported by STATE GRID Corporation of China. His research interests include decision-making theory, operation research, power system markets, integrated energy systems, and smart grids. He has authored or coauthored several peer-reviewed papers in international journals and supervised more than 20 Ph.D. students.

Lei Wu received the B.S. degree in electrical engineering and the M.S. degree in systems engineering from Xi'an Jiaotong University, Xi'an, China, in 2001 and 2004, respectively, and the Ph.D. degree in electrical engineering from Illinois Institute of Technology (IIT), Chicago, IL, USA, in 2008. From 2008 to 2010, he was a senior research associate with the Robert W. Galvin Center for Electricity Innovation, IIT. He was a professor with the Electrical and Computer Engineering Department, Clarkson University, Potsdam, NY, USA, till 2018. He is currently a professor with the Electrical and Computer Engineering Department, Stevens Institute of Technology, Hoboken, NJ.

His primary research and teaching areas are focused on power and energy system optimization and control, with specific interests in the modeling of large-scale power systems with a high penetration of demand response and renewable energy, and community resilience microgrid. He is the recipient of Transactions Prize Paper Award from the IEEE Power and Energy Society (PES) in 2009 and the IEEE PES Student Prize Paper Award in Honor of T. Burke Hayes as an adviser in 2014. He is an IEEE fellow.

Zhigang Zeng received the Ph.D. degree in systems analysis and integration from Huazhong University of Scienceand Technology, Wuhan, China, in 2003. He is currently a professor with the School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China. He has published more than 100 international journal articles. His current research interests include theory of functional differential equations and differential equations with discontinuous right-hand sides and their applications to dynamics of neural networks, memristive systems, and control systems.

Professor Zeng was an associate editor of the IEEE Transactions on Neural Networks and Learning Systems from 2010 to 2011. He has been an associate editor of the IEEE Transactions on Cybernetics since 2014 and the IEEE Transactions on Fuzzy Systems since 2016 and a member of the Editorial Board of Neural Networks since 2012, Cognitive Computation since 2010, and Applied Soft Computing since 2013.

Professor Zeng is currently the director of KeyLaboratory of Image Processing and Intelligent Control of the Education Ministry of China, Huazhong University of Science and Technology, Wuhan, China. He is also a Cheung Kong scholar and the receiver of Outstanding Fund of National Natural Science Foundation of China. He is an IEEE fellow.

作者簡介(中文翻譯)

Yuanzheng Li於2011年獲得華中科技大學電氣工程碩士學位,並於2015年獲得華南理工大學電氣工程博士學位。他在2014年1月至12月期間,曾作為訪問博士生在英國利物浦大學電氣與電子工程系進修。獲得博士學位後,他前往新加坡南洋理工大學,並於2016年6月至2017年12月期間擔任該校電氣與電子工程學院的研究員。目前,李博士是華中科技大學人工智能與自動化學院的副教授。

他還是由中國國家電網公司支持的未來電力網格研究所的核心成員。他的研究興趣包括人工智能及其在智能電網中的應用、深度學習、強化學習、最佳電力系統/微電網調度和決策、考慮到可再生能源大規模融入電力系統的隨機優化以及多目標優化。他在國際期刊上發表或合著了多篇同行評審的論文,其中包括40多篇IEEE Transactions論文。其中一些論文被選為特色文章、ESI高被引論文、最佳會議論文獎、高被引期刊論文等。他是IEEE Transactions on Intelligent Vehicles和IET Renewable Power Generation的副編輯。

Yong Zhao於1992年和1996年分別獲得華中科技大學系統工程碩士學位和博士學位。他在1996年至1998年期間擔任機械工程的博士後研究員。他於1998年和2000年分別晉升為華中科技大學人工智能與自動化學院的副教授和教授。他在2005年至2006年期間曾作為訪問學者在英國牛津大學系統工程系進修。

目前,他是由中國國家電網公司支持的未來電力網格研究所的副主任。他的研究興趣包括決策理論、運營研究、電力系統市場、綜合能源系統和智能電網。他在國際期刊上發表或合著了多篇同行評審的論文,並指導了20多名博士生。

Lei Wu於2001年和2004年分別獲得西安交通大學電氣工程學士學位和系統工程碩士學位,並於2008年獲得美國伊利諾伊理工學院電氣工程博士學位。從2008年到2010年,他在伊利諾伊理工學院的羅伯特·W·加爾文電力創新中心擔任高級研究員。他曾是紐約州波茨坦的克拉克森大學電氣與計算機工程系的教授,直到2018年。目前,他是新澤西州霍博肯的史蒂文斯理工學院電氣與計算機工程系的教授。

他的主要研究和教學領域集中在電力和能源系統的優化和控制,特別關注高需求響應和可再生能源大規模融入的大型電力系統建模以及社區韌性微電網。他獲得了IEEE電力與能源學會(PES)的Transactions Prize Paper Award(2009年)和以T. Burke Hayes為指導教授的IEEE PES學生獎論文獎(2014年)。他是IEEE的會士。

Zhigang Zeng於2003年獲得華中科技大學系統分析與集成博士學位。他目前是一位教授。