Introduction to AI Techniques for Renewable Energy System
暫譯: 可再生能源系統的人工智慧技術入門
Tripathi, Suman Lata, Dubey, Mithilesh Kumar, Rishiwal, Vinay
商品描述
Introduction to AI techniques for Renewable Energy System
Artificial Intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated, involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensional information domain. Design, control, and operation of renewable energy systems require a long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer from several shortcomings, like inferior quality of data, and in-sufficient long series. The book focuses on AI techniques to overcome these problems. It summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. It outlines selected AI applications for renewable energy. In particular, it discusses methods using the AI approach for prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems.
Features
- Focuses on a significant area of concern to develop a foundation for the implementation of renewable energy system with intelligent techniques
- Showcases how researchers working on renewable energy systems can correlate their work with intelligent and machine learning approaches
- Highlights international standards for intelligent renewable energy systems design, reliability, and maintenance
- Provides insights on solar cell, biofuels, wind, and other renewable energy systems design and characterization, including the equipment for smart energy systems
This book, which includes real-life examples, is aimed at undergraduate and graduate students and academicians studying AI techniques used in renewal energy systems.
商品描述(中文翻譯)
可再生能源系統的人工智慧技術介紹
人工智慧（AI）技術在可再生能源的性能建模、分析和預測中扮演著重要角色。用於建模、控制或預測能源系統性能的演算法相當複雜，涉及微分方程、大量計算能力和時間需求。與其依賴複雜的規則和數學程序，AI 技術可以在多維信息領域中學習關鍵信息模式。可再生能源系統的設計、控制和運行需要長期的氣象數據系列，例如太陽輻射、溫度或風速數據。這些長期測量在大多數感興趣的地點往往不存在，或者即使可用，也存在數據質量差和長期系列不足等多種缺陷。本書專注於AI技術以克服這些問題。它總結了可再生能源中常用的AI方法，特別強調神經網絡、模糊邏輯和遺傳演算法。它概述了可再生能源的選定AI應用，特別討論了使用AI方法進行太陽輻射預測和建模、性能捕捉以及太陽能光伏（PV）系統的控制方法。
特點
- 專注於一個重要的關注領域，以建立實施智能技術的可再生能源系統的基礎
- 展示了從事可再生能源系統研究的研究人員如何將他們的工作與智能和機器學習方法相關聯
- 突出智能可再生能源系統設計、可靠性和維護的國際標準
- 提供有關太陽能電池、生物燃料、風能及其他可再生能源系統設計和特徵的見解，包括智能能源系統的設備
本書包含實際案例，旨在為學習可再生能源系統中使用的AI技術的本科生、研究生和學術界人士提供參考。
作者簡介
Suman Lata Tripathi is working as a Professor at School of Electronics and Electrical Engineering, Lovely Professional University, India.
Mithilesh Kumar Dubey is working as an Associate Professor at School of Computer Science and Engineering, Lovely Professional University, India.
Vinay Rishiwal is working as a Professor at Department of Computer Science and Information Technology, Faculty of Engineering and Technology, MJP Rohilkhand University, Bareilly, Uttar Pradesh, India.
Sanjeevikumar Padmanaban is working as a faculty member, at Department of Energy Technology, Aalborg University, Esbjerg, Denmark.
作者簡介(中文翻譯)
Suman Lata Tripathi 目前擔任印度 Lovely Professional University 電子與電氣工程學院的教授。
Mithilesh Kumar Dubey 目前擔任印度 Lovely Professional University 計算機科學與工程學院的副教授。
Vinay Rishiwal 目前擔任印度 Uttar Pradesh 巴雷利 MJP Rohilkhand University 計算機科學與資訊技術系的教授。
Sanjeevikumar Padmanaban 目前擔任丹麥奧爾堡大學 Esbjerg 能源技術系的教職員。
