03885cam a22004338i 4500 21874241 CSPC 20250306153541.0 210121s2021 flu b 001 0 eng 2021001773 9780367610920 (hbk) DLC eng rda DLC CSPC pcc TJ808 .I66 2021 621.042028563 In891 23 Introduction to AI techniques for renewable energy system / edited by Suman Lata Tripathi, [and 3 others]. First edition. 2106 Boca Raton, FL ; Abingdon, Oxon : CRC Press, 2021. xii, 410 pages ; 24 cm. text txt rdacontent unmediated n rdamedia volume nc rdacarrier Includes bibliographical references and index. Artificial intelligence : a new era in renewable energy systems -- Role of AI in renewable energy management -- AI-based renewable energy with emerging applications: issues and challenges -- Foundations of machine learning -- Introduction of AI techniques and approaches -- A comprehensive overview of hybrid renewable energy systems -- Dynamic modeling and performance analysis of switched-mode controller for hybrid energy systems -- Artificial intelligence and machine learning methods for renewable energy -- Artificial neural network-based power optimizer for solar photovoltaic system: an integrated approach with genetic algorithm -- Predictive maintenance: AI behind equipment failure prediction -- AI techniques for the challenges in smart energy systems -- Energy efficiency -- Renewable (bio-based) energy from natural resources (plant biomass matters) --Evolving trends for smart grid using artificial intelligent techniques -- Introduction to AI techniques for photovoltaic energy conversion system -- Deep learning-based fault identification of microgrid transformers -- Power quality improvement for grid-integrated renewable energy sources: a comparative analysis of UPQC topologies -- AI-based energy-efficient fault mitigation technique for reliability enhancement of wireless sensor network -- AI techniques applied to wind energy -- Comparative performance analysis of multi-objective metaheuristic approaches for parameter identification of three-diode-modeled photovoltaic cells -- Artificial intelligence techniques in smart grid -- Parameter identification of a new reverse two-diode model by moth flame optimizer -- Time series energy prediction and improved decision-making -- Machine learning-enabled cyber security in smart grids. "The book summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. Book outlines selected AI applications for renewable energy. In particular, discusses methods using the AI approach for the following applications using suitable examples: prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems"-- Provided by publisher. Renewable energy sources. Power-plants Automatic control. Artificial intelligence. Tripathi, Suman Lata, editor. Dubey, Mithilesh Kumar, editor. Rishiwal, Vinay, editor. Padmanaban, Sanjeevikumar, editor. Online version: Introduction to AI techniques for renewable energy system First edition Boca Raton : CRC Press, 2021 9781003104445 (DLC) 2021001774 7 cbc orignew 1 ecip 20 y-gencatlg ddc BK 23 621.042028563 In891 ENG 2021 0 0 0 ddc 0 0 CSPC CSPC ENG 2025-03-06 0 ENG 621.042028563 In891 2021 029099 2025-03-06 15:36:05 1-1 2025-03-06 BK 29034 29034