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Intelligent data analytics for power and energy systems

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Intelligent data analytics for power and energy systemsedited by Hasmat Malik, Md. Waseem Ahmad, D. P. Kothari.
其他作者:	Malik, Hasmat.
出版者:	Singapore :Springer Singapore :2022.
面頁冊數:	xxii, 641 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Electric power systemsData processing.
電子資源:	https://doi.org/10.1007/978-981-16-6081-8
ISBN:	9789811660818$q(electronic bk.)

Intelligent data analytics for power and energy systems
Intelligent data analytics for power and energy systems[electronic resource] /edited by Hasmat Malik, Md. Waseem Ahmad, D. P. Kothari. - Singapore :Springer Singapore :2022. - xxii, 641 p. :ill. (some col.), digital ;24 cm. - Lecture notes in electrical engineering,v. 8021876-1119 ;. - Lecture notes in electrical engineering ;v.132..

Intelligent Approach for Analysis and Diagnosis of Attack, Fault and Load Variation in SCADA Systems: A Power System Application -- Intelligent Approach for Distributed Generation Planning and Distribution Network Reconfiguration Using Metaheuristic Technique -- Intelligent Modelling and Analysis of Direct Torque Control-Space Vector Modulation of Doubly Fed Induction Generator (DFIG) -- Modelling and Analysis of an Intelligent Approach for Load Frequency Control in a Deregulated Power System: A Case Study Based on Different Control Schemes -- Mathematical Approach Based Power System Analysis: A Review of Short Term Hydro Scheduling -- Novel Approach for Power System Stability Analysis and Improvement: A Case Study Based on UPFC Application -- Intelligent Modelling and Analysis of P-Q Control Technique for SPV Plant Supplying Power to Grid -- Intelligent Approach for Fuel Constrained Economic Emission Dispatch Analysis Using Multi-objective Differential Evolution -- Intelligent Adaptive Critic Scheme Implementation and Investigation Using Policy Iteration Technique: A case study of Multi-Area Automatic Generation Control (AGC) Problem -- Intelligent Method for Installation and Investigation of VSC-HVDC Converter Using Metaheuristic Algorithm: A Case Study of Unified Optimal Power Flow problem -- Implementation and Analysis of TID Controller for Power Apparatus Applications using Flower Pollination Algorithm -- Intelligent Technique for Eccentricity Fault Diagnosis of Power Apparatus Using Signal Processing Method -- Intelligent Methods for Power System Analysis: Advancement in Optimization and its Application -- Investigation and Analysis of Harmonics in Different Control Techniques of PMSM Drives: An Application of Power System Health Monitoring -- Design and Analysis of Artificial Intelligence Method for MPPT Control: An Application of Grid Connected PV System.

This book brings together state-of-the-art advances in intelligent data analytics as driver of the future evolution of PaE systems. In the modern power and energy (PaE) domain, the increasing penetration of renewable energy sources (RES) and the consequent empowerment of consumers as a central and active solution to deal with the generation and development variability are driving the PaE system towards a historic paradigm shift. The small-scale, diversity, and especially the number of new players involved in the PaE system potentiate a significant growth of generated data. Moreover, advances in communication (between IoT devices and M2M: machine to machine, man to machine, etc.) and digitalization hugely increased the volume of data that results from PaE components, installations, and systems operation. This data is becoming more and more important for PaE systems operation, maintenance, planning, and scheduling with relevant impact on all involved entities, from producers, consumer,s and aggregators to market and system operators. However, although the PaE community is fully aware of the intrinsic value of those data, the methods to deal with it still necessitate substantial enhancements, development and research. Intelligent data analytics is thereby playing a fundamental role in this domain, by enabling stakeholders to expand their decision-making method and achieve the awareness on the PaE environment. The editors also included demonstrated codes for presented problems for better understanding for beginners.

ISBN: 9789811660818$q(electronic bk.)

Standard No.: 10.1007/978-981-16-6081-8doiSubjects--Topical Terms:

310284
Electric power systems
--Data processing.

LC Class. No.: TK1005 / .I58 2022

Dewey Class. No.: 621.3102856312

Intelligent data analytics for power and energy systems
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520 $a This book brings together state-of-the-art advances in intelligent data analytics as driver of the future evolution of PaE systems. In the modern power and energy (PaE) domain, the increasing penetration of renewable energy sources (RES) and the consequent empowerment of consumers as a central and active solution to deal with the generation and development variability are driving the PaE system towards a historic paradigm shift. The small-scale, diversity, and especially the number of new players involved in the PaE system potentiate a significant growth of generated data. Moreover, advances in communication (between IoT devices and M2M: machine to machine, man to machine, etc.) and digitalization hugely increased the volume of data that results from PaE components, installations, and systems operation. This data is becoming more and more important for PaE systems operation, maintenance, planning, and scheduling with relevant impact on all involved entities, from producers, consumer,s and aggregators to market and system operators. However, although the PaE community is fully aware of the intrinsic value of those data, the methods to deal with it still necessitate substantial enhancements, development and research. Intelligent data analytics is thereby playing a fundamental role in this domain, by enabling stakeholders to expand their decision-making method and achieve the awareness on the PaE environment. The editors also included demonstrated codes for presented problems for better understanding for beginners.
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