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Intelligent Methods in Electrical Power Systems de Chetan B. Khadse

Intelligent Methods in Electrical Power Systems: Engineering Optimization: Methods and Applications

Editat de Chetan B. Khadse, Ishaan R. Kale, Apoorva S. Shastri
en Limba Engleză Hardback – 3 noi 2024

Observăm în Intelligent Methods in Electrical Power Systems o abordare tehnică riguroasă, care debutează prin exerciții de mare actualitate, precum analiza defectelor pe partea de curent alternativ a micro-rețelelor folosind rețele neuronale de tip SCGB (Scaled Conjugate Gradient Backpropagation). Această metodă demonstrează capacitatea algoritmilor avansați de a identifica și clasifica erorile într-un mediu energetic complex, oferind o precizie superioară metodelor convenționale.

Descoperim un volum structurat pentru a servi drept ghid practic, unde fiecare capitol este de sine stătător și include atât o revizuire a literaturii de specialitate, cât și studii de caz aplicate. Progresia conținutului urmărește un fir logic de la fundamentul teoretic al metodelor inteligente la aplicații extrem de specifice, cum ar fi utilizarea algoritmului Artificial Bee Colony în controlul automat al generării pentru sistemele termice sau implementarea sistemelor de automatizare a locuinței prin protocolul IFTTT și Google Assistant. Dacă Modern Optimization Techniques with Applications in Electric Power Systems v-a oferit cadrul teoretic necesar înțelegerii algoritmilor genetici și a sistemelor fuzzy, volumul coordonat de Chetan B. Khadse și colegii săi oferă instrumentele practice și implementările software (precum aplicația Weka pentru prognoza sarcinii) necesare inginerului contemporan.

Recomandăm această lucrare pentru modul în care integrează optimizarea metaheuristică și algoritmii Random Forest în gestionarea rețelelor inteligente (Smart Grids). Analiza pierderilor în sistemele de distribuție și alocarea acestora în funcție de factorul de putere al sarcinii reprezintă un punct forte al cărții, oferind soluții concrete pentru eficientizarea operațională a sistemelor electroenergetice moderne.

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Specificații

ISBN-13: 9789819757176
ISBN-10: 9819757177
Pagini: 188
Ilustrații: X, 190 p. 100 illus., 50 illus. in color.
Dimensiuni: 160 x 241 x 16 mm
Greutate: 0.49 kg
Ediția:2025
Editura: Springer
Colecția Engineering Optimization: Methods and Applications
Seria Engineering Optimization: Methods and Applications

Locul publicării:Singapore, Singapore

De ce să citești această carte

Recomandăm această carte profesioniștilor și studenților de la masterat care doresc să treacă de la teorie la implementarea algoritmilor de inteligență artificială în ingineria electrică. Cititorul câștigă acces la studii de caz detaliate despre rețele neuronale, IoT și optimizare metaheuristică, primind soluții aplicabile imediat pentru prognoza consumului, detectarea defectelor la motoarele de inducție și managementul eficient al micro-rețelelor.

Despre autor

Volumul este editat de o echipă de specialiști condusă de Chetan B. Khadse, Ishaan R. Kale și Apoorva S. Shastri. Chetan B. Khadse este recunoscut pentru expertiza sa în aplicarea metodelor computaționale inteligente în sistemele de putere, contribuind constant la literatura tehnică prin cercetări axate pe optimizarea și stabilitatea rețelelor electrice. Editorii au selectat contribuții care reflectă cele mai recente tendințe în optimizarea ingineriei, publicate sub egida prestigioasei edituri Springer, asigurând un standard academic înalt și o aplicabilitate practică directă în industria de profil.

Descriere scurtă

This book provides a comprehensive review of the latest developments in optimization based learning algorithms within the field of electrical engineering. It covers various power system applications including efficient power system operation, load forecasting, fault analysis, home automation and efficient smart grid management. Each application is accompanied by case studies and a literature review in self-contained chapters. The book is dedicated to study the effectiveness of intelligent methods in addressing the power system problems and its mitigation using optimization algorithms. It discusses several optimization algorithms such as random forest algorithm, metaheuristic algorithm, scaled conjugate gradient descent algorithm, artificial bee colony algorithm etc. and their usability in intelligent decision makers for the various optimization problems in electrical engineering. This timely book serves as a practical guide and reference sources for students, researchers and professionals.

Cuprins

Review on intelligent methods in Electrical power systems.- Investigation of Electric Load Forecasting Methods: A Weka Application (Regression and Optimization).- Integration of Intelligent Systems for Efficient Smart Grid Management.- An Application of Artificial Bee Colony and Cohort Intelligence in Automatic Generation Control of Thermal Power System.- Distribution System Losses and Its Allocation: Effects of Load Power Factor and Distributed Generations.- IoT based Intelligent Home Automation System using IFTTT with Google Assistant.- A review on Meta-heuristic Optimization Methods for Efficient Power System Operation.- Ice thickness control circuit to automate the milk chilling system.- SCGB Neural Network based Micro-grid AC Side Fault Analysis.- Artificial intelligence based system for detection and classification of faults in Induction motor.

Notă biografică

Chetan B. Khadse holds a PhD in "AI applications in Electrical Engineering" from Visvesvaraya National Institute of Technology Nagpur, India,  an MTech in Power Systems from Shivaji University, India, and a Bachelors from Amravati University, India. He is currently working as an Assistant Professor in the School of Electrical Engineering at the MITWPU, Pune, India. His research interests include artificial intelligence, power systems, power quality, optimization algorithms, and intelligent systems. He has published over  18 research papers in peer-reviewed reputed journals, chapters, and conferences. He is actively involved in the Center of Excellence of Electric vehicle at MITWPU where his research is mainly focused on AI techniques for the betterment of EVs. 
Ishaan R. Kale holds a Ph.D. in Nature-Inspired Optimization Techniques from the faculty of Mechanical Engineering at Symbiosis International University. He received his Master of Engineering in Mechanical Design Engineering from Maharashtra Institute of Technology, Pune University, and his Bachelor of Engineering from North Maharashtra University. Ishaan worked as an Assistant Professor at Symbiosis Institute of Technology for six years. Currently, he is working as a Research Assistant Professor at the Institute of Artificial Intelligence, MIT World Peace University. His research interests include Design Engineering, Structural Optimization, Computational Intelligence, Constraint Handling, Probability Collectives, Socio Inspired Optimization Methods, Physics-Based Optimization Methods, Cohort Intelligence, Particle Swarm Optimization, Genetic Algorithms, Hybrid Metaheuristics, Game Theory, Operation Research, and Numerical Methods.  He has published 10 research papers in peer-reviewed journals, conferences, and chapters along with one authored and one edited book. He is also involved as an active research member of the Optimization and Agent Technology Research Lab.
Apoorva S. Shastri holds a PhD in Optimization Algorithms and Applications from Symbiosis International (Deemed University), a Master of Technology (M. Tech) in VLSI Design, and a Bachelor of Engineering in Electronics & Product Design Technology from R.T.M.N.U, Nagpur. She has also earned a Diploma from the Govt. Polytechnic, Nagpur. She worked as a guest faculty at the Centre for Development of Advanced Computing (C-DAC), Pune. Currently, she is a Research Assistant Professor at the Institute of Artificial Intelligence at the MITWPU, Pune, India. Her research interests include optimization algorithms, VLSI design, multi-objective optimization, continuous, discrete, and combinatorial optimization, complex systems, manufacturing, and self-organizing systems. Apoorva developed socio-inspired optimization methodologies such as Multi-Cohort Intelligence Algorithm and Expectation Algorithm. Apoorva has published several research papers in peer-reviewed journals, chapters, and conferences along with one Springer authored book. She is a regular reviewer of different journals Elsevier and Springer. She has also served as session chair for a few international conferences.

Caracteristici

Covers the optimization algorithms used in power systems Serves as a practical guide and reference resource for students, researchers and professionals Includes AI oriented chapters in electrical applications