Applied Neural Networks and Fuzzy Logic in Power Electronics, Motor Drives, Renewable Energy Systems and Smart Grids

• Autore: Simões Marcelo Godoy
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
• Descrizione fisica: 1 online resource (202 p.)
• Soggetto topico: History of engineering and technology
• Soggetto non controllato: adaptive neuro-fuzzy inference system; artificial intelligence; asynchronous motor; automatic generation control; back propagation algorithm; CNN-LSTM; cognitive meters; condition assessment; convolutional neural network; current balancing algorithm; Data Envelopment Analysis (DEA); decision optimization; deep learning; deep reinforcement learning; distribution network equipment; droop curve; electric load forecasting; electricity forecasting; energy Internet; error differentiation; frequency regulation; Fuzzy Analytical Network Process (FANP); fuzzy iteration; fuzzy logic; fuzzy neural network control; Fuzzy Theory; knowledge embed; level-shifted SPWM; linear active disturbance rejection control; load disaggregation; long-term forecasting (LTF); machine learning; medium-term forecasting (MTF); medium-voltage applications; meta-heuristic algorithms; motor drives; multi information source; multi-layer perceptron; multilevel current source inverter; NILM; non-dominated sorting genetic algorithm II; non-technical losses; particle swarm optimization; phase-shifted carrier SPWM; renewable energy; reserve power; semi-supervised learning; short-term forecasting (STF); smart grid; solar power plant; STATCOM; state machine; the rate of change of frequency; thermostatically controlled loads; vector control; very short-term forecasting (VSTF)
• Persona (resp. second.): ParedesHelmo Kelis Morales; SimõesMarcelo Godoy
• Sommario/riassunto: Artificial intelligence techniques, such as expert systems, fuzzy logic, and artificial neural network techniques have become efficient tools in modeling and control applications. For example, there are several benefits in optimizing cost-effectiveness, because fuzzy logic is a methodology for the handling of inexact, imprecise, qualitative, fuzzy, and verbal information systematically and rigorously. A neuro-fuzzy controller generates or tunes the rules or membership functions of a fuzzy controller with an artificial neural network approach. There are new instantaneous power theories that may address several challenges in power quality. So, this book presents different applications of artificial intelligence techniques in advanced high-tech electronics, such as applications in power electronics, motor drives, renewable energy systems and smart grids.
• Titolo autorizzato: Applied Neural Networks and Fuzzy Logic in Power Electronics, Motor Drives, Renewable Energy Systems and Smart Grids
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557103703321
• Lo trovi qui: Univ. Federico II