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Book
Applied Neural Networks and Fuzzy Logic in Power Electronics, Motor Drives, Renewable Energy Systems and Smart Grids
Authors: ---
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

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.

Keywords

droop curve --- frequency regulation --- fuzzy logic --- the rate of change of frequency --- reserve power --- smart grid --- energy Internet --- convolutional neural network --- decision optimization --- deep reinforcement learning --- electric load forecasting --- non-dominated sorting genetic algorithm II --- multi-layer perceptron --- adaptive neuro-fuzzy inference system --- meta-heuristic algorithms --- automatic generation control --- fuzzy neural network control --- thermostatically controlled loads --- back propagation algorithm --- particle swarm optimization --- load disaggregation --- artificial intelligence --- cognitive meters --- machine learning --- state machine --- NILM --- non-technical losses --- semi-supervised learning --- knowledge embed --- deep learning --- distribution network equipment --- condition assessment --- multi information source --- fuzzy iteration --- current balancing algorithm --- level-shifted SPWM --- medium-voltage applications --- multilevel current source inverter --- motor drives --- phase-shifted carrier SPWM --- STATCOM --- electricity forecasting --- CNN–LSTM --- very short-term forecasting (VSTF) --- short-term forecasting (STF) --- medium-term forecasting (MTF) --- long-term forecasting (LTF) --- asynchronous motor --- linear active disturbance rejection control --- error differentiation --- vector control --- renewable energy --- solar power plant --- Data Envelopment Analysis (DEA) --- Fuzzy Analytical Network Process (FANP) --- Fuzzy Theory


Book
Applied Neural Networks and Fuzzy Logic in Power Electronics, Motor Drives, Renewable Energy Systems and Smart Grids
Authors: ---
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Bookmark

Abstract

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.

Keywords

History of engineering & technology --- droop curve --- frequency regulation --- fuzzy logic --- the rate of change of frequency --- reserve power --- smart grid --- energy Internet --- convolutional neural network --- decision optimization --- deep reinforcement learning --- electric load forecasting --- non-dominated sorting genetic algorithm II --- multi-layer perceptron --- adaptive neuro-fuzzy inference system --- meta-heuristic algorithms --- automatic generation control --- fuzzy neural network control --- thermostatically controlled loads --- back propagation algorithm --- particle swarm optimization --- load disaggregation --- artificial intelligence --- cognitive meters --- machine learning --- state machine --- NILM --- non-technical losses --- semi-supervised learning --- knowledge embed --- deep learning --- distribution network equipment --- condition assessment --- multi information source --- fuzzy iteration --- current balancing algorithm --- level-shifted SPWM --- medium-voltage applications --- multilevel current source inverter --- motor drives --- phase-shifted carrier SPWM --- STATCOM --- electricity forecasting --- CNN–LSTM --- very short-term forecasting (VSTF) --- short-term forecasting (STF) --- medium-term forecasting (MTF) --- long-term forecasting (LTF) --- asynchronous motor --- linear active disturbance rejection control --- error differentiation --- vector control --- renewable energy --- solar power plant --- Data Envelopment Analysis (DEA) --- Fuzzy Analytical Network Process (FANP) --- Fuzzy Theory


Book
Applied Neural Networks and Fuzzy Logic in Power Electronics, Motor Drives, Renewable Energy Systems and Smart Grids
Authors: ---
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

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Bookmark

Abstract

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.

Keywords

History of engineering & technology --- droop curve --- frequency regulation --- fuzzy logic --- the rate of change of frequency --- reserve power --- smart grid --- energy Internet --- convolutional neural network --- decision optimization --- deep reinforcement learning --- electric load forecasting --- non-dominated sorting genetic algorithm II --- multi-layer perceptron --- adaptive neuro-fuzzy inference system --- meta-heuristic algorithms --- automatic generation control --- fuzzy neural network control --- thermostatically controlled loads --- back propagation algorithm --- particle swarm optimization --- load disaggregation --- artificial intelligence --- cognitive meters --- machine learning --- state machine --- NILM --- non-technical losses --- semi-supervised learning --- knowledge embed --- deep learning --- distribution network equipment --- condition assessment --- multi information source --- fuzzy iteration --- current balancing algorithm --- level-shifted SPWM --- medium-voltage applications --- multilevel current source inverter --- motor drives --- phase-shifted carrier SPWM --- STATCOM --- electricity forecasting --- CNN–LSTM --- very short-term forecasting (VSTF) --- short-term forecasting (STF) --- medium-term forecasting (MTF) --- long-term forecasting (LTF) --- asynchronous motor --- linear active disturbance rejection control --- error differentiation --- vector control --- renewable energy --- solar power plant --- Data Envelopment Analysis (DEA) --- Fuzzy Analytical Network Process (FANP) --- Fuzzy Theory


Book
Power Electronics in Renewable Energy Systems
Authors: ---
ISBN: 3039210459 3039210440 Year: 2019 Publisher: MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

This book offers a collection of 30 scientific papers which address the problems associated with the use of power electronic converters in renewable energy source-based systems. Relevant problems associated with the use of power electronic converters to integrate renewable energy systems to the power grid are presented. Some of the covered topics relate to the integration of photovoltaic and wind energy generators into the rest of the system, and to the use of energy storage to mitigate power fluctuations, which are a characteristic of renewable energy systems. The book provides a good overview of the abovementioned topics.

Keywords

n/a --- washout filter --- turbine and generator --- unbalanced power grid --- PV --- transient dynamics --- multi-input single output (MISO) --- permanent magnet synchronous generator (PMSG) --- static frequency characteristics --- impedance analysis --- FACTS devices --- coordinated control --- improved additional frequency control --- experiment --- resonant controller --- two-stage photovoltaic power --- voltage cancellation --- energy --- power matching --- LCL filter --- adaptive-MPPT (maximum power point tracking) --- VSC --- active power filter --- perturb and observe --- coordination control --- voltage-type control --- multiple VSGs --- wind power prediction --- linear quadratic regulator --- multiport converter (MPC) --- grid support function --- power ripple elimination --- adaptive resonant controller --- phase space reconstruction --- sliding mode control --- impedance emulation --- photovoltaic systems --- grid-connected converter --- SVM --- photovoltaic generators --- power grid --- active front-end converter --- THD --- type-4 wind turbine --- inertia --- ROCOF --- microgrid --- coupled oscillators --- multilevel power converter --- DC-AC power converters --- internal model --- back-to-back converter --- duty-ratio constraints --- selective harmonic mitigation --- parallel inverters --- discontinuous conduction mode --- droop control --- step size --- grid-connected --- inverter --- short-circuit fault --- energy router --- oscillation mitigation --- improved-VSG (virtual synchronous generator) --- source and load impedance --- synchronverter --- digital signal processor (DSP) TMS320F28335 --- operation optimization --- battery-energy storage --- generator speed control --- electrical power generation --- virtual impedance --- weak grid --- doubly-fed induction generator --- grid synchronization --- Energy Internet --- open circuit voltage --- state-of-charge balancing --- renewable power system --- control strategies --- adaptive notch filter (ANF) --- renewable energy --- hardware in the loop (HIL) --- energy storage --- microgrids --- inertia and damping characteristics --- electric vehicle --- multi-energy complementary --- static compensator --- stability --- battery energy storage system --- power-hardware-in- the-loop --- electricity price --- notch filter --- time series --- distorted grid --- oscillation suppression --- phase-locked loop (PLL) --- modules --- organic Rankine cycle --- failure zone --- Opal-RT Technologies® --- distributed generation --- modular multilevel converter --- governor --- microgrid (MG) --- second-life battery --- thermoelectric generator --- stability analysis --- wind energy system --- variable coefficient regulation --- single ended primary inductor converter (SEPIC) --- error --- soft switching --- power electronics --- PLL --- SPWM --- virtual synchronous generator --- perturbation frequency --- phase shifted --- grid-connected inverter --- cloud computing --- low inertia --- boost converter --- impedance reshaping --- small-signal and transient stability --- speed control --- multivariate linear regression --- photovoltaic --- adaptive control --- frequency regulation --- variable power tracking control --- power converters --- maximum power point tracking --- virtual admittance --- synchronization --- peak-current-mode control --- dynamic modeling --- discontinuous operation mode --- demand response

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