Narrow your search

Library

FARO (2)

KU Leuven (2)

LUCA School of Arts (2)

Odisee (2)

Thomas More Kempen (2)

Thomas More Mechelen (2)

UCLL (2)

UGent (2)

ULB (2)

ULiège (2)

More...

Resource type

book (2)


Language

English (2)


Year
From To Submit

2020 (1)

2019 (1)

Listing 1 - 2 of 2
Sort by

Book
Distributed Energy Resources Management 2018
Authors: ---
ISBN: 3039281712 3039281704 Year: 2020 Publisher: MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

The Special Issue Distributed Energy Resources Management 2018 includes 13 papers, and is a continuation of the Special Issue Distributed Energy Resources Management. The success of the previous edition shows the unquestionable relevance of distributed energy resources in the operation of power and energy systems at both the distribution level and at the wider power system level. Improving the management of distributed energy resources makes it possible to accommodate the higher penetration of intermittent distributed generation and electric vehicle charging. Demand response programs, namely the ones with a distributed nature, allow the consumers to contribute to the increased system efficiency while receiving benefits. This book addresses the management of distributed energy resources, with a focus on methods and techniques to achieve an optimized operation, in order to aggregate the resources namely in the scope of virtual power players and other types of aggregators, and to remunerate them. The integration of distributed resources in electricity markets is also addressed as an enabler for their increased and efficient use.

Keywords

n/a --- virtual power plant --- bidding strategy --- local flexibility market --- multi-period optimal power flow --- flexibility service --- occupant comfort --- unbalanced networks --- decentralized energy management system --- autonomous control --- optimization --- energy storage --- microgrids --- energy efficiency --- distributed energy --- control system --- DSM --- optimal scheduling --- adaptability --- synergistic optimization strategy --- teaching-learning --- distributed generation --- energy storage system --- stackelberg dynamic game --- IoT (Internet of Things) --- supply and demand --- comprehensive benefits --- distributed generator --- frequency bus-signaling --- active distribution networks --- swarm intelligence --- wind --- multi-agent technology --- solar --- power system management --- fault-tolerant control --- indoor environment quality --- multi-temporal optimal power flow --- multi-agent synergetic estimation --- smart grids --- local energy trading --- active power control --- prosumer --- microgrid --- trade agreements --- healthy building --- smart grid --- nonlinear control --- algorithm design and analysis --- batteries --- droop control --- distributed energy resources --- aggregator --- multi-agent system --- frequency control --- particle swarm optimization --- distribution system operator --- building climate control --- low voltage networks --- demand Response --- clustering --- distributed coordination --- demand-side management --- demand response


Book
Intelligent Control in Energy Systems
Author:
ISBN: 3039214160 3039214152 Year: 2019 Publisher: MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

The editors of this Special Issue titled “Intelligent Control in Energy Systems” have attempted to create a book containing original technical articles addressing various elements of intelligent control in energy systems. In response to our call for papers, we received 60 submissions. Of those submissions, 27 were published and 33 were rejected. In this book, we offer the 27 accepted technical articles as well as one editorial. Authors from 15 countries (China, Netherlands, Spain, Tunisia, United Sates of America, Korea, Brazil, Egypt, Denmark, Indonesia, Oman, Canada, Algeria, Mexico, and the Czech Republic) elaborate on several aspects of intelligent control in energy systems. The book covers a broad range of topics including fuzzy PID in automotive fuel cell and MPPT tracking, neural networks for fuel cell control and dynamic optimization of energy management, adaptive control on power systems, hierarchical Petri Nets in microgrid management, model predictive control for electric vehicle battery and frequency regulation in HVAC systems, deep learning for power consumption forecasting, decision trees for wind systems, risk analysis for demand side management, finite state automata for HVAC control, robust ?-synthesis for microgrids, and neuro-fuzzy systems in energy storage.

Keywords

energy management system --- artificial neural network --- control architecture --- intelligent buildings --- sensitivity analysis --- neural networks --- active balance --- photovoltaic system --- fast frequency response --- artificial intelligence --- MPPT operation --- model uncertainty --- load frequency control --- decision tree --- multi-agent control --- hybrid power plant --- Fault Ride Through Capability --- optimization --- small scale compressed air energy storage (SS-CAES) --- smart micro-grid --- current distortion --- hybrid electric vehicle --- parameter estimation --- railway --- ANFIS --- solar monitoring system --- urban microgrids --- phase-load balancing --- model reduction --- high-speed railway --- energy internet --- coordination of reserves --- differential evolution --- photovoltaic array --- ancillary service --- adjacent areas --- instantaneous optimization minimum power loss --- model predictive control --- HVAC systems --- sliding mode control --- MPPT: maximum power point tracking --- power oscillations --- thyristor --- interaction minimization --- occupancy model --- fuzzy logic controller --- power transformer winding --- RLS --- integrated energy systems --- vibration characteristics --- battery safety --- error estimation --- error compensation --- static friction --- convolutional neural network --- forecasting --- continuous voltage control --- medium voltage --- bridgeless SEPIC PFC converter --- building climate control --- PEM fuel cell --- proton exchange membrane fuel cell --- compound structured permanent-magnet motor --- occupancy-based control --- four phases interleaved boost converter --- long short term memory --- line switching --- lithium-ion battery pack --- back propagation (BP) neural network --- doubly-fed induction generator --- double forgetting factors --- current controller design --- repetitive controller --- exhaust gas recirculation (EGR) valve system --- neural network controller --- step-up boost converter --- internal short circuit resistance --- electric power consumption --- electric vehicle --- multiphysical field analysis --- energy efficiency --- multi-energy complementary --- system identification --- ?-synthesis --- network sensitivity --- intelligent control --- ?-class function --- frequency support --- multi-step forecasting --- frequency containment reserve --- orthogonal least square --- rule-based control --- industrial process --- hierarchical Petri nets --- wind integrated power system --- probabilistic power flow --- voltage controlling --- adaptive backstepping --- AC-DC converters --- line loss --- demand side management --- energy systems --- short-circuit experiment --- winding-fault characteristics --- neutral section --- stochastic power system operating point drift --- neural network algorithm --- operation limit violations --- fractional order fuzzy PID controller --- preventive control --- AC static switch --- battery packs --- model-based fault detection --- automotive application --- nonlinear power systems --- adaptive damping control --- pilot point --- energy management --- position control --- frequency control dead band --- fuzzy --- voltage violations --- distribution network planning --- frequency regulation --- energy management strategy --- multiple-point control --- electric meter --- polynomial expansion --- commercial/residential buildings --- system modelling --- three-stage --- soft internal short circuit --- demand response

Listing 1 - 2 of 2
Sort by