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Short-Term Load Forecasting by Artificial Intelligent Technologies

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ISBN: 9783038975823 9783038975830 Year: Pages: 444 DOI: 10.3390/books978-3-03897-583-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-01-29 10:55:39
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In last few decades, short-term load forecasting (STLF) has been one of the most important research issues for achieving higher efficiency and reliability in power system operation, to facilitate the minimization of its operation cost by providing accurate input to day-ahead scheduling, contingency analysis, load flow analysis, planning, and maintenance of power systems. There are lots of forecasting models proposed for STLF, including traditional statistical models (such as ARIMA, SARIMA, ARMAX, multi-variate regression, Kalman filter, exponential smoothing, and so on) and artificial-intelligence-based models (such as artificial neural networks (ANNs), knowledge-based expert systems, fuzzy theory and fuzzy inference systems, evolutionary computation models, support vector regression, and so on). Recently, due to the great development of evolutionary algorithms (EA) and novel computing concepts (e.g., quantum computing concepts, chaotic mapping functions, and cloud mapping process, and so on), many advanced hybrids with those artificial-intelligence-based models are also proposed to achieve satisfactory forecasting accuracy levels. In addition, combining some superior mechanisms with an existing model could empower that model to solve problems it could not deal with before; for example, the seasonal mechanism from the ARIMA model is a good component to be combined with any forecasting models to help them to deal with seasonal problems.

Exact and Heuristic Scheduling Algorithms

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ISBN: 9783039284689 9783039284696 Year: Pages: 200 DOI: 10.3390/books978-3-03928-469-6 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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This edited book presents new results in the area of the development of exact and heuristic scheduling algorithms. It contains eight articles accepted for publication for a Special Issue in the journal Algorithms. The book presents new algorithms, e.g., for flow shop, job shop, and parallel machine scheduling problems. The particular articles address subjects such as a heuristic for the routing and scheduling problem with time windows, applied to the automotive industry in Mexico, a heuristic for the blocking job shop problem with tardiness minimization based on new neighborhood structures, fast heuristics for the Euclidean traveling salesman problem or a new mathematical model for the period-aggregated resource leveling problem with variable job duration, and several others.

Brain-Computer Interfaces for Human Augmentation

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ISBN: 9783039219063 9783039219070 Year: Pages: 128 DOI: 10.3390/books978-3-03921-907-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Psychology
Added to DOAB on : 2019-12-09 11:49:16
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The field of Brain–Computer Interfaces (BCIs) has grown rapidly in the last few decades, allowing the development of faster and more reliable assistive technologies based on direct links between the brain and an external device. Novel applications of BCIs have also been proposed, especially in the area of human augmentation, i.e., enabling people to go beyond human limitations in sensory, cognitive and motor tasks. Brain-imaging techniques, such as electroencephalography, have been used to extract neural correlates of various brain processes and transform them, via machine learning, into commands for external devices. Brain stimulation technology has allowed to trigger the activation of specific brain areas to enhance the cognitive processes associated to the task at hand, hence improving performance. BCIs have therefore extended their scope from assistive technologies for people with disabilities to neuro-tools for human enhancement. This Special Issue aims at showing the recent advances in BCIs for human augmentation, highlighting new results on both traditional and novel applications. These include, but are not limited to, control of external devices, communication, cognitive enhancement, decision making and entertainment.

Ensemble Forecasting Applied to Power Systems

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ISBN: 9783039283125 9783039283132 Year: Pages: 134 DOI: 10.3390/books978-3-03928-313-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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Modern power systems are affected by many sources of uncertainty, driven by the spread of renewable generation, by the development of liberalized energy market systems and by the intrinsic random behavior of the final energy customers. Forecasting is, therefore, a crucial task in planning and managing modern power systems at any level: from transmission to distribution networks, and in also the new context of smart grids. Recent trends suggest the suitability of ensemble approaches in order to increase the versatility and robustness of forecasting systems. Stacking, boosting, and bagging techniques have recently started to attract the interest of power system practitioners. This book addresses the development of new, advanced, ensemble forecasting methods applied to power systems, collecting recent contributions to the development of accurate forecasts of energy-related variables by some of the most qualified experts in energy forecasting. Typical areas of research (renewable energy forecasting, load forecasting, energy price forecasting) are investigated, with relevant applications to the use of forecasts in energy management systems.

Computational Intelligence in Photovoltaic Systems

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ISBN: 9783039210985 9783039210992 Year: Pages: 180 DOI: 10.3390/books978-3-03921-099-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 16:10:12
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Photovoltaics, among the different renewable energy sources (RES), has become more popular. In recent years, however, many research topics have arisen as a result of the problems that are constantly faced in smart-grid and microgrid operations, such as forecasting of the output of power plant production, storage sizing, modeling, and control optimization of photovoltaic systems. Computational intelligence algorithms (evolutionary optimization, neural networks, fuzzy logic, etc.) have become more and more popular as alternative approaches to conventional techniques for solving problems such as modeling, identification, optimization, availability prediction, forecasting, sizing, and control of stand-alone, grid-connected, and hybrid photovoltaic systems. This Special Issue will investigate the most recent developments and research on solar power systems. This Special Issue “Computational Intelligence in Photovoltaic Systems” is highly recommended for readers with an interest in the various aspects of solar power systems, and includes 10 original research papers covering relevant progress in the following (non-exhaustive) fields: Forecasting techniques (deterministic, stochastic, etc.); DC/AC converter control and maximum power point tracking techniques; Sizing and optimization of photovoltaic system components; Photovoltaics modeling and parameter estimation; Maintenance and reliability modeling; Decision processes for grid operators.

Control of Multiphase Machines and Drives

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ISBN: 9783039281367 9783039281374 Year: Pages: 146 DOI: 10.3390/books978-3-03928-137-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-01-30 16:39:46
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With the growing interest in electrical machines in recent times, the multiphase machine field has developed into a fascinating research area. Their intrinsic features (power splitting, better fault tolerance, or lower torque ripple) make them an appealing competitor to conventional three-phase machines. Multiphase electric drives have been recently used in applications where fault tolerance and continuous operation of the drive are required. However, the difficulties in extending the three-phase conventional current regulation and control structure to multiphase systems still limit their broad applicability in industry solutions. The main objective of this book is to illustrate new advances, developments, and applications in the field of multiphase machines and drives, while exposing these advances, developments, and applications to the scientific community and industry.

Smart Energy Management for Smart Grids

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ISBN: 9783039281428 9783039281435 Year: Pages: 350 DOI: 10.3390/books978-3-03928-143-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book.

Keywords

seawater pumped storage --- renewable energy --- active distribution networks --- two-stage --- scheduling --- distributed generation --- storage device --- MILP --- ToU tariff --- optimization --- daily consumption curve --- peak/off-peak --- programmable appliances --- smart grid --- smart energy --- sustainability --- values --- technology acceptance --- technology adoption --- smart grid --- Smart Grid Station --- renewable energy sources --- energy management system --- smart metering --- feedback --- households --- energy and water consumption --- theories of social practice --- smart grid --- differentiation --- development demand --- comprehensive evaluation --- energy management system --- energy storage system --- semantic web technologies --- rules --- ontology --- engineering support --- smart grid architecture model --- model driven architecture --- IEC 61850 --- IEC 61499 --- energy storage system --- electricity charge discount program --- peak reduction --- economic feasibility analysis --- policy effectiveness evaluation --- occupant behavior --- single-person household --- energy consumption --- Korean Time Use Survey --- EnergyPlus --- data mining --- K-modes clustering --- support vector machine --- Gaussian process regression --- combined dispatch (CD) strategy --- optimization --- HOMER --- net present cost (NPC) --- sensitivity analysis --- renewable energy --- solar power generation prediction --- smart grid --- photovoltaic power --- machine learning --- electrical distribution system --- graph theory --- micro grids --- heuristic --- optimization --- planning --- unbalanced three-phase distribution networks --- optimal power flows --- genetic algorithm --- holomorphic embedding load flow method --- simulation --- forecasting --- solar generation --- storage capacity --- game theory --- nash equilibrium --- distributed energy management algorithm --- micro grid --- meta heuristic techniques --- R&amp --- D planning --- patent analysis --- sustainable smart grid technology --- R&amp --- D strategy --- STEEP analysis --- scenario planning --- electric vehicle charging technology --- multilayer perceptron neural network --- support vector machine --- cyberattacks --- optimal power flow --- smart grid security --- intruder detection system

Autonomous Control of Unmanned Aerial Vehicles

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ISBN: 9783039210305 9783039210312 Year: Pages: 270 DOI: 10.3390/books978-3-03921-031-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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Unmanned aerial vehicles (UAVs) are being increasingly used in different applications in both military and civilian domains. These applications include surveillance, reconnaissance, remote sensing, target acquisition, border patrol, infrastructure monitoring, aerial imaging, industrial inspection, and emergency medical aid. Vehicles that can be considered autonomous must be able to make decisions and react to events without direct intervention by humans. Although some UAVs are able to perform increasingly complex autonomous manoeuvres, most UAVs are not fully autonomous; instead, they are mostly operated remotely by humans. To make UAVs fully autonomous, many technological and algorithmic developments are still required. For instance, UAVs will need to improve their sensing of obstacles and subsequent avoidance. This becomes particularly important as autonomous UAVs start to operate in civilian airspaces that are occupied by other aircraft. The aim of this volume is to bring together the work of leading researchers and practitioners in the field of unmanned aerial vehicles with a common interest in their autonomy. The contributions that are part of this volume present key challenges associated with the autonomous control of unmanned aerial vehicles, and propose solution methodologies to address such challenges, analyse the proposed methodologies, and evaluate their performance.

Control and Nonlinear Dynamics on Energy Conversion Systems

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ISBN: 9783039211104 9783039211111 Year: Pages: 438 DOI: 10.3390/books978-3-03921-111-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-08-28 11:21:27
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The ever-increasing need for higher efficiency, smaller size, and lower cost make the analysis, understanding, and design of energy conversion systems extremely important, interesting, and even imperative. One of the most neglected features in the study of such systems is the effect of the inherent nonlinearities on the stability of the system. Due to these nonlinearities, these devices may exhibit undesirable and complex dynamics, which are the focus of many researchers. Even though a lot of research has taken place in this area during the last 20 years, it is still an active research topic for mainstream power engineers. This research has demonstrated that these systems can become unstable with a direct result in increased losses, extra subharmonics, and even uncontrollability/unobservability. The detailed study of these systems can help in the design of smaller, lighter, and less expensive converters that are particularly important in emerging areas of research like electric vehicles, smart grids, renewable energy sources, and others. The aim of this Special Issue is to cover control and nonlinear aspects of instabilities in different energy conversion systems: theoretical, analysis modelling, and practical solutions for such emerging applications. In this Special Issue, we present novel research works in different areas of the control and nonlinear dynamics of energy conversion systems.

Keywords

data-driven --- prediction --- neural network --- air-handling unit (AHU) --- supply air temperature --- pulverizing system --- soft sensor --- inferential control --- moving horizon estimation --- multi-model predictive control --- micro-grid --- droop control --- virtual impedance --- harmonic suppression --- power quality --- combined heat and power unit --- two-stage bypass --- dynamic model --- coordinated control system --- predictive control --- decoupling control --- power conversion --- model–plant mismatches --- disturbance observer --- performance recovery --- offset-free --- electrical machine --- electromagnetic vibration --- multiphysics --- rotor dynamics --- air gap eccentricity --- calculation method --- magnetic saturation --- corrugated pipe --- whistling noise --- Helmholtz number --- excited modes --- switched reluctance generator --- capacitance current pulse train control --- voltage ripple --- capacitance current --- feedback coefficient --- distributed architecture --- maximum power point tracking --- sliding mode control --- overvoltage --- permanent magnet synchronous motor (PMSM) --- single artificial neuron goal representation heuristic dynamic programming (SAN-GrHDP) --- single artificial neuron (SAN) --- reinforcement learning (RL) --- goal representation heuristic dynamic programming (GrHDP) --- adaptive dynamic programming (ADP) --- sliding mode observer (SMO) --- permanent magnet synchronous motor (PMSM) --- extended back electromotive force (EEMF) --- position sensorless --- bridgeless converter --- discontinuous conduction mode (DCM) --- high step-up voltage gain --- power factor correction (PFC) --- space mechanism --- multi-clearance --- nonlinear dynamic model --- planetary gears --- vibration characteristics --- new step-up converter --- ultrahigh voltage conversion ratio --- small-signal model --- average-current mode control --- slope compensation --- monodromy matrix --- current mode control --- boost-flyback converter --- explosion-magnetic generator --- plasma accelerator --- current-pulse formation --- DC-DC buck converter --- contraction analysis --- global stability --- matrix norm --- DC micro grid --- efficiency optimization --- variable bus voltage MG --- variable switching frequency DC-DC converters --- centralized vs. decentralized control --- local vs. global optimization --- buck converter --- DC motor --- bifurcations in control parameter --- sliding control --- zero average dynamics --- fixed-point inducting control --- DC-DC converters --- quadratic boost --- maximum power point tracking (MPPT) --- nonlinear dynamics --- subharmonic oscillations --- photovoltaic (PV) --- steel catenary riser --- rigid body rotation --- wave --- the load of suspension point in the z direction --- Cable3D

Swarm Robotics

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ISBN: 9783038979227 9783038979234 Year: Pages: 310 DOI: 10.3390/books978-3-03897-923-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-06-26 08:44:06
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Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties:

Keywords

3D model identification --- shape normalization --- weighted implicit shape representation --- panoramic view --- scale-invariant feature transform --- optimization --- meta-heuristic --- parallel technique --- Swarm intelligence algorithm --- artificial flora (AF) algorithm --- bionic intelligent algorithm --- particle swarm optimization --- artificial bee colony algorithm --- swarm robotics --- search --- surveillance --- behaviors --- patterns --- comparison --- swarm behavior --- Swarm Chemistry --- self-organization --- asymmetrical interaction --- genetic algorithm --- cooperative target hunting --- multi-AUV --- improved potential field --- surface-water environment --- signal source localization --- multi-robot system --- event-triggered communication --- consensus control --- time-difference-of-arrival (TDOA) --- Cramer–Rao low bound (CRLB) --- optimal configuration --- UAV swarms --- path optimization --- multiple robots --- formation --- sliding mode controller --- nonlinear disturbance observer --- system stability --- formation control --- virtual structure --- formation reconfiguration --- multi-agents --- robotics --- unmanned aerial vehicle --- swarm intelligence --- particle swarm optimization --- search algorithm --- underwater environment --- sensor deployment --- event-driven coverage --- fish swarm optimization --- congestion control --- modular robots --- self-assembly robots --- environmental perception --- target recognition --- autonomous docking --- formation control --- virtual linkage --- virtual structure --- formation reconfiguration --- mobile robots --- robotics --- swarm robotics --- formation control --- coordinate motion --- obstacle avoidance --- n/a

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