04674nam 2201069z- 450 991040408060332120231214132853.03-03928-111-9(CKB)4100000011302332(oapen)https://directory.doabooks.org/handle/20.500.12854/40816(EXLCZ)99410000001130233220202102d2020 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierAnalysis for Power Quality MonitoringMDPI - Multidisciplinary Digital Publishing Institute20201 electronic resource (210 p.)3-03928-110-0 We are immersed in the so-called digital energy network, continuously introducing new technological advances for a better way of life. Numerous emerging words are in the spotlight, namely: Internet of Things (IoT), Big Data, Smart Cities, Smart Grid, Industry 4.0, etc. To achieve this formidable goal, systems should work more efficiently, and this fact inevitably leads to power quality (PQ) assurance. Apart from its economic losses, a bad PQ implies serious risks for machines, and consequently for people. Many researchers are endeavoring to develop new analysis techniques, instruments, measurement methods, and new indices and norms that match and fulfil the requirements regarding the current operation of the electrical network. This book offers a compilation of the some recent advances in this field. The chapters range from computing issues to technological implementations, going through event detection strategies and new indices and measurement methods that contribute significantly to the advancement of PQ analysis. Experiments have been developed within the frames of research units and projects, and deal with real data from industry and public buildings. Human beings have an unavoidable commitment with sustainability, which implies adapting PQ monitoring techniques to our dynamic world, defining a digital and smart concept of quality for electricity.modulationFPGAflickerDC power quality indiceslimited resources hardwarelow cost monitordynamic phasor estimationharmonicsRMS voltage estimationislanding operationembedded systemsignal waveform compressionbig datadigital signal processingdata scalabilitydata compressionwind-grid distributionvoltage fluctuationssmart grid (SG) applicationspower event detectionmodellingvoltage ripplepower quality monitoringhigher-order statistics (HOS)power distribution systemspower quality disturbancesreconfigurable computingoperation analysissensor nodepower quality (PQ)distribution networkswireless sensor networkreliabilitypower system measurementsembedded microcontrollerphasor measurement unitsIoTsoft computingsmart gridspower quality monitorinduction machinessensors and instruments for PQKalman filterslow-voltage DC networksconvolution neural networkspectral kurtosismunicipal distribution networkstatistical signal processingdetectionpower quality disturbancesmart gridenergizing warningdense-mesh topologylow computational costfourth-order statisticsPQ indices and thresholdsmachine learningvoltage sagspower qualitycomputational solutions for advanced metering infrastructure (AMI)constant amplitude trendphasor measurementimproved principal component analysislong-termGonzález de la Rosa Juan-Joséauth1267785Donsión Manuel PérezauthBOOK9910404080603321Analysis for Power Quality Monitoring3035779UNINA05052nam 22006375 450 991025495360332120200706163039.03-319-27523-210.1007/978-3-319-27523-9(CKB)3710000000651978(EBL)4514226(DE-He213)978-3-319-27523-9(MiAaPQ)EBC4514226(PPN)228320909(EXLCZ)99371000000065197820160425d2016 u| 0engur|n|---|||||txtrdacontentcrdamediacrrdacarrierAdvanced Planning and Scheduling in Manufacturing and Supply Chains /by Yuri Mauergauz1st ed. 2016.Cham :Springer International Publishing :Imprint: Springer,2016.1 online resource (584 p.)Description based upon print version of record.3-319-27521-6 Includes bibliographical references at the end of each chapters.Part 1. Modelling -- 1.Reference Models -- Chapter 2.Mathematical Models -- Chapter 3.Production Bottlenecks Models -- 4. Multi-Criteria Models and Decision Making -- 5.Planning Inputs -- 6.Demand Forecasting -- 7.Examples of Advanced Planning Models -- Part II. Planning Processes -- 8.Single-Echelon Inventory Planning -- 9.Supply Chain Inventory Dynamics -- 10.Planning of Supplies to Consumers -- 11.Lot Sizing -- 12.Production Scheduling -- 13.Shop Floor Scheduling: Single-Stage Problems -- 14.Shop Floor Scheduling: Multi-Stage Problems -- 15.Multi-Criteria Scheduling -- Schedule 1.Legend -- Schedule 2.Abbreviations and Definitions -- Schedule 3.Schedule Classification Parameters -- Schedule 4.Production Intensity Integral Calculations -- Schedule 5.Planning Software.This book is a guide to modern production planning methods based on new scientific achievements and various practical planning rules of thumb. Several numerical examples illustrate most of the calculation methods, while the text includes a set of programs for calculating production schedules and an example of a cloud-based enterprise resource planning (ERP) system. Despite the relatively large number of books dedicated to this topic, Advanced Planning and Scheduling is the first book of its kind to feature such a wide range of information in a single work, a fact that inspired the author to write this book and publish an English translation. This work consists of two parts, with the first part addressing the design of reference and mathematical models, bottleneck models and multi-criteria models and presenting various sample models. It describes demand-forecasting methods and also includes considerations for aggregating forecasts. Lastly, it provides reference information on methods for data stocking and sorting. The second part of the book analyzes various stock planning models and the rules of safety stock calculation, while also considering the stock traffic dynamics in supply chains. Various batch computation methods are described in detail, while production planning is considered on several levels, including supply planning for customers, master planning, and production scheduling. This book can be used as a reference and manual for current planning methods. It is aimed at production planning department managers, company information system specialists, as well as scientists and PhD students conducting research in production planning. It will also be a valuable resource for students at universities of applied sciences.Production managementMathematical modelsEngineering economicsEngineering economyOperations researchDecision makingOperations Managementhttps://scigraph.springernature.com/ontologies/product-market-codes/519000Mathematical Modeling and Industrial Mathematicshttps://scigraph.springernature.com/ontologies/product-market-codes/M14068Engineering Economics, Organization, Logistics, Marketinghttps://scigraph.springernature.com/ontologies/product-market-codes/T22016Operations Research/Decision Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/521000Production management.Mathematical models.Engineering economics.Engineering economy.Operations research.Decision making.Operations Management.Mathematical Modeling and Industrial Mathematics.Engineering Economics, Organization, Logistics, Marketing.Operations Research/Decision Theory.650Mauergauz Yuriauthttp://id.loc.gov/vocabulary/relators/aut972621BOOK9910254953603321Advanced Planning and Scheduling in Manufacturing and Supply Chains2212286UNINA