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Integration of photovoltaics and electrification in agriculture. Works on the integration of photovoltaics in agriculture, as well as electrification and microgrids in agriculture. In addition, some works on sustainability in agriculture are added.

transpiration --- PV heat conversion --- plant heat stress --- agrivoltaic system --- sustainable integration --- thermal analysis --- sustainable agriculture --- nexus approach --- rural development --- solar micro-grid --- techno-economic impact --- agrivoltaics --- solar energy --- agriculture --- energy innovation --- technology adoption --- photovoltaics --- extraterrestrial solar irradiation --- global, beam and diffuse solar components --- ground-reflected solar radiation --- horizontal, tilted and oriented solar irradiation --- solar photovoltaics --- agricultural robots --- Agri 4.0 --- battery-based farm machinery --- mobile irrigation system --- smart water sprinklers --- smart pesticide sprayers --- multi-purpose farming robots --- agrophotovoltaic --- agrivoltaic --- dual-land use --- solar sharing --- solar photovoltaic energy --- water–food–energy nexus --- fuses coordination --- protection device --- distributed generation --- distribution network --- photovoltaic --- DIgSILENT --- Agri-PV --- shading --- crop performance --- yields --- product quality --- organic agriculture --- biodynamic agriculture --- land productivity --- localization --- link budget --- spreading factor --- range --- LoRa --- node sensitivity --- SNR --- sustainable greenhouse --- semi-transparent photovoltaic panels --- amorphous silicon --- building-integrated photovoltaics --- microgrid --- organic photovoltaics --- greenhouses --- tomato --- arid region --- food-energy nexus --- solar-powered irrigation --- benefit-cost ratio --- land equivalent ratio --- n/a --- water-food-energy nexus

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The principal advantage of smart electricity meters is their ability to transfer digitized electricity consumption data to remote processing systems. The data collected by these devices make the realization of many novel use cases possible, providing benefits to electricity providers and customers alike. This book includes 14 research articles that explore and exploit the information content of smart meter data, and provides insights into the realization of new digital solutions and services that support the transition towards a sustainable energy system. This volume has been edited by Andreas Reinhardt, head of the Energy Informatics research group at Technische Universität Clausthal, Germany, and Lucas Pereira, research fellow at Técnico Lisboa, Portugal.

Technology: general issues --- smart grid --- nontechnical losses --- electricity theft detection --- synthetic minority oversampling technique --- K-means cluster --- random forest --- smart grids --- smart energy system --- smart meter --- GDPR --- data privacy --- ethics --- multi-label learning --- Non-intrusive Load Monitoring --- appliance recognition --- fryze power theory --- V-I trajectory --- Convolutional Neural Network --- distance similarity matrix --- activation current --- electric vehicle --- synthetic data --- exponential distribution --- Poisson distribution --- Gaussian mixture models --- mathematical modeling --- machine learning --- simulation --- Non-Intrusive Load Monitoring (NILM) --- NILM datasets --- power signature --- electric load simulation --- data-driven approaches --- smart meters --- text convolutional neural networks (TextCNN) --- time-series classification --- data annotation --- non-intrusive load monitoring --- semi-automatic labeling --- appliance load signatures --- ambient influences --- device classification accuracy --- NILM --- signature --- load disaggregation --- transients --- pulse generator --- smart metering --- smart power grids --- power consumption data --- energy data processing --- user-centric applications of energy data --- convolutional neural network --- energy consumption --- energy data analytics --- energy disaggregation --- real-time --- smart meter data --- transient load signature --- attention mechanism --- deep neural network --- electrical energy --- load scheduling --- satisfaction --- Shapley Value --- solar photovoltaics --- review --- deep learning --- deep neural networks --- smart grid --- nontechnical losses --- electricity theft detection --- synthetic minority oversampling technique --- K-means cluster --- random forest --- smart grids --- smart energy system --- smart meter --- GDPR --- data privacy --- ethics --- multi-label learning --- Non-intrusive Load Monitoring --- appliance recognition --- fryze power theory --- V-I trajectory --- Convolutional Neural Network --- distance similarity matrix --- activation current --- electric vehicle --- synthetic data --- exponential distribution --- Poisson distribution --- Gaussian mixture models --- mathematical modeling --- machine learning --- simulation --- Non-Intrusive Load Monitoring (NILM) --- NILM datasets --- power signature --- electric load simulation --- data-driven approaches --- smart meters --- text convolutional neural networks (TextCNN) --- time-series classification --- data annotation --- non-intrusive load monitoring --- semi-automatic labeling --- appliance load signatures --- ambient influences --- device classification accuracy --- NILM --- signature --- load disaggregation --- transients --- pulse generator --- smart metering --- smart power grids --- power consumption data --- energy data processing --- user-centric applications of energy data --- convolutional neural network --- energy consumption --- energy data analytics --- energy disaggregation --- real-time --- smart meter data --- transient load signature --- attention mechanism --- deep neural network --- electrical energy --- load scheduling --- satisfaction --- Shapley Value --- solar photovoltaics --- review --- deep learning --- deep neural networks

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The principal advantage of smart electricity meters is their ability to transfer digitized electricity consumption data to remote processing systems. The data collected by these devices make the realization of many novel use cases possible, providing benefits to electricity providers and customers alike. This book includes 14 research articles that explore and exploit the information content of smart meter data, and provides insights into the realization of new digital solutions and services that support the transition towards a sustainable energy system. This volume has been edited by Andreas Reinhardt, head of the Energy Informatics research group at Technische Universität Clausthal, Germany, and Lucas Pereira, research fellow at Técnico Lisboa, Portugal.

Technology: general issues --- smart grid --- nontechnical losses --- electricity theft detection --- synthetic minority oversampling technique --- K-means cluster --- random forest --- smart grids --- smart energy system --- smart meter --- GDPR --- data privacy --- ethics --- multi-label learning --- Non-intrusive Load Monitoring --- appliance recognition --- fryze power theory --- V-I trajectory --- Convolutional Neural Network --- distance similarity matrix --- activation current --- electric vehicle --- synthetic data --- exponential distribution --- Poisson distribution --- Gaussian mixture models --- mathematical modeling --- machine learning --- simulation --- Non-Intrusive Load Monitoring (NILM) --- NILM datasets --- power signature --- electric load simulation --- data-driven approaches --- smart meters --- text convolutional neural networks (TextCNN) --- time-series classification --- data annotation --- non-intrusive load monitoring --- semi-automatic labeling --- appliance load signatures --- ambient influences --- device classification accuracy --- NILM --- signature --- load disaggregation --- transients --- pulse generator --- smart metering --- smart power grids --- power consumption data --- energy data processing --- user-centric applications of energy data --- convolutional neural network --- energy consumption --- energy data analytics --- energy disaggregation --- real-time --- smart meter data --- transient load signature --- attention mechanism --- deep neural network --- electrical energy --- load scheduling --- satisfaction --- Shapley Value --- solar photovoltaics --- review --- deep learning --- deep neural networks --- n/a

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The principal advantage of smart electricity meters is their ability to transfer digitized electricity consumption data to remote processing systems. The data collected by these devices make the realization of many novel use cases possible, providing benefits to electricity providers and customers alike. This book includes 14 research articles that explore and exploit the information content of smart meter data, and provides insights into the realization of new digital solutions and services that support the transition towards a sustainable energy system. This volume has been edited by Andreas Reinhardt, head of the Energy Informatics research group at Technische Universität Clausthal, Germany, and Lucas Pereira, research fellow at Técnico Lisboa, Portugal.

smart grid --- nontechnical losses --- electricity theft detection --- synthetic minority oversampling technique --- K-means cluster --- random forest --- smart grids --- smart energy system --- smart meter --- GDPR --- data privacy --- ethics --- multi-label learning --- Non-intrusive Load Monitoring --- appliance recognition --- fryze power theory --- V-I trajectory --- Convolutional Neural Network --- distance similarity matrix --- activation current --- electric vehicle --- synthetic data --- exponential distribution --- Poisson distribution --- Gaussian mixture models --- mathematical modeling --- machine learning --- simulation --- Non-Intrusive Load Monitoring (NILM) --- NILM datasets --- power signature --- electric load simulation --- data-driven approaches --- smart meters --- text convolutional neural networks (TextCNN) --- time-series classification --- data annotation --- non-intrusive load monitoring --- semi-automatic labeling --- appliance load signatures --- ambient influences --- device classification accuracy --- NILM --- signature --- load disaggregation --- transients --- pulse generator --- smart metering --- smart power grids --- power consumption data --- energy data processing --- user-centric applications of energy data --- convolutional neural network --- energy consumption --- energy data analytics --- energy disaggregation --- real-time --- smart meter data --- transient load signature --- attention mechanism --- deep neural network --- electrical energy --- load scheduling --- satisfaction --- Shapley Value --- solar photovoltaics --- review --- deep learning --- deep neural networks --- n/a

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The pandemic period has caused severe socio-economic damage, but it is accompanied by environmental deterioration that can also affect economic opportunities and social equity. In the face of this double risk, future generations are ready to be resilient and make their contribution not only on the consumption side, but also through their inclusion in all companies by bringing green and circular principles with them. Policy makers can also favor this choice.

Technology: general issues --- mobility choice --- COVID-19 --- best-worst method --- multi-criteria decision making --- air pollution --- air quality --- health effects --- economic burden --- food system --- circular economy --- sustainability --- EU --- Twitter --- COVID-19 pandemic --- local community --- perception analysis --- econometric modeling --- data science --- reflexive governance --- climate change --- infrastructure --- urban resilience --- social sustainability --- economic sustainability --- environmental sustainability --- China --- business --- innovation ecosystem --- innovation strategy --- electric vehicle --- dominant design --- crisis --- pandemic --- higher education --- digitalization --- distance learning --- Covid-19 outbreak --- resilience --- strategic resilience --- multi-domain resilience --- strategic agility --- change --- sustainability strategy --- financialization --- TFP --- innovation --- resilience of city --- infectious disease --- urban planning --- supply chain resilience --- IT disruptions --- efficiency measurement --- warehouse logistics --- DEA --- resilient supply chains --- external capital --- customer-supplier relationship --- circular network --- cyber-security --- e-commerce --- Europe --- supply chain collaboration --- small- and medium-sized enterprises --- grey DEMATEL --- fuzzy best-worst method --- agrivoltaic system --- solar photovoltaics --- agronomic management --- crop production --- Food-Energy-Water nexus --- sustainable integration --- women's leadership --- America Latina --- small and medium-sized enterprises --- renewable energy --- sustainable electricity production --- socio-economic sustainability --- sustainable development goals --- emission level --- levelized cost --- gross domestic product --- pig farmers --- adoption willingness of IoT traceability technology --- Unified Theory of Acceptance and Use of Technology --- Latent Moderate Structural Equations --- biomethane --- natural gas grid --- bioenergy --- biogas --- gas supply decarbonization --- incentives --- competences --- digitization --- digital transformation --- Asia Pacific --- CO2 emission --- demand shock --- hypothetical extraction method --- input-output model --- sectoral linkage --- emerging cities --- sustainable operations --- case studies --- the Asian region --- resilience decisions --- cybersecurity --- consumers' awareness --- methodology --- mobility choice --- COVID-19 --- best-worst method --- multi-criteria decision making --- air pollution --- air quality --- health effects --- economic burden --- food system --- circular economy --- sustainability --- EU --- Twitter --- COVID-19 pandemic --- local community --- perception analysis --- econometric modeling --- data science --- reflexive governance --- climate change --- infrastructure --- urban resilience --- social sustainability --- economic sustainability --- environmental sustainability --- China --- business --- innovation ecosystem --- innovation strategy --- electric vehicle --- dominant design --- crisis --- pandemic --- higher education --- digitalization --- distance learning --- Covid-19 outbreak --- resilience --- strategic resilience --- multi-domain resilience --- strategic agility --- change --- sustainability strategy --- financialization --- TFP --- innovation --- resilience of city --- infectious disease --- urban planning --- supply chain resilience --- IT disruptions --- efficiency measurement --- warehouse logistics --- DEA --- resilient supply chains --- external capital --- customer-supplier relationship --- circular network --- cyber-security --- e-commerce --- Europe --- supply chain collaboration --- small- and medium-sized enterprises --- grey DEMATEL --- fuzzy best-worst method --- agrivoltaic system --- solar photovoltaics --- agronomic management --- crop production --- Food-Energy-Water nexus --- sustainable integration --- women's leadership --- America Latina --- small and medium-sized enterprises --- renewable energy --- sustainable electricity production --- socio-economic sustainability --- sustainable development goals --- emission level --- levelized cost --- gross domestic product --- pig farmers --- adoption willingness of IoT traceability technology --- Unified Theory of Acceptance and Use of Technology --- Latent Moderate Structural Equations --- biomethane --- natural gas grid --- bioenergy --- biogas --- gas supply decarbonization --- incentives --- competences --- digitization --- digital transformation --- Asia Pacific --- CO2 emission --- demand shock --- hypothetical extraction method --- input-output model --- sectoral linkage --- emerging cities --- sustainable operations --- case studies --- the Asian region --- resilience decisions --- cybersecurity --- consumers' awareness --- methodology