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This Special Issue “Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) Technologies” was in session from 1 May 2019 to 31 May 2020. For this Special issue, we invited articles on current state-of-the-art technologies and solutions in G2V and V2G, including but not limited to the operation and control of gridable vehicles, energy storage and management systems, charging infrastructure and chargers, EV demand and load forecasting, V2G interfaces and applications, V2G and energy reliability and security, environmental impacts, and economic benefits as well as demonstration projects and case studies in the aforementioned areas. Articles that deal with the latest hot topics in V2G are of particular interest, such as V2G and demand-side response control technique, smart charging infrastructure and grid planning, advanced power electronics for V2G systems, adaptation of V2G systems in the smart grid, adaptation of smart cities for a large number of EVs, integration, and the optimization of V2G systems, utilities and transportation assets for advanced V2G systems, wireless power transfer systems for advanced V2G systems, fault detection, maintenance and diagnostics in V2G processes, communications protocols for V2G systems, energy management system (EMS) in V2G systems, IoT for V2G systems, distributed energy and storage systems for V2G, transportation networks and V2G, energy management for V2G, smart charging/discharging stations for efficient V2G, environmental and socio-economic benefits and challenges of V2G systems, and building integrated V2G systems (BIV2G). Five manuscripts are published in this Special Issue, including “An Ensemble Stochastic Forecasting Framework for Variable Distributed Demand Loads” by Agyeman et al., “Where Will You Park? Predicting Vehicle Locations for Vehicle-to-Grid, An MPC Scheme with Enhanced Active Voltage Vector Region for V2G Inverter” by Shipman et al., “Electric Vehicles Energy Management with V2G/G2V Multifactor Optimization of Smart Grids” by Xia et al., and “A Review on Communication Standards and Charging Topologies of V2G and V2H Operation Strategies” by Savitti et al.

History of engineering & technology --- vehicle-to-grid (V2G) --- vehicle-to-home (V2H) --- bi-directional charging topologies --- communication standards --- battery cycle --- smart grid --- optimization --- energy management --- electric vehicles --- distributed generation --- MPC --- AV2R --- V2G --- inverter --- vehicle-to-grid --- vehicle location prediction --- automated machine learning --- machine learning --- Bayesian --- deep neural network --- demand load forecast --- distributed load --- ensemble algorithm stochastic --- K-means --- vehicle-to-grid (V2G) --- vehicle-to-home (V2H) --- bi-directional charging topologies --- communication standards --- battery cycle --- smart grid --- optimization --- energy management --- electric vehicles --- distributed generation --- MPC --- AV2R --- V2G --- inverter --- vehicle-to-grid --- vehicle location prediction --- automated machine learning --- machine learning --- Bayesian --- deep neural network --- demand load forecast --- distributed load --- ensemble algorithm stochastic --- K-means

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This Special Issue “Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) Technologies” was in session from 1 May 2019 to 31 May 2020. For this Special issue, we invited articles on current state-of-the-art technologies and solutions in G2V and V2G, including but not limited to the operation and control of gridable vehicles, energy storage and management systems, charging infrastructure and chargers, EV demand and load forecasting, V2G interfaces and applications, V2G and energy reliability and security, environmental impacts, and economic benefits as well as demonstration projects and case studies in the aforementioned areas. Articles that deal with the latest hot topics in V2G are of particular interest, such as V2G and demand-side response control technique, smart charging infrastructure and grid planning, advanced power electronics for V2G systems, adaptation of V2G systems in the smart grid, adaptation of smart cities for a large number of EVs, integration, and the optimization of V2G systems, utilities and transportation assets for advanced V2G systems, wireless power transfer systems for advanced V2G systems, fault detection, maintenance and diagnostics in V2G processes, communications protocols for V2G systems, energy management system (EMS) in V2G systems, IoT for V2G systems, distributed energy and storage systems for V2G, transportation networks and V2G, energy management for V2G, smart charging/discharging stations for efficient V2G, environmental and socio-economic benefits and challenges of V2G systems, and building integrated V2G systems (BIV2G). Five manuscripts are published in this Special Issue, including “An Ensemble Stochastic Forecasting Framework for Variable Distributed Demand Loads” by Agyeman et al., “Where Will You Park? Predicting Vehicle Locations for Vehicle-to-Grid, An MPC Scheme with Enhanced Active Voltage Vector Region for V2G Inverter” by Shipman et al., “Electric Vehicles Energy Management with V2G/G2V Multifactor Optimization of Smart Grids” by Xia et al., and “A Review on Communication Standards and Charging Topologies of V2G and V2H Operation Strategies” by Savitti et al.

vehicle-to-grid (V2G) --- vehicle-to-home (V2H) --- bi-directional charging topologies --- communication standards --- battery cycle --- smart grid --- optimization --- energy management --- electric vehicles --- distributed generation --- MPC --- AV2R --- V2G --- inverter --- vehicle-to-grid --- vehicle location prediction --- automated machine learning --- machine learning --- Bayesian --- deep neural network --- demand load forecast --- distributed load --- ensemble algorithm stochastic --- K-means

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Artificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in today’s world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that.

Information technology industries --- data mining --- decision-making system --- rough set --- mixed integer linear programming --- assembly clearance --- diesel engine quality --- Internet of things --- Wireless nodes --- Hybrid clustering --- Multi-hop routing --- Network lifetime --- Artificial intelligence --- data envelopment analysis --- decision making --- artificial intelligence --- performance --- visual analytics --- system --- air quality --- spatiotemporal --- multivariate --- dimension reduction --- clustering --- regular patterns --- anomalies --- speech recognition --- Long Short Term Memory (LSTM) --- speech output correction --- most-matching --- empirical correlations --- rheological properties --- real-time --- water-based drill-in fluid --- artificial neural network --- elastic parameters --- Poisson's ratio --- sandstone --- self-adaptive differential evolution --- total organic carbon --- barnett shale --- devonian shale --- fishbone multilateral wells --- predictive models --- well productivity --- international research --- knowledge map visualization --- policy documents quantification --- research hotspot --- policy keyword --- minimum miscibility pressure (MMP) --- CO2 flooding --- new models --- face recognition --- security --- spoofing --- histogram of oriented gradients --- smart cities --- deep learning --- LSTM --- neural networks --- location prediction --- trajectories --- smart tourism --- static Young's modulus --- sandstone formations --- machine learning --- data mining --- decision-making system --- rough set --- mixed integer linear programming --- assembly clearance --- diesel engine quality --- Internet of things --- Wireless nodes --- Hybrid clustering --- Multi-hop routing --- Network lifetime --- Artificial intelligence --- data envelopment analysis --- decision making --- artificial intelligence --- performance --- visual analytics --- system --- air quality --- spatiotemporal --- multivariate --- dimension reduction --- clustering --- regular patterns --- anomalies --- speech recognition --- Long Short Term Memory (LSTM) --- speech output correction --- most-matching --- empirical correlations --- rheological properties --- real-time --- water-based drill-in fluid --- artificial neural network --- elastic parameters --- Poisson's ratio --- sandstone --- self-adaptive differential evolution --- total organic carbon --- barnett shale --- devonian shale --- fishbone multilateral wells --- predictive models --- well productivity --- international research --- knowledge map visualization --- policy documents quantification --- research hotspot --- policy keyword --- minimum miscibility pressure (MMP) --- CO2 flooding --- new models --- face recognition --- security --- spoofing --- histogram of oriented gradients --- smart cities --- deep learning --- LSTM --- neural networks --- location prediction --- trajectories --- smart tourism --- static Young's modulus --- sandstone formations --- machine learning