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Active building energy systems : operation and control / / Vahid Vahidinasab and Behnam Mohammadi-Ivatloo, editors
| Active building energy systems : operation and control / / Vahid Vahidinasab and Behnam Mohammadi-Ivatloo, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (394 pages) |
| Disciplina | 720.472 |
| Collana | Green energy and technology |
| Soggetto topico |
Architecture and energy conservation
Buildings - Energy conservation Renewable energy sources |
| ISBN | 3-030-79742-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910568255703321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Demand-Side Peer-to-Peer Energy Trading / / edited by Vahid Vahidinasab, Behnam Mohammadi-Ivatloo
| Demand-Side Peer-to-Peer Energy Trading / / edited by Vahid Vahidinasab, Behnam Mohammadi-Ivatloo |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (222 pages) |
| Disciplina | 929.374 |
| Collana | Green Energy and Technology |
| Soggetto topico |
Energy policy
Energy and state Electric power distribution Renewable energy sources Energy Policy, Economics and Management Energy Grids and Networks Energy System Transformation Renewable Energy |
| ISBN | 3-031-35233-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Overview of the Peer-to-Peer (P2P) Transactions and Transactive Energy (TE) Concepts, Challenges, and Outlook -- Chapter 2. The Role and Position of P2P and TE in Worldwide Energy Evolution -- Looking at P2P Transactions and TE Through the Lens of Sharing Economy and Digital Economy -- Chapter 3. TE Technologies, Standards, and Communication Protocols -- Chapter 4. Policy, Regulation, and Market Issues in P2P Transactions -- Chapter 5. Pilots and Demonstrators Around the World -- Chapter 6. Cybersecurity and Data Privacy Issues in P2P Transactions -- Chapter 7. Application of Artificial Intelligence and Machine Learning Approaches in P2P -- Chapter 8. Transactions -- Chapter 9. Long-Term Effects of P2P Transactions on Energy Systems -- Chapter 10. Participation of the Demand-Side Agents in Ancillary Services via P2P Transactions -- Chapter 11. The Cryptocurrencies and Their Role in Future Energy Transactions -- Chapter 12. Blockchain-based TE Platform for Energy Transactions -- Chapter 13. Distributed Optimization Applications to P2P Trading -- Chapter 14. Utilizing Shared Energy Storage in P2P Trading. |
| Record Nr. | UNINA-9910736978103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Electric vehicle integration via smart charging : technology, standards, implementation, and applications / / Vahid Vahidinasab, Behnam Mohammadi-Ivatloo, editors
| Electric vehicle integration via smart charging : technology, standards, implementation, and applications / / Vahid Vahidinasab, Behnam Mohammadi-Ivatloo, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (250 pages) |
| Disciplina | 629.286 |
| Collana | Green energy and technology |
| Soggetto topico | Battery charging stations (Electric vehicles) |
| ISBN | 3-031-05909-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- About the Editors -- Contributors -- 1 Standardised Domestic EV Smart Charging for Interoperable Demand Side Response: PAS 1878 and 1879 -- 1.1 Introduction -- 1.1.1 Purpose of Demand-Side Response -- 1.1.2 Status Quo, Challenges and Outlook -- 1.1.3 Assumptions of the Standardised Framework -- 1.1.4 Overview of Operation -- 1.1.5 Underpinning Principles -- 1.1.6 Scope -- 1.2 System Architecture -- 1.2.1 Functional Architecture -- 1.2.1.1 Compatibility with International Standards -- 1.2.1.2 Key Requirements -- 1.2.2 Descriptions of Functional Devices and Entities -- 1.2.2.1 DSR Service Provider (DSRSP) -- 1.2.2.2 Customer Energy Manager (CEM) -- 1.2.2.3 Home Energy Management System (HEMS) -- 1.2.2.4 Chargepoint (The ESA Functionality) -- 1.2.2.5 Chargepoint Manufacturer -- 1.2.2.6 Electric Vehicle (EV) -- 1.2.2.7 System Operators and Market Participants (SOMPs) -- 1.2.2.8 Electricity Supplier -- 1.2.2.9 National Electricity Regulator -- 1.2.3 Descriptions of Interfaces -- 1.2.3.1 Interface A -- 1.2.3.2 Interface B -- 1.2.3.3 Manufacturer Interface -- 1.2.3.4 Interface C -- 1.2.3.5 Interface M -- 1.2.3.6 External System Interface -- 1.2.3.7 Chargepoint and EV Interface -- 1.3 Operation Framework -- 1.3.1 Operation Process and DSR Modes -- 1.3.1.1 (a) Consumer Registration with the DSRSP -- 1.3.1.2 (b) Discovery, Authentication and Device Registration -- 1.3.1.3 (c) Initialisation -- 1.3.1.4 (d) Normal Operation -- 1.3.1.5 (e) De-registration -- 1.3.2 Power Profiles for DSR -- 1.3.2.1 Flexibility Offers as Power Profiles -- 1.3.2.2 Frequency Response Indicator -- 1.3.2.3 Information Required for Power Profiles -- 1.3.2.4 Power Reporting -- 1.3.3 Cyber Security Approach -- 1.4 EV Smart Charging for DSR Services -- 1.4.1 Mapping to IEC/ISO Standards for EVs.
1.4.2 Example Use Case: EV Implementation for DSR Services -- 1.4.2.1 Registration -- 1.4.2.2 Normal Operation -- 1.4.2.3 De-registration -- Bibliography -- 2 The Concept of Li-Ion Battery Control Strategies to Improve Reliability in Electric Vehicle (EV) Applications -- 2.1 Introduction -- 2.2 Battery Management System (BMS) -- 2.3 Battery Fault Detection -- 2.4 Battery State-of-Function Estimation -- 2.4.1 Battery SoH Estimation -- 2.4.2 Battery SoC Estimation -- 2.5 Conclusions -- References -- 3 Recognition of Electric Vehicles Charging Patterns with Machine Learning Techniques -- 3.1 Introduction -- 3.1.1 Electric Vehicles -- 3.1.1.1 Taxonomy of EVs -- 3.1.1.2 EV Integration's Benefits -- 3.1.1.3 Challenges and Problems of EVs High Penetration -- 3.1.2 Data Challenges of the High Penetration of the EVs -- 3.1.3 Energy Management of the EVs' Smart Charging -- 3.1.3.1 Concepts and Applications -- 3.1.3.2 Challenges and Opportunities -- 3.1.4 Literature Review on EV Integration -- 3.2 Identification of EV Charging Patterns -- 3.2.1 Clustering Concept and Principles -- 3.2.1.1 Concept of the Clustering -- 3.2.1.2 Principles of the Clustering -- 3.2.2 Clustering of the Charging Patterns -- 3.2.3 Utilization of ML Algorithms for Clustering the Charging Patterns -- 3.2.3.1 Unsupervised Learning -- 3.2.3.2 Supervised Learning -- 3.2.4 ML-Based Approach to Cluster the EV Charging Behaviors -- 3.2.4.1 Preprocessing -- 3.2.4.2 EV's Charging Behavior Clustering Using K-Means Algorithm -- 3.2.4.3 K-NN Classification for EV Charging Behavior -- 3.2.5 A Toy Example -- 3.2.6 Application of Charging Pattern Recognition in Smart Charging -- 3.3 Status Quo, Challenges, and Outlook -- 3.4 Concluding Remarks -- References -- 4 Cybersecurity and Data Privacy Issues of Electric Vehicles Smart Charging in Smart Microgrids -- 4.1 Introduction. 4.2 Cyberattacks and Security Issues of EVs -- 4.2.1 Various Attacks on EVs -- 4.2.1.1 Attacks on Control Systems -- 4.2.1.2 Attacks on Driving System Parts -- 4.2.1.3 Attacks on V2X Communication -- 4.2.2 The Vulnerability of EV Charging Stations to Cyberattacks -- 4.2.2.1 Web-Based Vulnerabilities -- 4.2.2.2 Human-Machine Interface Vulnerabilities and Physical Access Points -- 4.2.2.3 The Vulnerability of Servers -- 4.2.2.4 The Vulnerability of Smartphones -- 4.2.2.5 The Vulnerability of Building Energy Management System and Grid Interface -- 4.2.2.6 The Vulnerability of Original Equipment Manufacturers/Vendors -- 4.2.3 Cybersecurity Challenges in EV Communication -- 4.2.3.1 Limited Connectivity -- 4.2.3.2 Limited Computational Performance -- 4.2.3.3 The Scenarios and Threats of Unpredictable Attacks -- 4.2.3.4 Critical Hazard to the Life of Drivers and Passengers -- 4.2.4 Data Privacy Challenges in Smart EV Networks -- 4.2.5 Classifying the Cybersecurity Threats of On-Board Charging -- 4.2.5.1 Modification -- 4.2.5.2 Interference -- 4.2.5.3 Interruption -- 4.2.5.4 Interception -- 4.2.6 Risk Assessment -- 4.2.7 The Review of Attacker-Defender Models -- 4.2.8 Cybersecurity Requirements -- 4.2.8.1 The Security Goals for EV Ecosystem -- 4.2.8.2 Security Requirements Based on NISTIR 7628 -- 4.3 Status Quo, Challenges, and Outlook -- 4.4 Learned Lessons and Concluding Remarks -- References -- 5 Evaluation of Cyberattacks in Distribution Network with Electric Vehicle Charging Infrastructure -- 5.1 Introduction -- 5.2 Status Quo, Challenges, and Outlook -- 5.2.1 EV2EVSE -- 5.2.2 EVSE2EVSE -- 5.2.3 EV2EV -- 5.3 Related Work -- 5.4 Cyberattack Model -- 5.4.1 Response Model -- 5.5 Experimental Results -- 5.6 Conclusion -- References -- 6 Electric Vehicle Services to Support the Power Grid -- 6.1 Introduction. 6.2 Classification of EV Services Presentable to the Power Grid -- 6.2.1 EV's Active and Reactive Power Support Services -- 6.2.1.1 Frequency Control -- 6.2.1.2 Load Variance Minimization, Peak Shaving, and Valley Filling -- 6.2.1.3 Loads Restoration -- 6.2.1.4 Loss Minimization -- 6.2.1.5 Voltage Control -- 6.2.2 Support Services for Renewable Energy Sources Integration -- 6.3 Combination Capability of EVs' Different Services -- 6.4 Mathematical Modeling of EVs' Charging and Discharging Optimization Problem in the Power System -- 6.4.1 Constraints on EVs' Charging and Discharging Optimization Problem -- 6.4.1.1 EV Constraints -- 6.4.1.2 Network Constraints -- 6.4.2 Mathematical Models and Problem-Solving Methods for Optimizing Charge and Discharge of EVs -- 6.5 Current Status, Challenges, and Outlook -- 6.6 Conclusion -- References -- 7 Smart Charging of EVs to Harvest Flexibility for PVs -- 7.1 Status Quo, Challenges and Outlook -- 7.2 Introduction -- 7.2.1 Background and Literature Review -- 7.2.2 Contributions -- 7.2.3 Chapter Organization -- 7.3 Determination of Optimal EV Demand Profile -- 7.3.1 Assumptions -- 7.3.2 Mathematical Formulation -- 7.4 Numerical Studies -- 7.4.1 Data -- 7.4.2 Case-I: EVs Profile Optimization, Without Considering PVs -- 7.4.3 Case-II: EVs Profile Optimization, Considering PVs -- 7.4.4 Comparative Analysis of Cases -- 7.5 Conclusion -- Bibliography -- 8 A Robust Optimization-Based Model for Smart Charging of PEV Under Multiple Uncertainties -- 8.1 Introduction -- 8.2 Mathematical Representation of the Deterministic PEV Smart Charging -- 8.2.1 Constraints -- 8.3 The Proposed IGDT-Based Model for Robust Smart PEV Charging -- 8.3.1 The Information Gap Decision Theory (IGDT) -- 8.3.2 The Proposed IGDT-Based PEV Smart Charging -- 8.3.3 Multi-objective Particle Swarm Optimization (MOPSO). 8.3.3.1 Concise Review of PSO Algorithm -- 8.3.3.2 The Concept of Dominance in a Multi-objective Problem -- 8.3.3.3 The MOPSO Step-by-Step Implementation -- 8.3.4 Fuzzy Satisfaction Method -- 8.4 Numerical Results -- 8.4.1 Input Data -- 8.4.2 The SOC and Power Analysis -- 8.4.3 Robustness Assessment -- 8.5 Conclusion -- References -- 9 The Role of Smart Electric Vehicle Charging in Optimal Decision-making of the Active Distribution Network -- Nomenclature -- Sets and Indices -- Parameters -- Variables -- Binary Variables -- 9.1 Introduction -- 9.2 Status Quo, Challenges, and Outlook -- 9.3 Formulation -- 9.3.1 Hybrid Stochastic Programming/Robust Optimization Model -- 9.3.2 Electric Vehicles -- 9.3.3 Combined Heat and Power Unit -- 9.3.4 Solar Distributed Generations -- 9.3.5 Distribution System -- 9.3.6 The Objective Function -- 9.4 Results and Discussions -- 9.5 Conclusion -- References -- 10 Operational Challenges of Electric Vehicle Smart Charging -- 10.1 Status Quo, Challenges, and Outlook -- 10.2 Definition -- 10.3 Electric Vehicle Technology -- 10.4 Electric Vehicles Charging -- 10.4.1 Charging Standards for Electric Vehicles -- 10.4.2 Charging Speed and Duration -- 10.4.3 Electric Vehicle Smart Charging (EVSC) -- 10.5 Control of EVSC: Centralized and Decentralized Control Approaches -- 10.6 Benefits of EVSC -- 10.7 Main Challenges of Using EVSCs -- 10.7.1 Connectivity and Infrastructure in EVSC -- 10.7.2 The Minimum Requirements for EVSC -- 10.8 Conclusion -- References -- Index. |
| Record Nr. | UNINA-9910592991503321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Emerging Technologies for the Energy Systems of the Future
| Emerging Technologies for the Energy Systems of the Future |
| Autore | Anvari-Moghaddam Amjad |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (212 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
hybrid systems
photovoltaic wind energy energy economics RES investments Zimbabwe Africa and energy security electricity price forecasting (EPF) wind power forecasting (WPF) spot market balancing market ARMAX NARX-ANN 100% renewable power system secondary voltage control tertiary voltage control grid code wind farms photovoltaic parks energy transition renewable energy sources island power systems hybrid power plants wind turbines battery energy storage systems marine microgrid tidal generation system black widow optimization supplementary control fractional integrator non-linear fractional integrator 100% renewable power generation nexus food energy water greenhouse gas emission microgrid ancillary services energy storage power management solar hot waters thermosyphon thermal performance Morocco economic outcomes CO2 environmental assessment solar system domestic hot water production solar water heaters individual and collective solar water heater systems dynamic simulation TRNbuild TRNSYSstudio energy management residential and commercial loads short-term load forecasting deep learning bidirectional long short-term memory (Bi-LSTM) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557361303321 |
Anvari-Moghaddam Amjad
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Whole energy systems : bridging the gap via vector-coupling technologies / / Vahid Vahidinasab, Behnam Mohammadi-Ivatloo, editors
| Whole energy systems : bridging the gap via vector-coupling technologies / / Vahid Vahidinasab, Behnam Mohammadi-Ivatloo, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (354 pages) |
| Disciplina | 333.79 |
| Collana | Power Systems |
| Soggetto topico | Power resources |
| ISBN | 3-030-87653-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910544847303321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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