Intro
Foreword
Preface
Contents
Smart Grid 3.0: Grid with Proactive Intelligence
1 Introduction
2 Evolution of Power Grid to Smart Grid 3.0
2.1 Smart Grid 1.0
2.2 Smart Grid 2.0
2.3 Smart Grid 3.0
3 Smart Grid 3.0: Communication and Computational Technologies
3.1 AI for Smart Grid
3.2 Blockchain for Smart Grid
3.3 Bigdata Analytics for Smart Grid
3.4 Cloud, Fog, and Edge Computing for Smart Grid
3.5 5G for Smart Grid
3.6 IoT for Smart Grid
4 Challenges and Possible Solutions
4.1 Challenges for Implementing AI in Smart Grid

4.2 Challenges for Blockchain in Smart Grid
4.3 Challenges for Bigdata Analytics in Smart Grid
4.4 Challenges for Edge, Fog, and Cloud Computing in Smart Grid
4.5 Challenges for 5G and IoT in Smart Grid
5 Conclusions
References
Blockchain for Energy Management: Smart Meters, Home Automation, and Electric Vehicles
1 Introduction
2 Blockchain Technology-Definition, Evolution, and Operation
2.1 Definition and Structure
2.2 Blockchain Technology Evolution
2.3 Smart Contracts
2.4 The Token Concept
3 Architecture of an Association of Producers/Energy Distributors

3.1 Peer-to-Peer-DSO Networks
3.2 Peer-to-Peer-Microgrid Networks
3.3 Association of Renewable Energy Producers with Surplus Energy Injected into the National System that Distributes Energy to Consumers
3.4 Renewable Energy Producer/consumer of an Association Using a Batteries Stack
4 Application of Blockchain Technology for Proposed Energy Architectures
4.1 Smart Contract for the Login Application
4.2 Results-Testing and Validating the Behavior of the Smart Contract and the Web Application
5 Discussions and Future Perspectives
6 Conclusions
References

Engineering Applications of Blockchain Based Crowdsourcing Concept in Active Distribution Grids
1 Introduction
2 Crowdsourcing Energy System
3 Blockchain Technology
4 Enhanced Prosumers Trading Approach
4.1 Problem Formulation
4.2 The Blockchain-Based Crowdsourcing Algorithm Design for P2P Energy Transactions
5 Case Study
6 Conclusions
References
Machine Learning-Based Approaches for Transmission Line Fault Detection Using Synchrophasor Measurements in a Smart Grid
1 Introduction
2 LabVIEW Based Synchrophasor Measurements
2.1 Phasor Measurement Unit (PMU)

2.2 Phasor Estimation
2.3 LabVIEW Based SPM
2.4 Fault Detection from SPMs
3 Machine Learning Algorithms
3.1 KNN Algorithm
3.2 Support Vector Machine
3.3 Logistic Regression
4 Experimental Setup and Results Discussion
5 Conclusion
References
Data Mining-Based Approaches in the Power Quality Analysis
1 Introduction
2 Performance Indicators for the Electricity Distribution Service
3 Data Mining-Based Analysis of the Power Quality
4 Testing the Methodology
4.1 Voltage Quality Analysis
4.2 Analysis of Continuity in the Electricity Supply
5 Conclusions