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Table of Contents
Intro
Preface
Organization
Contents
Power System Planning, Control and Analysis
Intelligent Pre-warning Method of Transmission Line Icing Based on Stack Denoising Autoencoder
1 Introduction
2 Sample Preprocessing
2.1 Sample Generation and Selection
2.2 Data Preprocessing
2.3 Sample Cluster
3 Ice Thickness Growth Prediction Model
3.1 Feature Extraction Based on SDAE
3.2 Ice Thickness Growth Regression Based on Feedforward Neural Network
4 Procedures of Ice Pre-Warning
4.1 Evaluation of Icing Trend
4.2 Ice Coating Severity Pre-Warning Procedure
4.3 Flow Chart of Pre-Warning Procedure
5 Simulation Results
6 Conclusion
References
Smart Contract Planning for Micro Grid Using Virtual Power Plants-Based Approach
1 Introduction
1.1 Power Flow and Information Flow of Virtual Power Plant
1.2 Electricity Retailing Utility Enterprise Participation in VPP Mode
2 Literature Review
3 Methods
3.1 Resources Allocation Decision Model
3.2 Operations of Smart Contracts
3.3 Contract Mechanism
3.4 Infrastructure of Virtual Power Plant
3.5 Type of Contract Between Virtual Power Plant and Distributed Energy
4 Results and Discussion
4.1 Application of Smart Contracts in Certain Cases
4.2 Transaction Mode of Smart Contract in Virtual Power Plants
5 Conclusion
References
Smart Grid System Cooperative Output Control Method Based on Distributed Compensation Algorithm
1 Introduction
2 Output Tracking Algorithm Based on Full-State Information
3 Smart Grid Simulation Experiments
4 Conclusion
References
Optimizing the Location and Capacity of Charging Stations for a Public Electric Bus System Considering Actual Operating Service Conditions Based on Differential Evolution Algorithm
1 Introduction
2 Electric Bus System Modelling
2.1 Analysis of the Bus system
2.2 Charging Demand for Electric Bus
3 Problem Formulation
3.1 The Desired Capacity of Charging Stations
3.2 The Cost of the Desired Capacity of the Battery
3.3 The Total Cost of the Electric Bus System
4 The Proposed Optimizing the Location and Capacity of the Charging Station and Onboard Battery Capacity Based on Differential Evolution Algorithm
5 Results and Discussion
5.1 Scenario 1: Studying the Usage of Blue Line Buses Within Khon Kaen University in 1 Round Trip on Maximum Battery Capacity
5.2 Scenario 2: Finding the Optimal Charging Station Location, Charging Station Capacity, and Onboard Battery Capacity by Using the Proposed Algorithm Based on DE
6 Conclusion
References
High-Severity N-x-k Contingency Ranking and Screening Based on Deep Learning and Heuristic Search
Preface
Organization
Contents
Power System Planning, Control and Analysis
Intelligent Pre-warning Method of Transmission Line Icing Based on Stack Denoising Autoencoder
1 Introduction
2 Sample Preprocessing
2.1 Sample Generation and Selection
2.2 Data Preprocessing
2.3 Sample Cluster
3 Ice Thickness Growth Prediction Model
3.1 Feature Extraction Based on SDAE
3.2 Ice Thickness Growth Regression Based on Feedforward Neural Network
4 Procedures of Ice Pre-Warning
4.1 Evaluation of Icing Trend
4.2 Ice Coating Severity Pre-Warning Procedure
4.3 Flow Chart of Pre-Warning Procedure
5 Simulation Results
6 Conclusion
References
Smart Contract Planning for Micro Grid Using Virtual Power Plants-Based Approach
1 Introduction
1.1 Power Flow and Information Flow of Virtual Power Plant
1.2 Electricity Retailing Utility Enterprise Participation in VPP Mode
2 Literature Review
3 Methods
3.1 Resources Allocation Decision Model
3.2 Operations of Smart Contracts
3.3 Contract Mechanism
3.4 Infrastructure of Virtual Power Plant
3.5 Type of Contract Between Virtual Power Plant and Distributed Energy
4 Results and Discussion
4.1 Application of Smart Contracts in Certain Cases
4.2 Transaction Mode of Smart Contract in Virtual Power Plants
5 Conclusion
References
Smart Grid System Cooperative Output Control Method Based on Distributed Compensation Algorithm
1 Introduction
2 Output Tracking Algorithm Based on Full-State Information
3 Smart Grid Simulation Experiments
4 Conclusion
References
Optimizing the Location and Capacity of Charging Stations for a Public Electric Bus System Considering Actual Operating Service Conditions Based on Differential Evolution Algorithm
1 Introduction
2 Electric Bus System Modelling
2.1 Analysis of the Bus system
2.2 Charging Demand for Electric Bus
3 Problem Formulation
3.1 The Desired Capacity of Charging Stations
3.2 The Cost of the Desired Capacity of the Battery
3.3 The Total Cost of the Electric Bus System
4 The Proposed Optimizing the Location and Capacity of the Charging Station and Onboard Battery Capacity Based on Differential Evolution Algorithm
5 Results and Discussion
5.1 Scenario 1: Studying the Usage of Blue Line Buses Within Khon Kaen University in 1 Round Trip on Maximum Battery Capacity
5.2 Scenario 2: Finding the Optimal Charging Station Location, Charging Station Capacity, and Onboard Battery Capacity by Using the Proposed Algorithm Based on DE
6 Conclusion
References
High-Severity N-x-k Contingency Ranking and Screening Based on Deep Learning and Heuristic Search