Smart Grid Technology: A Cloud Computing and Data Management Approach

Contents
Figures
Tables
Foreword
Preface
Part I Introduction
	1. Introduction to Smart Grid
		1.1 Smart Grid Framework and Communication Model
		1.2 Smart Grid Vision
		1.3 Requirements of a Smart Grid
			1.3.1 Energy management
			1.3.2 Need to support multiple devices
			1.3.3 Information management
			1.3.4 Layered architecture
			1.3.5 Security
		1.4 Components of the Smart Grid
			1.4.1 Bi-directional communication
			1.4.2 Smart meter
			1.4.3 Micro-grid
			1.4.4 Plug-in hybrid electric vehicles
		1.5 Smart Grid Interoperability
		1.6 Summary
		References
	2. Introduction to Cloud Computing
		2.1 Allied Computing Models
			2.1.1 Mainframes
			2.1.2 Client–server architecture
			2.1.3 Cluster computing
			2.1.4 Grid computing
			2.1.5 Service oriented architecture (SOA)
			2.1.6 Utility computing
			2.1.7 Pay-per-use model
		2.2 Virtualization
		2.3 Hypervisor
		2.4 Types of Services
			2.4.1 Infrastructure as a service
			2.4.2 Platform as a service
			2.4.3 Software as a service
		2.5 Types of Deployment
			2.5.1 Public cloud
			2.5.2 Private cloud
			2.5.3 Hybrid cloud
			2.5.4 Community cloud
		2.6 Advantages of Cloud Computing
			2.6.1 Elastic nature
			2.6.2 Shared architecture
			2.6.3 Metering architecture
			2.6.4 Supports existing internet services
		2.7 Architecture of Cloud Computing
		2.8 Summary
		References
	3. Introduction to Big Data Analytics
		3.1 Attributes of Big Data
			3.1.1 Volume of data
			3.1.2 Velocity of data
			3.1.3 Variety of data
		3.2 Overview of Big Data Analytics
		3.3 Benefits of Big Data Analytics
		3.4 Big Data Analytics for Smart Grid
		3.5 Big Data Analytics Tools
		3.6 Summary
		References
	4. Fundamental Mathematical Prerequisites
		4.1 Linear Programming
		4.2 Integer Linear Programming
		4.3 Mixed Integer Linear Programming
		4.4 Non-Linear Programming
		4.5 Quadratic Function
		4.6 Different Distributions
			4.6.1 Normal distribution
			4.6.2 Poisson distribution
			4.6.3 Gaussian distribution
		4.7 Dimension Reduction Methods
			4.7.1 Principal component regression (PCR) method
			4.7.2 Reduced rank regression (RRR) method
		4.8 Approximation Algorithms
		4.9 Summary
		References
Part II Cloud Computing Applications for Smart Grid
	5. Demand Response
		5.1 Fundamentals of Demand Response and Challenges
		5.2 Different Demand Response Mechanisms
			5.2.1 Economic demand response
			5.2.2 Emergency demand response
			5.2.3 Ancillary demand response
		5.3 Problems with Existing Approaches without Cloud
		5.4 Cloud-Based Demand Response in Smart Grid
			5.4.1 Demand response in smart grid energy management
			5.4.2 Demand response in data centers for the smart grid
		5.5 Future Trends and Issues
		5.6 Summary
		References
	6. Geographical Load-Balancing
		6.1 Need for Load-Balancing in Smart Grid
		6.2 Challenges
		6.3 Problems with Existing Load-Balancing Approaches without Cloud
			6.3.1 Coalition formation
			6.3.2 Flexible demand forecasting
			6.3.3 Centralized load controller
		6.4 Cloud-Based Load-Balancing
			6.4.1 Price-based energy load-balancing
			6.4.2 Load-balancing at the smart grid data centers
			6.4.3 Renewable energy-aware load-balancing
			6.4.4 Load-balancing at data center networks
		6.5 Future Trends and Issues
		6.6 Summary
		References
	7. Dynamic Pricing
		7.1 Deployment of Dynamic Pricing in Smart Grids
			7.1.1 Determination of actual time-slot
			7.1.2 Need for adequate infrastructure
		7.2 Existing Dynamic Pricing Policies without Cloud
			7.2.1 Day-ahead pricing policy
			7.2.2 Demand-based pricing policy
			7.2.3 Supply-based pricing policy
			7.2.4 Supply–demand-based pricing policy
		7.3 Problems with Existing Approaches without Cloud
			7.3.1 Local knowledge of supply–demand information
			7.3.2 Unfair pricing tariffs for customers
		7.4 Cloud-Based Dynamic Pricing Policies
		7.5 Future Trends and Issues
		7.6 Summary
		References
	8. Virtual Power Plant
		8.1 Concept of Virtual Power Plant
			8.1.1 Commercial VPP
			8.1.2 Technical VPP
		8.2 Advantages of Virtual Power Plant
			8.2.1 Acts as internet of energy
			8.2.2 Energy efficiency
			8.2.3 Online optimization platform
			8.2.4 Systems security
		8.3 Virtual Power Plant Control Strategy
		8.4 Virtual Power Plant: Different Methodologies
			8.4.1 Integration of electric vehicles
			8.4.2 Implementation of energy storage devices
		8.5 Future Trends and Issues
		8.6 Summary
		References
	9. Advanced Metering Infrastructure
		9.1 Requirements
		9.2 Different Approaches of AMI
			9.2.1 Data collection for AMI
			9.2.2 Classification of AMI data
			9.2.3 Security for AMI
			9.2.4 Electricity theft detection in AMI
		9.3 Future Trends and Issues
		9.4 Summary
		References
	10. Cloud-Based Security and Privacy
		10.1 Security in Data Communication
			10.1.1 Overview of PKI
		10.2 Security and Privacy Challenges and Opportunities
		10.3 Security and Privacy Approaches without Cloud
		10.4 Cloud-Based Security and Privacy Approaches
			10.4.1 Identity-based encryption
		10.5 Future Trends and Issues
		10.6 Summary
		References
Part III Smart Grid Data Management and Applications
	11. Smart Meter Data Management
		11.1 Smart Metering Architecture
		11.2 Challenges and Opportunities
			11.2.1 Requirement of scalable computing facility
			11.2.2 Presence of heterogeneous data
			11.2.3 Requirement of large storage devices
			11.2.4 Information integration from different levels
			11.2.5 Complex architecture in the presence of multiple parties
		11.3 Smart Meter Data Management
			11.3.1 Cluster-based management
			11.3.2 Data compression and pattern extraction
			11.3.3 Cloud computing for big data management
			11.3.4 Calibration with big data
			11.3.5 Fuzzy logic-based management
		11.4 Future Trends and Issues
		11.5 Summary
		References
	12. PHEVs: Internet of Vehicles
		12.1 Convergence of PHEVs and Internet of Vehicles
		12.2 Electric Vehicles Management
			12.2.1 Charging and discharging of PHEVs
			12.2.2 Energy management for data centers and PHEVs
			12.2.3 Providing on-board internet service facility
		12.3 Future Trends and Issues
		12.4 Summary
		References
	13. Smart Buildings
		13.1 Concept of Smart Building
		13.2 Challenges and Opportunities
		13.3 Different Approaches for Establishing Smart Buildings
			13.3.1 Automatic energy management systems
			13.3.2 Intelligent information management systems
		13.4 Future Trends and Issues
		13.5 Summary
		References
Part IV Smart Grid Design and Deployment
	14. Simulation Tools
		14.1 Simulation Tools
			14.1.1 Open DSS
			14.1.2 MATPOWER
			14.1.3 NS-2 and NS-3
			14.1.4 GridSim
			14.1.5 OMNeT++
			14.1.6 GridLAB-D
			14.1.7 SUMO
		14.2 Summary
		References
	15. Worldwide Initiatives
		15.1 Initiatives Taken by EU
		15.2 Initiatives Taken by US Department of Energy
		15.3 Smart Grid Initiatives in Other Countries
			15.3.1 Initiatives in China
			15.3.2 Initiatives in India
		15.4 Smart Grid Standards
		15.5 Summary
		References
Index