Operation of Smart Homes (Power Systems)

✍ Scribed by Mehdi Rahmani-Andebili (editor)

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 171
• Category: Library

✦ Synopsis

This book presents the latest research advancements in the operation of smart homes. It comprises new operation techniques including cooperative distributed energy scheduling, framework to react to malicious cyberattacks, framework for demand-side management, and framework for the design of smart homes to support residents’ wellness as well as new optimization techniques such as stochastic model predictive control and multi-time scale optimization. In addition, the book analyzes 11,000 studies that have been indexed in scientific databases and categorizes them based on various data points, including the field and the subject of the research, the name of the institutions, and the nationality of the authors.

• Presents new operation techniques of smart homes;
• Introduces new optimization techniques for operation of smart homes;
• Analyses 11,000 studies and categorizes them based on different data points.

✦ Table of Contents

Preface
Contents
Chapter 1: Worldwide Research Trends on Smart Homes
1.1 Introduction
1.2 Data
1.3 Subjects from Worldwide Publications
1.4 Countries, Affiliations, and Their Main Topics
1.5 Keywords from Worldwide Publications
1.6 Worldwide Research Trends
1.6.1 Internet of Things
1.6.2 Activity Recognition
1.6.3 Security
1.6.4 Energy
1.6.5 Machine Learning
1.7 Research Trends by Country
1.7.1 China
1.7.2 USA
1.7.3 India
1.7.4 South Korea
1.8 Relationship Between the Authors and Their Countries
References
Chapter 2: Multi-time Scale Stochastic Model Predictive Control for Cooperative Distributed Energy Scheduling of Smart Homes
2.1 Introduction
2.1.1 Related Works
2.1.2 The Contributions of the Study
2.1.2.1 Applying Cooperative Distributed Optimization in the Energy Scheduling Problem of Smart Homes
2.1.2.2 Applying Stochastic Approach to Address the Uncertainty of Renewables´ Power
2.1.2.3 Applying Multi-time Scale Optimization to Have Vast Vision for the Optimization Time Horizon and Precise Resolution fo...
2.1.2.4 Applying MPC to Address the Time-Varying Power of Renewables
2.1.2.5 Modeling the Technical and Economic Constraints of Resources
2.1.2.6 Applying GA-LP as an Effective and Fast Optimization Technique to Deal with Both Desecrate and Continuous Variables
2.2 The Proposed Technique
2.2.1 The Cooperative Distributed Energy Scheduling
2.2.2 The Multi-time Scale Stochastic MPC
2.2.2.1 The Stochastic Approach
2.2.2.2 The Multi-time Scale MPC
2.2.3 The Optimization Technique
2.3 The Problem Formulation
2.3.1 The Objective Function
2.3.2 The Constraints
2.3.2.1 The Supply-Demand Balance
2.3.2.2 The Power Limits of the DG
2.3.2.3 The Minimum Up/Down Time Limits of the DG
2.3.2.4 The Power Limits of the PEV´s Battery
2.3.2.5 The Depth of Discharge Limit of the PEV´s Battery
2.3.2.6 The Unviability of the PEV for the Smart Home
2.3.2.7 The Full Charge Constraint for the PEV´s Battery Before Departure
2.3.2.8 The Maximum Accessible Power from a Connected Smart Home
2.4 The Numerical Study
2.4.1 Case Study 1
2.4.1.1 The Problem Simulation Without Energy Scheduling
2.4.1.2 The Problem Simulation with Non-cooperative Energy Scheduling
2.4.1.3 The Problem Simulation with Cooperative Distributed Energy Scheduling
Applying Five-Minute Scale Stochastic MPC
Applying the One-Hour Scale Stochastic MPC
Applying Multi-time Scale Stochastic MPC
2.4.2 Case Study 2
2.5 Conclusion
References
Chapter 3: How to Employ Competitive Smart Home Retailers to React to Cyberattacks in Smart Cities?
3.1 Introduction
3.1.1 Cybersecurity Analysis of Power Systems
3.1.2 Smart Homes Analysis
3.2 Proposed Framework
3.2.1 Fast Reconfiguration
3.2.2 Market-Based Contribution of Non-attacked SH Retailers
3.2.3 Administrative Forced Load Curtailment for Passive Non-attacked SH Retailers
3.3 Problem Formulation
3.3.1 Administrative Reconfiguration
3.3.2 Market-Based Load Curtailment
3.3.3 Administrative Forced Load Curtailment
3.4 Case Study and Numerical Results
3.5 Conclusions
References
Chapter 4: Demand Response Frameworks for Smart Residential Buildings
4.1 Introduction
4.2 Type of Household Appliances
4.2.1 Non-Interruptible and Non-Schedulable Demands (NINSDs)
4.2.2 Interruptible and Non-Schedulable Demands (INSDs)
4.2.3 Schedulable Demands (SDs)
4.3 Model of Household Components
4.3.1 Model of NINSDs
4.3.2 Model of INSDs
4.3.3 Model of SDs
4.3.4 Model of Battery
4.3.5 Model of RER
4.4 IRLMS with Priority-Based Load Scheduling Algorithm for Demand Response
4.4.1 Controlling of NINSDs
4.4.2 Controlling of INSDs
4.4.3 Scheduling of SDs
4.5 IRLMS with Optimization-Based Scheduling Algorithm for Demand Response
4.5.1 Optimization Based Scheduling Algorithm
4.5.1.1 Demand Scheduling Constraint
4.5.1.2 Load Computational Constraint
4.5.1.3 Preemptive Constraint
4.5.1.4 Demand Constraint
4.6 IRLMS for Demand Response in Buildings with Energy Storage Devices
4.6.1 Functioning of Modified IRLMS
4.6.1.1 Demand Constraint
4.6.1.2 Battery Operating Mode Constraint
4.6.1.3 Battery Boundary Constraint
4.6.2 Controlling the Operation of Battery
4.7 IREMS for Demand Response in Buildings with Renewable Energy Resources
4.7.1 Architecture of IREMS
4.7.2 Functioning of IREMS
4.7.3 Scheduling of SDs
4.7.3.1 Demand Constraint
4.7.3.2 Power Injection Constraint
4.7.4 Scheduling of Battery
4.8 Case Study
4.9 Summary
References
Chapter 5: Smart Homes to Support the Wellness and Pleasurable Experience of Residents
5.1 Introduction
5.1.1 The Health Smart Home
5.1.2 Prospective Users
5.1.3 Acceptance of Technologies
5.2 Promoting Residents´ Wellness in Health Smart Homes
5.2.1 Case Study: Smart Homes for Single-Person Households
5.2.1.1 Motivation and Users
5.2.1.2 Wellness Framework
5.2.1.3 Results and Discussion
5.2.1.4 Proposing Smart Homes for Young, Single-Person Households
5.3 Supporting Residents´ Pleasurable Experiences with Smart Technologies
5.3.1 Case Study: Enjoyable Smart Environments for Older Adults
5.3.1.1 Motivation and Users
5.3.1.2 Evaluation Framework Focusing on Pleasurable Experiences
5.3.1.3 Proposing Enjoyable Smart Environments for Older Adults
5.4 A Conceptual Framework for the Design of Smart Homes
5.4.1 Wellness: Healthy Living
5.4.2 User: Daily Activities
5.4.3 Home: The Domestic Setting
5.4.4 Human-Computer Interaction: Smart Technology
5.5 Challenges and Issues for the Design of Smart Homes
5.5.1 Understanding of Prospective Users as a Way of Emphasizing Wellness
5.5.2 User Engagement and Perceptions of Technologies for Adoption
5.5.3 Optimal and Pleasurable Experiences with Positive Technology
5.5.4 A Multidisciplinary Approach and the Role of the Architectural Domain
References
Index