Smart Zero-energy Buildings and Communities for Smart Grids

Cover
Half-Title Page
Title Page
Copyright Page
Contents
Preface
	Why this book?
	Who is this book for?
	Structure
	Acknowledgments
List of Acronyms
1. The Role of Smart Grids in the Building Sector
	1.1. Smart and zero-energy buildings
		1.1.1. Smart metering
		1.1.2. Demand response (DR)
		1.1.3. Distributed systems
	1.2. Smart and zero-energy communities
	1.3. Conclusion and future prospects
2. Integrated Design (ID) Towards Smart Zero-energy Buildings and Smart Grids
	2.1. Introduction
	2.2. Methodology
	2.3. Integrated design in smart and zero-energy buildings
	2.4. ID process principles and guidelines
		2.4.1. Benefits
		2.4.2. Barriers
	2.5. Scope of services
	2.6. Remuneration models
		Level 1 – Basic remuneration
		Level 2 – Extra remuneration for extra tasks
		Level 3 – Performance-related remuneration
	2.7. Application of evaluation tools
	2.8. Sustainability certification
	2.9. Consultancy and quality assurance
	2.10. Measurement of design quality criteria
	2.11. Defining a client’s objectives
		2.11.1. Capital cost reduction
		2.11.2. Delivery risk reduction
	2.12. Defining the tenant’s objectives
		2.12.1. Operational cost reduction
		2.12.2. Building unsuitability risk reduction
	2.13. Best practice sites
		2.13.1. Alexandros N. Tombazis and Associates Architects S.A. office building
		2.13.2. APIVITA Commercial and Industrial S.A.
		2.13.3. Stavros Niarchos Foundation Cultural Center
		2.13.4. Karelas Office Park
3. Data Analysis and Energy Modeling in Smart and Zero-energy Buildings and Communities
	3.1. Energy signature for the NTL of Cyprus Institute1
	3.2. Athalassa Campus and the NTL building
		3.2.1. Methodology
		3.2.2. Description of the Novel Technology case study
		3.2.3. Data exploration
		3.2.4. Correlation matrix
		3.2.5. Regression model
	3.3. Linear Fresnel solar collector at the NTL building, Cyprus Institute2
		3.3.1. Development of the NTL model
		3.3.2. Energy performance analysis in the NTL
		3.3.3. Discussion
	3.4. Conclusion
4. On the Comparison of Occupancy in Relation to Energy Consumption and Indoor Environmental Quality: A Case Study
	4.1. Introduction
	4.2. Methodology
	4.3. Description of the case building
	4.4. Description of the experimental procedure
	4.5. Results
		4.5.1. Investigation of energy consumption and indoor air quality
		4.5.2. Days of special interest – high occupancy
		4.5.3. Days of special interest – increased energy consumption
	4.6. Discussion and concluding remarks
5. Indoor Environmental Quality and Energy Consumption Assessment and ANN Predictions for an Integrated Internet-based Energy Management System Towards a Zero-energy Building
	5.1. Introduction
	5.2. Description of the SDE buildings
		5.2.1. General information
		5.2.2. Monitoring activities for SDE 3
	5.3. The power loads and hourly energy consumption
	5.4. Indoor environmental quality
		5.4.1. Thermal comfort assessment – time series analysis
		5.4.2. Indoor air quality
		5.4.3. The indoor illuminance levels
	5.5. Cross correlation
	5.6. Prediction using artificial neural networks (ANN)
		5.6.1. Prediction of outdoor temperature
		5.6.2. Prediction of relative humidity
		5.6.3. Prediction of power loads
	5.7. Specifications for an integrated internet-based energy management system towards a zero-energy building
	The scope of the integrated internet-based energy management for SDE
		5.7.1. The phases of the internet-based energy management system for SDE
		5.7.2. Integration of software and prediction algorithms
	5.8. Conclusion
6. Objective and Subjective Evaluation of Thermal Comfort in the Loccioni Leaf Lab, Italy
	6.1. Introduction
	6.2. Background information
	6.3. Methodology
		6.3.1. Subjective measurements
		6.3.2. Objective measurements
		6.3.3. Combined analysis of objective and subjective measurements
		6.3.4. User preferences and satisfaction with internal conditions
	6.4. Collection of building background data
	6.5. Collection of monitored data
	6.6. Right-Now questionnaire survey
	6.7. Results
		6.7.1. Analysis of MyLeaf measurements
		6.7.2. Analysis of Comfort Meter measurements
		6.7.3. Analysis of Right-Now survey responses
		6.7.4. Respondent characteristics and thermal comfort
		6.7.5. Combined analysis of objective and subjective measurements
		6.7.6. Correlation analysis for MyLeaf and Right-Now survey measurements
		6.7.7. Correlation analysis for objective and subjective measurements (Research for Innovation office space)
		6.7.8. Comparison between objective and subjective thermal sensation measurements
		6.7.9. Determination of acceptable and unacceptable conditions
	6.8. Conclusion
7. Smart Meters and User Engagement in the Leaf House
	7.1. Introduction
	7.2. Methodology
	7.3. Analysis of user engagement
		7.3.1. Development of the questionnaire
		7.3.2. Leaf House case study
	7.4. Results
		7.4.1. Demographics, socioeconomics
		7.4.2. Physiological, social and behavioral aspects
		7.4.3. Information level
		7.4.4. Health and comfort
		7.4.5. Living situation
	7.5. Conclusion
8. Integration of Energy Storage in Smart Communities and Smart Grids
	8.1. Energy storage systems in smart grids
		8.1.1. Electrical and electrochemical energy storage in smart grids
		8.1.2. Mechanical energy storage in smart grids
		8.1.3. Thermal energy storage in smart grids
	8.2. Energy storage and smart grids: case studies
		8.2.1. Case study 1: the Leaf Community smart grid energy storage system
		8.2.2. Case study 2: energy storage of CSP and integration with smart grids
	8.3. Conclusion and future prospects
Conclusion and Recommendations
References
List of Authors
Index
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