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El. knyga: Smart Energy Control Systems for Sustainable Buildings

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There is widespread interest in the way that smart energy control systems, such as assessment and monitoring techniques for low carbon, nearly-zero energy and net positive buildings can contribute to a Sustainable future, for current and future generations.  There is a turning point on the horizon for the supply of energy from finite resources such as natural gas and oil become less reliable in economic terms and extraction become more challenging, and more unacceptable socially, such as adverse public reaction to fracking. Thus, in 2016 these challenges are having a major influence on the design, optimisation, performance measurements, operation and preservation of: buildings, neighbourhoods, cities, regions, countries and continents. The source and nature of energy, the security of supply and the equity of distribution, the environmental impact of its supply and utilization, are all crucial matters to be addressed by suppliers, consumers, governments, industry, academia, and financial institutions.





This book entitled Smart Energy Control Systems for Sustainable Buildings contains eleven chapters written by international experts based on enhanced conference papers presented at the Sustainability and Energy in Buildings International conference series.





This book will be of interest to University staff and students; and also industry practioners.
1 Zero-Energy Living Lab
1(36)
Salvatore Carlucci
Francesco Causone
Lorenzo Pagliano
Marco Pietrobon
1.1 Introduction
2(3)
1.2 The Climate Challenges
5(3)
1.3 The Building
8(2)
1.4 Simulation and Optimization of the Design Concept
10(10)
1.4.1 Mathematical Optimization
11(3)
1.4.2 Dynamic Building Performance Simulation
14(1)
1.4.3 Simulation Outcome and Discussion
15(5)
1.5 Experimental Set-up
20(1)
1.6 Earth to Air Heat Exchanger
21(9)
1.6.1 Location of the Earth-to-Air Heat Exchanger and Identification of the Boundary Conditions
21(1)
1.6.2 Design of the EAHE
22(6)
1.6.3 Design of the Monitoring System of the Earth-to-Air Heat Exchanger
28(1)
1.6.4 Installation of the Earth-to-Air Heat Exchanger
29(1)
1.7 System Start-up and Early Outcomes
30(1)
1.8 Conclusions
31(6)
References
32(5)
2 Assessment of the Green Roofs Thermal Dynamic Behavior for Increasing the Building Energy Efficiencies
37(24)
Antonio Gagliano
Maurizio Detommaso
Francesco Nocera
2.1 Introduction
39(1)
2.2 Materials and Methods
40(3)
2.3 Green Roof Modeling
43(1)
2.4 Methodology
44(2)
2.4.1 Building Simulations
44(2)
2.5 Pilot Study
46(2)
2.5.1 Reference Building
46(2)
2.6 Building Retrofits Scenario
48(1)
2.6.1 Descriptions of the Green Roof
48(1)
2.7 Energy Performance Simulations
49(7)
2.7.1 Building Simulations
49(2)
2.7.2 Energy Needs
51(1)
2.7.3 Assessment of the Thermal Dynamic Behaviour
52(2)
2.7.4 Assessment of Thermal Comfort
54(2)
2.8 Discussion
56(1)
2.9 Conclusions
56(5)
References
57(4)
3 Understanding Opportunities and Barriers for Social Occupant Learning in Low Carbon Housing
61(28)
Magdalena Baborska-Narozny
Fionn Stevenson
Paul Chatterton
3.1 Introduction
62(1)
3.2 Home Use Social Learning Conceptual Framework
63(4)
3.3 Methods
67(3)
3.3.1 Quantitative Monitoring
67(1)
3.3.2 Qualitative Building and User Related Data
68(1)
3.3.3 The Surveys
69(1)
3.4 Understanding the Key Home Use Learning Challenges
70(1)
3.5 Analysing Home Use Expectations, Prior Experiences and Skills
71(2)
3.6 Provision of Individual Home Use Learning Support
73(2)
3.7 Decision-Making, Skills and Understanding Related to Home Use
75(1)
3.8 Correlation of Results for MVHR in Relation to Clarity of Use
76(4)
3.9 Discussion of Barriers and Opportunities for Collective Learning
80(3)
3.10 Conclusions
83(6)
References
85(4)
4 An Archetype Based Building Stock Aggregation Methodology Using a Remote Survey Technique
89(28)
James Pittam
Paul D. O'Sullivan
Garrett O'Sullivan
4.1 Introduction and Background
90(1)
4.2 Overview of Existing Studies Using Stock Modelling Methodologies
91(4)
4.2.1 Various Modelling Techniques
93(2)
4.3 Stock Modelling Method Used
95(4)
4.3.1 Data Collection Methods
95(4)
4.4 Methodology for Archetype Development
99(2)
4.5 Application of Stock Aggregation Method
101(6)
4.5.1 Results for Geometrical and Thermal Characteristics
105(2)
4.6 Archetypes Development
107(3)
4.7 Results from Case Study
110(3)
4.8 Discussion
113(1)
4.9 Conclusion and Future Work
114(3)
References
114(3)
5 Renewable Homes---Feasibility Options for UK Traditional Buildings Through Green Deal
117(22)
Charikleia Moschou
Catalina Spataru
5.1 Introduction
117(1)
5.2 Green Deal
118(10)
5.2.1 Insulation
121(1)
5.2.2 Glazing
122(2)
5.2.3 Ventilation
124(1)
5.2.4 Micro-distributed Technologies
125(3)
5.3 Proposed Packages Through Green Deal
128(2)
5.4 Results
130(6)
5.4.1 Economic Analysis
131(2)
5.4.2 Carbon Savings
133(1)
5.4.3 Cost and CO2 Savings of Recommended Green Deal Packages
134(2)
5.5 Discussions and Conclusions
136(3)
References
137(2)
6 Analysing the Contribution of Internal Heat Gains When Evaluating the Thermal Performance of Buildings
139(20)
Rainer Elsland
6.1 Background and Objectives
139(1)
6.2 Methodological Approach
140(7)
6.2.1 Structural Framework
140(2)
6.2.2 Modelling Procedure
142(2)
6.2.3 Norm-Based Modelling of Useful Energy Demand for Space Heating Purposes
144(2)
6.2.4 Modelling Dynamic Internal Heat Gain Development
146(1)
6.3 Case Study
147(7)
6.3.1 Calibration Basis
147(1)
6.3.2 Scenario Definition
148(1)
6.3.3 Energy Policy Framework
149(1)
6.3.4 Results
150(4)
6.4 Conclusions
154(5)
Appendix
154(3)
References
157(2)
7 Smart Home Appliance Control via Hand Gesture Recognition Using a Depth Camera
159(14)
Dong-Luong Dinh
Tae-Seong Kim
7.1 Introduction
160(2)
7.2 Hand Gesture-Based Interface System
162(1)
7.3 Methodology
163(5)
7.3.1 Hand Depth Silhouette Acquisition
163(1)
7.3.2 Hand Parts Recognition
164(2)
7.3.3 Hand Gesture Recognition
166(2)
7.4 Experimental Results and Demonstrations
168(2)
7.4.1 Results of Hand Parts Recognition
168(1)
7.4.2 Results of Hand Pose Recognition
168(1)
7.4.3 Graphic User Interfaces (GUIs) for Demonstrations
169(1)
7.5 Conclusions
170(3)
References
170(3)
8 Neural Networks Applied to Short Term Load Forecasting: A Case Study
173(26)
Filipe Rodrigues
Carlos Cardeira
J.M.F. Calado
8.1 Introduction
174(1)
8.2 State of the Art
175(2)
8.3 Methodology
177(7)
8.3.1 Designing Artificial Neural Networks
177(3)
8.3.2 ANN Energy Consumption Model
180(3)
8.3.3 Daily Energy Consumption: Average and Maximum
183(1)
8.3.4 Hourly Energy Consumption
183(1)
8.4 Validation
184(5)
8.4.1 Database
184(1)
8.4.2 Selection of the Network Architecture
185(4)
8.5 Results and Discussion
189(6)
8.5.1 Daily Energy Consumption: Average and Maximum
190(1)
8.5.2 Hourly Energy Demand
190(4)
8.5.3 Results Obtained in Similar Studies
194(1)
8.6 Conclusion
195(4)
References
196(3)
9 Development of a Holistic Method to Analyse the Consumption of Energy and Technical Services in Manufacturing Facilities
199(26)
John Cosgrove
John Littlewood
Paul Wilgeroth
9.1 Energy in Industry
199(6)
9.1.1 Introduction
199(2)
9.1.2 Sustainable Manufacturing
201(2)
9.1.3 Energy Efficiency Potential
203(1)
9.1.4 Energy Efficiency Results
204(1)
9.2 Industrial Energy Classification
205(5)
9.2.1 Production Versus Facilities
205(1)
9.2.2 Significant Energy Users (SEUs)
206(3)
9.2.3 Electric Motors
209(1)
9.3 Production Centered Energy Management
210(4)
9.3.1 Monitoring and Targeting
212(1)
9.3.2 Energy Flows in Production Operations
212(1)
9.3.3 Methodologies
213(1)
9.4 Value Stream Mapping
214(5)
9.4.1 Lean Energy Management
214(3)
9.4.2 Mapping Methodology
217(2)
9.5 Conclusion
219(6)
References
221(4)
10 Two-Stage Optimization for Building Energy Management
225(20)
Jorn K. Gruber
Milan Prodanovic
10.1 Introduction
226(1)
10.2 Building Energy Management
227(3)
10.2.1 Problem Description
228(1)
10.2.2 Two-Stage Optimization Framework
229(1)
10.3 Optimization Approach
230(3)
10.3.1 Overview
230(1)
10.3.2 Medium Term Optimization
231(1)
10.3.3 Short Term Optimization
231(1)
10.3.4 Optimization Procedure
232(1)
10.4 Case Study
233(2)
10.4.1 Building Energy System
233(2)
10.4.2 Implementation
235(1)
10.5 Simulation Results
235(6)
10.6 Conclusions
241(4)
References
241(4)
11 An Investigation of Indoor Air Quality in UK Passivhaus Dwellings
245
Grainne McGill
Tim Sharpe
Lukumon Oyedele
Greg Keeffe
Keith McAllister
11.1 Introduction
246(1)
11.2 Background
247(1)
11.3 Methodology
248(2)
11.3.1 Indoor Air Quality Measurements
248(2)
11.3.2 Structured Occupant Interviews
250(1)
11.3.3 Occupant Diary and Building Survey
250(1)
11.4 Results
250(12)
11.4.1 Heating and Ventilation
250(2)
11.4.2 Carbon Dioxide and Average Occupancy in Open Plan Living Area
252(2)
11.4.3 Summer Bedroom Conditions
254(1)
11.4.4 Living Room Relative Humidity and Temperature
255(2)
11.4.5 Formaldehyde Levels in Open Plan Living Room and Kitchen
257(2)
11.4.6 Volatile Organic Compounds (VOC's) in House No. 1
259(1)
11.4.7 Indoor Air Quality Perception
260(1)
11.4.8 Thermal Comfort Perception
261(1)
11.5 Discussion
262(3)
11.6 Conclusions
265
References
266