Smart Zero-energy Buildings and Communities for Smart Grids

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Smart zero-energy buildings and communities have a major role to play in the evolution of the electric grid towards alignment with carbon neutrality policies. The goal to reduce greenhouse gas emissions in the built environment can be pursued through a holistic approach, including the drastic reduction of buildings’ energy consumption.<br /><br />The state-of-the-art in this field relates, on the one hand, to design methodologies and innovative technologies which aim to minimize the energy demand at the building level. On the other hand, the development of information and communication technologies, along with the integration of renewable energy and storage, provide the basis for zero and positive energy buildings and communities that can produce, store, manage and exchange energy at a local level.<br /><br />This book provides a structured and detailed insight of the state-of-the-art in this context based on the analysis of real case studies and applications.

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In Chapter 5, the energy consumption and indoor environmental quality of one of the three buildings of the Design and Environment School (SDE3) of the National University of Singapore is evaluated and cross-correlated based on a different perspective. Prediction algorithms based on artificial neural network models are tested.

In Chapter 6, objective and subjective evaluation of thermal comfort is analyzed in the context of a unique smart zero-energy industrial facility in Italy.

In Chapter 7, the user engagement of residents in a smart zero-energy building in the same area of Italy is investigated in order to provide the framework for analyzing individual preferences, identifying consumption patterns and assessing the utilisability of information provided to users as well as how effective this is in supporting behavioral change.

Chapter 8deals with the integration of energy storage in smart communities and smart grids. The various energy storage technologies are presented including electrical, mechanical, chemical and thermal. Energy storage and optimization of its utilization in smart grids integrating renewable energy technologies is explored through state-of-the-art case studies.

Finally, the conclusion outlines the main and overall conclusions and recommendations stemming from the findings of the presented research.

Acknowledgments

The editors express their deepest appreciation and gratitude to all partners, personnel, and researchers for their unique contributions, time and efforts which altogether resulted in making this publication happen. We are also very thankful to the European Commission and the EU taxpayer for devoting the necessary financial resources for the implementation of the Smart GEMS project.

Nikos KAMPELIS

November 2021

List of Acronyms

AMI Advanced Metering Infrastructure
ANN Artificial Neural Network
AP Accredited Professional
ATES Aquifer Thermal Energy Storage
BAS Building Automation System
BCVTB Building Controls Virtual Test Bed
BEMS Building Energy Management System
BIM Building Information Modeling
biPV building-integrated PhotoVoltaics
BMS Building Management System
CAES Compressed Air Energy Storage
CDD Cooling Degree Days
CHP Cogeneration of Heat and Power
COP Coefficient Of Performance
CPC Compound Parabolic Collector
CSP Curtailment Service Provider
Cv Coefficient of variance
DA Day-Ahead
DC Direct Current
DER Distributed Energy Resources
DG Diesel Generator
DHW Domestic Hot Water
DNI Direct Normal Irradiance
DR Demand Response
DSG Direct Steam Generation
DSM Demand Side Management
EED Energy Efficiency Directive
EER Energy Efficiency Ratio
EES Electrical Energy Storage
EMS Energy Management System
EPBD Energy Performance Buildings Directive
ES Energy Signature
ESEER European Seasonal Energy Efficiency Ratio
ETL Extract, Transform, Load
EV Electric Vehicles
FC Fuel Cell
FCU Fan Coil Units
FMU Functional Mock-up Units
G2V Grid-to-Vehicle
GA Genetic Algorithm
GSHP Ground Source Heat Pumps
HDD Heating Degree Days
HESS Hybrid Energy Storage Systems
HMI Human Machine Interface
HPS Hydro-Pumped Systems
HRU Heat Recovery Units
HTF Heat Transfer Fluid
HVAC Heating, Ventilation, Air Conditioning
HVDC High Voltage Direct Current
IAM Incident Angle Modifier
ICT Information and Computer Technology
ID Integrated Design
IED Integrated Energy Design
IoT Internet of Things
k-NN k-Nearest Neighbor
KPI Key Performance Indicator
LCA LifeCycle Analysis
LCC LifeCycle Cost
LCCA LifeCycle Cost Assessment
LFC Linear Fresnel Collectors
LFR Linear Fresnel Reflector
LOLP Loss Of Load Probability
MAPE Mean Average Percentage Error
MS Member States
MS Molten Salt
MS-TES Molten Salt Thermal Energy Storage
NARX Nonlinear AutoRegressive network with eXogenous input
NUS National University of Singapore
NZEB Nearly Zero-Energy Building
ORC Organic Rankine Cycle
PCM Phase Change Material
PEV Plug-in Electric Vehicles
PLC Programmable Logic Controller
PMP Performance Measurement Protocols
PMV Predicted Mean Vote
POD Point Of Delivery
PPD Percentage of People Dissatisfied
PSO Particle Swarm Optimization
PTC Parabolic Trough Collectors
PV PhotoVoltaic
R Pearson's coefficient
RES Renewable Energy Sources
RforI Research for Innovation
RH Relative Humidity
RMSE Root Mean Squared Error
SCTF Single Coil Twin Fan
SDE School of Design and Environment
SEER Seasonal Energy Efficiency Ratio
SHC Solar Heating and Cooling
SME Small and Medium Enterprises
SMERC SMart grid Energy Research Center
SMES Superconducting Magnetic Energy Storage
SPSS Statistical Package for Social Sciences
TES Thermal Energy Storage
V2B Vehicle-to-Building
V2G Vehicle-to-Grid
VRFB Vanadium Redox Flow Batteries
WT Wind Turbine
ZEB Zero-Energy Buildings

Chapter written by Nikos KAMPELIS.

1

The Role of Smart Grids in the Building Sector

A smart grid is a dynamically interactive real-time infrastructure concept that encompasses the many visions of the stakeholders of diverse energy systems (El-Hawary 2014). Smart grids are electrical power grids that are more efficient and more resilient, and therefore “smarter”, than existing conventional power grids. The smartness is focused not only on the elimination of blackouts, but also on making the grid greener, more efficient, adaptable to customers’ needs, and therefore, less costly (El-Hawary 2014; Giordano et al. 2013). Smart grids incorporate innovative IT technology that allows for two-way communication between the utility and its customers/users. As a result, the sensing along the transmission lines and the sensing from the customer’s side is what makes the grid “smart”.

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