A Review of Key Performance Indicators for Building Flexibility Quantification to Support the Clean Energy Transition

The transition to a sustainable society and a carbon-neutral economy by 2050 requires extensive deployment of renewable energy sources that, due to the aleatority and non-programmability of most of them, may seriously affect the stability of existing power grids. In this context, buildings are increasingly being seen as a potential source of energy flexibility for the power grid. In literature, key performance indicators, allowing different aspects of the load management, are used to investigate buildings’ energy flexibility. The paper reviews existing indicators developed in the context of theoretical, experimental and numerical studies on flexible buildings, outlining the current status and the potential future perspective. Moreover, the paper briefly reviews the range of grid services that flexible buildings can provide to support the reliability of the electric power system which is potentially challenged by the increasing interconnection of distributed variable renewable generation.

[1]  Vincenzo Antonucci,et al.  Grid interaction and environmental impact of a net zero energy building , 2020 .

[2]  Robert Ries,et al.  Investigating the Impact of Actual and Modeled Occupant Behavior Information Input to Building Performance Simulation , 2021, Buildings.

[3]  Fu Xiao,et al.  An interactive building power demand management strategy for facilitating smart grid optimization , 2014 .

[4]  Lieve Helsen,et al.  Quantification of flexibility in buildings by cost curves – Methodology and application , 2016 .

[5]  X. Xia,et al.  Combined residential demand side management strategies with coordination and economic analysis , 2016 .

[6]  Dirk Saelens,et al.  Energy flexible buildings: an evaluation of definitions and quantification methodologies applied to thermal storage , 2018 .

[7]  Maurizio Cellura,et al.  Modeling the energy and environmental life cycle of buildings: A co-simulation approach , 2017 .

[8]  Jaume Salom,et al.  Load matching, grid interaction, and advanced control , 2015 .

[9]  Yongjun Sun,et al.  Performance comparisons of two system sizing approaches for net zero energy building clusters under uncertainties , 2016 .

[10]  Rui Ma,et al.  Heuristic optimization for grid-interactive net-zero energy building design through the glowworm swarm algorithm , 2020 .

[11]  Anzar Mahmood,et al.  Prosumer based energy management and sharing in smart grid , 2018 .

[12]  I. Walker,et al.  Towards active buildings: Rating grid-servicing buildings , 2020 .

[13]  Paulo F. Ribeiro,et al.  History of demand side management and classification of demand response control schemes , 2013, 2013 IEEE Power & Energy Society General Meeting.

[14]  G. Krajačić,et al.  Modelling smart energy systems in tropical regions , 2018, Energy.

[15]  Johan Driesen,et al.  Grid Impact Indicators for Active Building Simulations , 2015, IEEE Transactions on Sustainable Energy.

[16]  Per Heiselberg,et al.  Energy flexibility of residential buildings using short term heat storage in the thermal mass , 2016 .

[17]  Dirk Saelens,et al.  Potential of structural thermal mass for demand-side management in dwellings , 2013 .

[18]  M. Cellura,et al.  A Review of Thermochemical Energy Storage Systems for Power Grid Support , 2020, Applied Sciences.

[19]  Lueder von Bremen,et al.  The Demand Side Management Potential to Balance a Highly Renewable European Power System , 2016 .

[20]  Maurizio Cellura,et al.  Investigation of design strategies and quantification of energy flexibility in buildings: A case-study in southern Italy , 2021 .

[21]  M.G.L.C. Loomans,et al.  Investigating the energy flexibility of Dutch office buildings on single building level and building cluster level , 2021 .

[22]  Ayako Taniguchi,et al.  Estimation of the contribution of the residential sector to summer peak demand reduction in Japan using an energy end-use simulation model , 2016 .

[23]  David Fischer,et al.  Model-based flexibility assessment of a residential heat pump pool , 2017 .

[24]  Wim Zeiler,et al.  Identification of a dynamic system model for a building and heating system including heat pump and thermal energy storage , 2020, MethodsX.

[25]  Rune Hylsberg Jacobsen,et al.  Demand response potential of ventilation systems in residential buildings , 2016 .

[26]  R. Fares,et al.  Grid-Interactive Efficient Buildings Technical Report Series: Overview of Research Challenges and Gaps , 2019 .

[27]  Johanna L. Mathieu,et al.  A framework for and assessment of demand response and energy storage in power systems , 2013, 2013 IREP Symposium Bulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid.

[28]  Weijun Gao,et al.  Techno-economic performance analysis of zero energy house applications with home energy management system in Japan , 2020 .

[29]  Li-Chen Fu,et al.  Demand-side management in residential community realizing sharing economy with bidirectional PEV while additionally considering commercial area , 2020 .

[30]  Pierluigi Mancarella,et al.  Techno-economic and environmental modelling and optimization of flexible distributed multi-generation options , 2014 .

[31]  Per Heiselberg,et al.  Zero energy buildings and mismatch compensation factors , 2011 .

[32]  Giuseppina Ciulla,et al.  THE REDESIGN OF AN ITALIAN BUILDING TO REACH NET ZERO ENERGY PERFORMANCES: A CASE STUDY OF THE SHC TASK 40 ECBCS Annex 52 , 2011 .

[33]  Laia Ferrer-Martí,et al.  Heuristic indicators for the design of community off-grid electrification systems based on multiple renewable energies , 2013 .

[34]  Gail Brager,et al.  Commercial Office Plug Load Energy Consumption Trends and the Role of Occupant Behavior , 2016 .

[35]  Peter Lund,et al.  Review of energy system flexibility measures to enable high levels of variable renewable electricity , 2015 .

[36]  Fu Xiao,et al.  Quantifying uncertainty in the aggregate energy flexibility of high-rise residential building clusters considering stochastic occupancy and occupant behavior , 2020 .

[37]  Dirk Saelens,et al.  Generic characterization method for energy flexibility: Applied to structural thermal storage in residential buildings , 2017 .

[38]  Roberto Lollini,et al.  New domain for promoting energy efficiency: Energy Flexible Building Cluster , 2018 .

[39]  Kun Zhang,et al.  Evaluating the impact of thermostat control strategies on the energy flexibility of residential buildings for space heating , 2021, Building Simulation.

[40]  Hassam ur Rehman,et al.  IEA EBC Annex83 Positive Energy Districts , 2021, Buildings.

[41]  Thomas Nuytten,et al.  Flexibility of a combined heat and power system with thermal energy storage for district heating , 2013 .

[42]  Karsten Voss,et al.  Net zero energy buildings: A consistent definition framework , 2012 .

[43]  Joachim Bertsch,et al.  Flexibility in Europe's power sector - an additional requirement or an automatic complement? , 2013 .

[44]  Leslie K. Norford,et al.  Experimental Study of Grid Frequency Regulation Ancillary Service of a Variable Speed Heat Pump , 2016, IEEE Transactions on Power Systems.

[45]  Mia Ala-Juusela,et al.  Defining and operationalising the concept of an energy positive neighbourhood , 2016 .

[46]  João Neves,et al.  A Literature Review of Methodologies Used to Assess the Energy Flexibility of Buildings , 2016 .

[47]  Karsten Voss,et al.  Load Matching and Grid Interaction of Net Zero Energy Buildings , 2010 .

[48]  Jaume Salom,et al.  Analysis of load match and grid interaction indicators in net zero energy buildings with simulated and monitored data , 2014 .

[49]  Thibault Péan,et al.  Towards standardising market-independent indicators for quantifying energy flexibility in buildings , 2020 .

[50]  Dirk Saelens,et al.  Assessing electrical bottlenecks at feeder level for residential net zero-energy buildings by integrated system simulation , 2012 .

[51]  P. André,et al.  Smart grid energy flexible buildings through the use of heat pumps and building thermal mass as energy storage in the Belgian context , 2015 .

[52]  Sebastian Stinner,et al.  Quantifying the operational flexibility of building energy systems with thermal energy storages , 2016 .

[53]  Anna Joanna Marszal,et al.  IEA EBC Annex 67 Energy Flexible Buildings , 2017 .

[54]  Erina Ferro,et al.  Load match optimisation of a residential building case study: A cross-entropy based electricity storage sizing algorithm , 2015 .

[55]  S. Attia,et al.  Net Zero Buildings—A Framework for an Integrated Policy in Chile , 2019, Sustainability.

[56]  P. Dobra,et al.  Key performance indicators for the evaluation of building indoor air temperature control in a context of demand side management: An extensive analysis for Romania , 2021 .

[57]  Lieve Helsen,et al.  The Impact of Load Profile on the Grid-Interaction of Building Integrated Photovoltaic (BIPV) Systems in Low-Energy Dwellings , 2010 .

[58]  S. Oberthür,et al.  Assessing the EU’s 2030 Climate and Energy Policy Framework: Incremental change toward radical transformation? , 2020, Review of European, Comparative & International Environmental Law.

[59]  M. Cellura,et al.  Load match and grid interaction optimization of a net zero energy building through electricity storage: An Italian case-study , 2016, 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC).

[60]  Michael E. Webber,et al.  Quantifying demand flexibility based on structural thermal storage and comfort management of non-residential buildings: A comparison between hot and cold climate zones , 2017 .

[61]  Muneeb Dawood,et al.  Demand response in blocks of buildings: opportunities and requirements , 2017 .

[62]  Arye Nehorai,et al.  An Optimal and Distributed Demand Response Strategy With Electric Vehicles in the Smart Grid , 2014, IEEE Transactions on Smart Grid.

[63]  Sebastian Herkel,et al.  Load shifting using the heating and cooling system of an office building: Quantitative potential evaluation for different flexibility and storage options , 2017 .

[64]  Santiago Grijalva,et al.  A Review of Reinforcement Learning for Autonomous Building Energy Management , 2019, Comput. Electr. Eng..

[65]  Henrik Madsen,et al.  Characterizing the energy flexibility of buildings and districts , 2018, Applied Energy.