Clustering a building stock towards representative buildings in the context of air-conditioning electricity demand flexibility

References

• Bruninx, Kenneth, Yury Dvorkin, Erik Delarue, William D'haeseleer, and Daniel S. Kirschen. 2018. “Valuing Demand Response Controllability via Chance Constrained Programming.” IEEE Transactions on Sustainable Energy 9: 178–187. doi: 10.1109/TSTE.2017.2718735
   Web of Science ®Google Scholar
• Buttitta, Giuseppina, William Turner, and Donal Finn. 2017. “Clustering of Household Occupancy Profiles for Archetype Building Models.” Energy Procedia 111: 161–170. 8th International Conference on Sustainability in Energy and Buildings, SEB-16, September, 11–13, 2016, Turin, Italy. doi: 10.1016/j.egypro.2017.03.018
   Google Scholar
• Callaway, Duncan S. 2009. “Tapping the Energy Storage Potential in Electric Loads to Deliver Load Following and Regulation, with Application to Wind Energy.” Energy Conversion and Management 50 (5): 1389–1400. doi: 10.1016/j.enconman.2008.12.012
   Web of Science ®Google Scholar
• Corbin, Charles D. 2014. “Assessing Impact of Large-Scale Distributed Residential HVAC Control Optimization on Electricity Grid Operation and Renewable Energy Integration.” PhD diss., University of Colorado.
   Google Scholar
• Corbin, C. D., and G. P. Henze. 2017a. “Predictive Control of Residential HVAC and Its Impact on the Grid. Part I: Simulation Framework and Models.” Journal of Building Performance Simulation 10 (3): 294–312. doi: 10.1080/19401493.2016.1231220
   Web of Science ®Google Scholar
• Corbin, C. D., and G. P. Henze. 2017b. “Predictive Control of Residential HVAC and Its Impact on the Grid. Part II: Simulation Studies of Residential HVAC as a Supply Following Resource.” Journal of Building Performance Simulation 10 (4): 365–377. doi: 10.1080/19401493.2016.1231221
   Web of Science ®Google Scholar
• Eberhart, Russell, and James Kennedy. 1995. “A New Optimizer using Particle Swarm Theory.” In Proceedings of the Sixth International Symposium on Micro Machine and Human Science. MHS'95, 39–43. IEEE, October 4-6, 1995, Nagoya, Japan
   Google Scholar
• EIA. 2017. “How Much Energy Is Consumed in Residential and Commercial Buildings in the United States?” Accessed September 2017. http://www.eia.gov/tools/faqs/faq.cfm?id=86&t=1.
   Google Scholar
• EU. 2010. “Directive 2010/31/EU of the European Parliament and of the Council of 19 May 2010 on the Energy Performance of Buildings.” Accessed September 2017. https://ec.europa.eu/energy/en/topics/energy-efficiency/buildings.
   Google Scholar
• Gaitani, N., C. Lehmann, M. Santamouris, G. Mihalakakou, and P. Patargias. 2010. “Using Principal Component and Cluster Analysis in the Heating Evaluation of the School Building Sector.” Applied Energy 87 (6): 2079–2086. doi: 10.1016/j.apenergy.2009.12.007
   Web of Science ®Google Scholar
• Gao, Xuefeng, and Ali Malkawi. 2014. “A New Methodology for Building Energy Performance Benchmarking: An Approach Based on Intelligent Clustering Algorithm.” Energy and Buildings 84: 607–616. doi: 10.1016/j.enbuild.2014.08.030
   Web of Science ®Google Scholar
• Geyer, Philipp, Arno Schlüter, and Sasha Cisar. 2017. “Application of Clustering for the Development of Retrofit Strategies for Large Building Stocks.” Advanced Engineering Informatics 31: 32–47. doi: 10.1016/j.aei.2016.02.001
   Web of Science ®Google Scholar
• Goy, Solène, and Donal Finn. 2015. “Estimating Demand Response Potential in Building Clusters.” Energy Procedia 78: 3391–3396. 6th International Building Physics Conference, IBPC 2015. doi: 10.1016/j.egypro.2015.11.756
   Google Scholar
• Hedegaard, Karsten, Brian Vad Mathiesen, Henrik Lund, and Per Heiselberg. 2012. “Wind Power Integration Using Individual Heat Pumps – Analysis of Different Heat Storage Options.” Energy 47 (1): 284–293. doi: 10.1016/j.energy.2012.09.030
   Web of Science ®Google Scholar
• Iacovella, Sandro, Frederik Ruelens, Pieter Vingerhoets, Bert Claessens, and Geert Deconinck. 2015. “Cluster Control of Heterogeneous Thermostatically Controlled Loads Using Tracer Devices.” IEEE Transactions on Smart Grid 8 (2): 528–536.
   Web of Science ®Google Scholar
• Jain, Anil K., M. Narasimha Murty, and Patrick J. Flynn. 1999. “Data Clustering: A Review.” ACM Computing Surveys 31 (3): 264–323. doi: 10.1145/331499.331504
   Web of Science ®Google Scholar
• Jones, P. J., S. Lannon, and J. Williams. 2001. “Modeling Building Energy Use at Urban Scale.” In Proceedings of Building Simulation, 175–180, August 13-15, 2001, Rio de Janeiro, Brazil
   Google Scholar
• Jota, Patricia R. S., Valéria R. B. Silva, and Fábio G. Jota. 2011. “Building Load Management Using Cluster and Statistical Analyses.” International Journal of Electrical Power and Energy Systems 33 (8): 1498–1505. doi: 10.1016/j.ijepes.2011.06.034
   Web of Science ®Google Scholar
• Judkoff, Ron, Ben Polly, Marcus Bianchi, and Joel Neymark. 2010. Building Energy Simulation Test for Existing Homes (BESTEST-EX); Phase 1 Test Procedure: Building Thermal Fabric Cases. Technical Report. National Renewable Energy Lab.(NREL), Golden, CO.
   Google Scholar
• Krejcie, Robert V., and Daryle W. Morgan. 1970. “Determining Sample Size for Research Activities.” Educational and Psychological Measurement 30 (3): 607–610. doi: 10.1177/001316447003000308
   Web of Science ®Google Scholar
• Liu, Benjamin Y. H., and Richard C. Jordan. 1960. “The Interrelationship and Characteristic Distribution of Direct, Diffuse and Total Solar Radiation.” Solar Energy 4 (3): 1–19. doi: 10.1016/0038-092X(60)90062-1
   Web of Science ®Google Scholar
• MathWorks. 2017b. “Linkage. Agglomerative Hierarchical Cluster Tree.” Accessed October 2017. https://mathworks.com/help/stats/linkage.html.
   Google Scholar
• MathWorks. 2017a. “Clusterdata. Agglomerative Clusters from Data.” Accessed September 2017. https://mathworks.com/help/stats/clusterdata.html.
   Google Scholar
• Nahmmacher, Paul, Eva Schmid, Lion Hirth, and Brigitte Knopf. 2016. “Carpe Diem: A Novel Approach to Select Representative Days for Long-term Power System Modeling.” Energy 112: 430–442. doi: 10.1016/j.energy.2016.06.081
   Web of Science ®Google Scholar
• Patteeuw, Dieter, Kenneth Bruninx, Alessia Arteconi, Erik Delarue, William D'haeseleer, and Lieve Helsen. 2015. “Integrated Modeling of Active Demand Response with Electric Heating Systems Coupled to Thermal Energy Storage Systems.” Applied Energy 151: 306–319. doi: 10.1016/j.apenergy.2015.04.014
   Web of Science ®Google Scholar
• Patteeuw, Dieter, Gregor P. Henze, and Lieve Helsen. 2016. “Comparison of Load Shifting Incentives for Low-energy Buildings with Heat Pumps to Attain Grid Flexibility Benefits.” Applied Energy 167: 80–92. doi: 10.1016/j.apenergy.2016.01.036
   Web of Science ®Google Scholar
• Reynders, Glenn, Jan Diriken, and Dirk Saelens. 2014. “Quality of Grey-box Models and Identified Parameters as Function of the Accuracy of Input and Observation Signals.” Energy and Buildings 82: 263–274. doi: 10.1016/j.enbuild.2014.07.025
   Web of Science ®Google Scholar
• Santamouris, M., G. Mihalakakou, P. Patargias, N. Gaitani, K. Sfakianaki, M. Papaglastra, C. Pavlou, et al. 2007. “Using Intelligent Clustering Techniques to Classify the Energy Performance of School Buildings.” Energy and Buildings 39 (1): 45–51. doi: 10.1016/j.enbuild.2006.04.018
   Web of Science ®Google Scholar
• UIUC, and LBNL. 2005. EnergyPlus Engineering Reference: The Reference to EnergyPlus Calculations. Technical Report. US Department of Energy.
   Google Scholar
• U.S. Energy Information Administration. 2009. “Residential Energy Consumption Survey (RECS).” Accessed 2009. http://www.eia.gov/consumption/residential/.
   Google Scholar
• Ward Jr, Joe H. 1963. “Hierarchical Grouping to Optimize an Objective Function.” Journal of the American Statistical Association 58 (301): 236–244. doi: 10.1080/01621459.1963.10500845
   Web of Science ®Google Scholar
• Yamaguchi, Y., Y. Shimoda, and M. Mizuno. 2007. “Proposal of a Modeling Approach Considering Urban Form for Evaluation of City Level Energy Management.” Energy and Buildings 39 (5): 580–592. doi: 10.1016/j.enbuild.2006.09.011
   Web of Science ®Google Scholar
• Yang, Junjing, Chao Ning, Chirag Deb, Fan Zhang, David Cheong, Siew Eang Lee, Chandra Sekhar, and Kwok Wai Tham. 2017. “k-Shape Clustering Algorithm for Building Energy Usage Patterns Analysis and Forecasting Model Accuracy Improvement.” Energy and Buildings 146: 27–37. doi: 10.1016/j.enbuild.2017.03.071
   Web of Science ®Google Scholar