Open Access
Issue |
E3S Web Conf.
Volume 197, 2020
75th National ATI Congress – #7 Clean Energy for all (ATI 2020)
|
|
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Article Number | 03001 | |
Number of page(s) | 14 | |
Section | Management of Energy Supply and Demand. Smart Grid | |
DOI | https://doi.org/10.1051/e3sconf/202019703001 | |
Published online | 22 October 2020 |
- International Energy Agency (IEA), Global status report for buildings and construction 2019, IEA, Paris (2019), available at: https://www.iea.org/reports/global-status-report-for-buildings-and-construction-2019 [accessed on September 2, 2020] [Google Scholar]
- T. Fleiter, R. Elsland, M. Rehfeldt, J. Steinbach, U. Reiter, G. Catenazzi, M. Jakob, C. Rutten, R. Harmsen, F. Dittmann, P. Riviére, P. Stabat, Profile of heating and cooling demand in 2015, D3.1 report, Heat Roadmap Europe 2050, A low-carbon heating and cooling strategy (2017), available at: https://heatroadmap.eu/wpcontent/uploads/2018/11/HRE4_D3.3andD3.4.pdf [accessed on September 2, 2020] [Google Scholar]
- D. Testi, M. Rocca, E. Menchetti, S. Comelato, Criticalities in the NZEB retrofit of scholastic buildings: analysis of a secondary school in Centre Italy, Energy Procedia, 140, 252-264 (2017) [CrossRef] [Google Scholar]
- S. Della Torre, M. Bocciarelli, L. Daglio, R. Neri, Buildings for education – a multidisciplinary overview of the design of school buildings, Springer (2020) [CrossRef] [Google Scholar]
- M. Dovjak, A. Kukec, Creating healthy and sustainable buildings, Springer (2019) [CrossRef] [Google Scholar]
- L. Kaufman, P.J. Rousseeuw, Finding groups in data – an introduction to cluster analysis, John Wiley & Sons (2005) [Google Scholar]
- G. Gan, C. Ma, J. Wu, Data clustering: theory, algorithms, and applications, ASA-SIAM Series on Statistics and Applied Probability (2007) [Google Scholar]
- J. Yang, C. Ning, C. Deb, F. Zhang, D. Cheong, S.E. Lee, C. Sekhar, K. Tham, k-shape clustering algorithm for building energy usage patterns analysis and forecasting model accuracy improvement, Energy and Buildings, 146, 27-37 (2017) [CrossRef] [Google Scholar]
- A. Zakovorotnyi, A. Seerig, Building energy data analysis by clustering measured daily profiles, Energy Procedia, 122, 583-588 (2017) [CrossRef] [Google Scholar]
- P. Marrone, P. Gori, F. Asdrubali, L. Evangelisti, L. Calcagnini, G. Grazieschi, Energy benchmarking in educational buildings through cluster analysis of energy retrofitting, Energies, 11, pp. 20-649 (2018) [CrossRef] [Google Scholar]
- M. Santamouris, G. Mihalakakou, P. Patargias, N. Gaitani, K. Sfakianaki, M. Papaglastra, C. Pavlou, P. Doukas, E. Primikiri, V. Geros, M.N. Assimakopoulos, R. Mitoula, S. Zerefos, Using intelligent clustering techniques to classify the energy performance of school buildings, Energy and Buildings, 39, 45-51 (2007) [CrossRef] [Google Scholar]
- K. Li, Z. Ma, D. Robinson, J. Ma, A two-level clustering strategy for energy performance evaluation of university buildings, Proceedings of the 4th International Conference on Building Energy and Environment (COBEE 2018), Melbourne, Australia, Paper 061, 168-173 (2018) [Google Scholar]
- E. Schito, P. Conti, L. Urbanucci, D. Testi, Multi-objective optimization of HVAC control in museum environment for artwork preservation, visitors’ thermal comfort and energy efficiency, Building and Environment, 180, 107018, 15 pp. (2020). [CrossRef] [Google Scholar]
- P.J. Rousseeuw, Silhouettes: a graphical aid to the interpretation and validation of cluster analysis, Computational and Applied Mathematics, 20, 53-65 (1987) [CrossRef] [Google Scholar]
- D.B. Crawley, J.W. Hand, M. Kummert, B.T. Griffith, Contrasting the capabilities of building energy performance simulation programs, Building and Environment, 43, 66173 (2008) [CrossRef] [Google Scholar]
- D. Testi, E. Schito, E. Tiberi, P. Conti, W. Grassi, Building energy simulation by an inhouse full transient model for radiant systems coupled to a modulating heat pump, Energy Procedia, 78, 1135-1140 (2015) [CrossRef] [Google Scholar]
- E. Schito, D. Testi, Integrated maps of risk assessment and minimization of multiple risks for artworks in museum environments based on microclimate control, Building and Environment, 123, 585-600 (2017) [CrossRef] [Google Scholar]
- R. Gelaro and other 30 authors, The Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), Journal of Climate, 30, 5419-5454 (2017) [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
- P.W. O’Callaghan, S.D. Probert, Technical note – sol-air temperature, Applied Energy, 3, 307-311 (1977) [CrossRef] [Google Scholar]
- D. Testi, E. Schito, P. Conti, Cost-optimal sizing of solar thermal and photovoltaic systems for the heating and cooling needs of a Nearly Zero-Energy Building: design methodology and model description, Energy Procedia, 91, 517-527 (2016) [CrossRef] [Google Scholar]
- A. Franco, E. Schito, Definition of optimal ventilation rates for balancing comfort and energy use in indoor spaces using CO2 concentration data, Buildings, 10, 135, 19 pp. (2020) [CrossRef] [Google Scholar]
- F. D’Ettorre, P. Conti, E. Schito, D. Testi, Model predictive control of a hybrid heat pump system and impact of the prediction horizon on cost-saving potential and optimal storage capacity, Applied Thermal Engineering, 148, 524-535 (2019) [CrossRef] [Google Scholar]
- F. D’Ettorre, M. De Rosa, P. Conti, D. Testi, D. Finn, Mapping the energy flexibility potential of single buildings equipped with optimally-controlled heat pump, gas boilers and thermal storage, Sustainable Cities and Society, 50, 101-689, 13 pp. (2019) [Google Scholar]
- L. Urbanucci, F. D’Ettorre, D. Testi, A comprehensive methodology for the integrated optimal sizing and operation of cogeneration systems with thermal energy storage, Energies, 12, 875, 17 pp. (2019) [CrossRef] [Google Scholar]
- L. Gigoni, A. Betti, E. Crisostomi, A. Franco, M. Tucci, F. Bizzarri, D. Mucci, Dayahead hourly forecasting of power generation from photovoltaic plants, IEEE Transactions on Sustainable Energy, 9, 831-842 (2017) [CrossRef] [Google Scholar]
- C. Bartoli, P. Conti, A. Franco, D. Testi, Experimental analysis of an air heat pump for heating service using a “hardware-in-the-loop” system, Energies, 13, 4498, 18 pp. (2020) [CrossRef] [Google Scholar]
- L. Schibuola, M. Scarpa, C. Tambani, CO2-based ventilation control in energy retrofit: an experimental assessment, Energy, 143, 606-614 (2018) [CrossRef] [Google Scholar]
- A. Franco, F. Leccese, Measurement of CO2 concentration for occupancy estimation in educational buildings with energy efficiency purposes, Journal of Building Engineering, 101714 (2020), available online (https://doi.org/10.1016/j.jobe.2020.101714) [CrossRef] [Google Scholar]
- UNI, Air-conditioning systems for thermal comfort in buildings – General, classification and requirements – Offer, order and supply specifications, Standard UNI 10339 (in Italian), Italian National Agency for Unification (1995) [Google Scholar]
- X. Xie, Q. Xue, Y. Zhou, K. Zhu, Q. Liu, J. Zhang, R. Song, Mental health status among children in home confinement during the coronavirus disease 2019 outbreak in Hubei province, China, JAMA Pediatrics, Research Letter, April 24, E1-E3 (2020) [Google Scholar]
- M. Poletti, A. Raballo, Evidence on school closure and children’s social contact: useful for coronavirus disease (COVID-19)?, Eurosurveillance, 25, Letter to the editor, April 30, 1-2 (2020) [Google Scholar]
- E. Schito, D. Testi, W. Grassi, A proposal for new microclimate indexes for the evaluation of indoor air quality in museums, Buildings, 6, 41, 15 pp. (2016) [CrossRef] [Google Scholar]
- E. Schito, P. Conti, D. Testi, Multi-objective optimization of microclimate in museums for concurrent reduction of energy needs, visitors’ discomfort and artwork preservation risks, Applied Energy, 224, 147-159 (2018) [CrossRef] [Google Scholar]
- A. Franco, Balancing user comfort and energy efficiency in public buildings through social interaction by ICT systems, Systems, 8, 29, 16 pp. (2020) [CrossRef] [Google Scholar]
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