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The recent dispositions related to the energy performance of buildings, launched by the European Directives 2002/91/EC and 2010/31/EU, turned attention to the Energy Performance Certificate (EPC). The aim of this study is to investigate the economic effects of the recent Italian statutory provisions related to energy performance of buildings on listing behaviour. With this aim an hedonic regression analysis is performed, in order to measure the impact of EPC level on listing prices. The study, based on a set of more than 500 housing property asset collected in 2012 from real estate advertisements websites, is focused on the Turin real estate market as a case study. Furthermore this paper contributes to the early limited literature on implication of the impact of EPC level on Italian housing market, representing one of the first systematic evidence about the energy certifications in the housing listing prices. Aestimum, Aestimum 65 (2014)

The recent dispositions related to the energy performance of buildings, launched by the European Directives 2002/91/EC and 2010/31/EU, turned attention to the Energy Performance Certificate (EPC). The aim of this study is to investigate the economic effects of the recent Italian statutory provisions related to energy performance of buildings on listing behaviour. With this aim an hedonic regression analysis is performed, in order to measure the impact of EPC level on listing prices. The study, based on a set of more than 500 housing property asset collected in 2012 from real estate advertisements websites, is focused on the Turin real estate market as a case study. Furthermore this paper contributes to the early limited literature on implication of the impact of EPC level on Italian housing market, representing one of the first systematic evidence about the energy certifications in the housing listing prices. Aestimum, Aestimum 65 (2014)

Solar tracking systems increase the electricity production by about 30% relative to fixed installations. A robust design of the mechanical system requiring less material than 100kg steel per kW nominal PV module power is essential to further improve the economics of PV tracker plants. The Solar Wings approach reaches this goal by using steel cables as a mounting system for the PV modules and benefits by the long-time experience of project partner BMF using steel cables in transportation systems such as ski-lift, funicular, aerial passenger lines. Tests with the first Solar Wings prototype in Switzerland passed successfully. The first 600 kW PV plant powered by the one axis Solar Wings tracking system will put into operation in December 2008 in Southern Germany. To maximize reliability and reduce maintenance costs only one electrical three-phase asynchronous motor is used to track 100kW PV modules. A two-axis tracking Solar Wings system will be available next year. Further development targets are low optical concentration by the use of planar mirrors mounted on a parallel axis to the PV module axis. PV modules and mirrors track individually and thus an increase of the electricity production of higher than 60% relative to fixed mounted installation is expected. First results of the measured increase of performance by individual tracking of the planar mirrors and the PV modules, performed on a small scale dish model, are reported. 23rd European Photovoltaic Solar Energy Conference and Exhibition, 1-5 September 2008, Valencia, Spain; 2790-2794

Solar tracking systems increase the electricity production by about 30% relative to fixed installations. A robust design of the mechanical system requiring less material than 100kg steel per kW nominal PV module power is essential to further improve the economics of PV tracker plants. The Solar Wings approach reaches this goal by using steel cables as a mounting system for the PV modules and benefits by the long-time experience of project partner BMF using steel cables in transportation systems such as ski-lift, funicular, aerial passenger lines. Tests with the first Solar Wings prototype in Switzerland passed successfully. The first 600 kW PV plant powered by the one axis Solar Wings tracking system will put into operation in December 2008 in Southern Germany. To maximize reliability and reduce maintenance costs only one electrical three-phase asynchronous motor is used to track 100kW PV modules. A two-axis tracking Solar Wings system will be available next year. Further development targets are low optical concentration by the use of planar mirrors mounted on a parallel axis to the PV module axis. PV modules and mirrors track individually and thus an increase of the electricity production of higher than 60% relative to fixed mounted installation is expected. First results of the measured increase of performance by individual tracking of the planar mirrors and the PV modules, performed on a small scale dish model, are reported. 23rd European Photovoltaic Solar Energy Conference and Exhibition, 1-5 September 2008, Valencia, Spain; 2790-2794

{"references": ["U.S. Energy Information Administration. \"How much energy is\nconsumed in residential and commercial buildings in the United States?\"\nAvailable at: http://www.eia.gov/tools/faqs/faq.cfm?id=86&t=1", "S. Darby, \"The effectiveness of feedback on energy consumption.\"\nEnvironmental Change Institute, University of Oxford, 2006. Available\nat: http://www.globalwarmingisreal.com/energyconsump-feedback.pdf.\nVisited: September 2015", "J. S. John, \"Putting energy disaggregation tech to the test,\" November,\n2013. Greentech Media. Available at:\nhttp://www.greentechmedia.com/articles/read/putting-energydisaggregation-tech-to-the-test.\nVisited: September 2015", "A. Zoha, A. Gluhak, M. A. Imran, S. Rajasegarar, \"Non-intrusive load\nmonitoring approaches for disaggregated energy sensing: a survey,\"\nSensors, vol. 12, no. 12, pp. 16838-16866, December 2012.", "G. W. Hart, \"Nonintrusive appliance load monitoring,\" in Proc. of the\nIEEE, vol. 80, pp. 1870-1891, December 1992.", "M. Baranski, J. Voss, \"Non-intrusive appliance load monitoring based\non Optical Sensor,\" IEEE Bologna PowerTech Conference, Bologna,\nItaly, June 2003. Available at:\nhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1304732", "L. Farinaccio, R. Zmeureanu, \"Using a pattern recognition approach to\ndisaggregate the total electricity consumption in a house into the major\nen-uses,\" Elsevier, Energy and Buildings, vol. 30, no. 3, pp. 245-259,\nAugust 1999.", "J. M. Abreu, F. C. Pereira, P. Ferr\u00e3o, \"Using pattern recognition to\nidentify habitual behavior in residential electricity consumption,\"\nElsevier, Energy and Buildings, vol. 49, pp. 479-487, June 2012.", "C. Beckel, L. Sadamori, S. Santini, \"Automatic socio-economic\nclassification of households using electricity consumption data,\" in\nProc. of the 4th international conference on future energy systems, New\nYork, 2013, pp. 75-86.\n[10] H. Zhao, F. Magoul\u00e8s, \"A review on the prediction of building energy\nconsumption,\" Elsevier, Renewable and Sustainable Energy Reviews,\nvol. 16, no. 6, pp. 3586-3592, August 2012.\n[11] G. K. F. Tso, K. K. W. Yau, \"Predicting electricity energy consumption:\nA comparison of regression analysis, decision tree and neural networks,\"\nElsevier, Energy, vol. 32, no. 9, pp. 1761-1768, September 2007.\n[12] F. Farzan, S. A. Vaghefi, K. Mahani, M. A. Jafari, J. Gong, \"Operational\nplanning for multi-building portfolio in an uncertain energy market,\"\nElsevier, Energy and Buildings, vol. 103, pp. 271-283, September 2015."]} Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.