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OPTICA APPLICATA; 04/2013; ISSN 1429-7507

This work has been developed under the AGROinLOG Project, “Demonstration of innovative integrated biomass logistics centres for the Agro-industry sector in Europe”. An Integrated Biomass Logistics Center (IBLC), is based on the introduction of new production chains into existing agro-industries by using new biomass feedstock. The AGROinLOG Project has dedicated great attention to investigate the potential of cereal chaff as a valuable resource.Chaff is the fine fraction of the thrashing residues, not usually collected. Chaff is made up of glumes, seed husks, rachis and the tinner part of the cereal stems, whole and cracked kernels, as well as weed seeds.Currently there are several mechanical solutions available on the market for chaff recovery, and others are still at prototype stage, but theyare not so common and very often unknown to the farmers.So far, the literature reportsfew cases of chaff collection with the specific purpose of weed seeds removal, but it still lacks specificexperiments on these machinesintentionally used for biomass collection.For this reason, during the Project AGROinLOG a series of large field tests were performed using an independent scientific approach with different kind of chaff harvesting technologiesin France, Sweden and Italy from 2017 to 2019.The present study collects the results of these activities with the aim to fill that gap and provide deeper understanding in the possibility to enhance the current cereal harvesting method, in order to improve the quantity of biomass collected by including the chaff. Proceedings of the 29th European Biomass Conference and Exhibition, 26-29 April 2021, Online, pp. 62-68

Wave energy is an important renewable energy source. Previous studies of wave energy conversion (WEC) have focused on the maximum power take-off (PTO) techniques of a single machine. However, there is a lack of research on the energy and power quality of wave farm systems. Owing to the pulsating nature of ocean waves and popular PTO devices, the generated electrical power suffers from severe fluctuations. Existing solutions require extra energy storage and overrated power converters for wave power integration. In this study, we developed a master-slave wave farm system with rotor inertia energy storage; this system delivers self-smoothed power output to the grid and reduces the number of converters. Two control methods based on the moving average filter (MAF) and energy filter (EF) are proposed to smooth the output power of wave farms. RTDS simulations show that the proposed systems and control methods facilitate simple and smooth grid integration of wave energy. Keywords: Wave farm, Energy storage, Power smoothing, Power quality, Energy quality

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)

{"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.

The importance of emission control has increased sharply due to increased need of energy from combustion. However, biomass utilization in energy production is not free from problems because of physical and chemical characteristics which are substantially different from conventional energy sources. In this situation, the quantity and quality of emissions as well as used renewable source as wood or corn grain are often unknown. To assess this problem the paper addresses the objectives to quantify the amount of greenhouse gases during the combustion of corn as compared to the emissions in fossil combustion (natural gas, LPG and diesel boiler). The test was carried out in Friuli Venezia Giulia in 2006-2008 to determine the air pollution (CO, NO, NO2, NOx, SO2 and CO2) from fuel combustion in the family boilers with power between 20-30 kWt. The flue gas emission was measured with a professional semi-continuous multi-gas analyzer, (Vario plus industrial, MRU air Neckarsulm-Obereisesheim). Data showed a lower emission of fossil fuel compared to corn in family boilers in reference to pollutants in the flue gas (NOx, SO2 and CO). In particular way the biomass combustion make a higher concentration of carbon monoxide (for a incomplete combustion because there aren’t a good mixing between fuel and air) and nitrogen oxides (in relation at higher content of nitrogen in herbaceous biomass in comparison of another fuel). Proceedings of the 19th European Biomass Conference and Exhibition, 6-10 June 2011, Berlin, Germany, pp. 1296-1304

Recent extreme weather events have resulted in an ongoing discussion on the issues of land use and compensation payments within Austrian agriculture. Building on a functional evaluation system for agricultural lands as developed within the Interreg IIIB project “ILUP”, the national project “Agriculture and Flooding” has as its goal to classify the flood-protection contribution and flood sensitivity of agricultural lands. This, in turn, enables the recommendation of targeted measures for potentially improving flood situations, as well as an estimate of their implementation costs. In addition to the digital soil map, other fundamental sources used for the project are the digital flood risk map, IACS land-use data and works by the Institute for Land and Water Management Research. Reference values and marginal returns sourced from the Federal Institute of Agricultural Economics also flow into the cost estimates for the recommended combination. The results will contribute to an understanding of the multifunctionality of agricultural lands and to the setting of priorities on a regional scale regarding packaged flood-prevention and damage-minimization. However, the results at hand can only serve as one step toward regional flood protection projects, whose development will require the cooperation of all interest groups.