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Methods for Asssessing Energy Efficiency of Grain Dryers

Abstract

The article presents an algorithm for calculating selected energy assessment indexes for grain driers. Particular attention was paid to the conversion of the equations obtained for the operating conditions of the drying process into equations allowing the calculation of indexes for the standard drying conditions. The indexes obtained allow a proper comparison of dryers operating in varied atmospheric conditions, as well as humidity and temperature of the dried material.

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CLIMATE PARAMETERS IN BUILT ENVIRONMENT FROM ENERGETIC POINT OF VIEW – TOWARDS CLIMATE SEVERITY INDEX IN HUNGARY

Abstract

The building energy sector is not immune from the physical impacts of climate change and must adapt. The impacts are more gradual, such as changes to heating and cooling demand. Disruptions to the energy system can also have significant knock-on effects on other critical services. To improve the climate resilience of the building energy system, governments need to design and implement frameworks that encourage prudent adaptation, while the private sector should assess the risks and impacts as part of its investment decisions. Comprehensive studies covering the impact of climate change on the building energy sector are still lacking, though some regional and sector-specific analysis exists. The buildings sector has been examined in more depth than most, with studies finding that temperature increases are expected to boost demand for air conditioning, while fuel consumption for space heating will be reduced. For the follow-up research activity the question has been posed: How can the climate changing trends and the building sector rising energy demand meet in urban environment? As an outlook this present paper can be defined as an ex-ante document in the DENZERO Project towards generating the Hungarian Climate Severity/Energy Index.

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Measuring the Size of the Dutch Bio-Economy

, 2013, no. 6, pp. 2751–2769. doi: 10.3390/su5062751 U.S. Energy Information Administration. 2016). Annual Energy Outlook 2016,With Projections to 2040. Washington, DC. Retrieved from https://www.eia.gov/forecasts/aeo/pdf/0383(2016).pdf USDA. 2011. Biobased Economy Indicators, A Report to the U.S. Congress. Washington D.C. Retrieved from www.usda.gov/oce/reports/energy/index.htm . VANDERMEULEN, V. – PRINS, W. – NOLTE, S. – VAN HUYLENBROECK, G. 2011. How to measure the size of a bio-based economy: Evidence from Flanders. In Biomass and Bioenergy, vol

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Assessment of Political Vulnerabilities on Security of Energy Supply in the Baltic States

. The Heritage Foundation. “Coordinated Terrorist Attacks on Global Energy Infrastructure: Modelling the Risks” (2011) // http://thf_media.s3.amazonaws.com/2011/pdf/sr0088.pdf . 42. Toft, Peter, Arash Duero, and Arunas Bieliauskas. “Terrorist targeting and energy security.” Energy Policy 38 (2013): 4411–4421 //DOI: http://dx.doi.org/10.1016/j.enpol.2010.03.070 . 43. U.S. Chamber of Commerce Institute for 21st Century Energy. “Index of U.S. Energy Security Risk: Assessing America’s vulnerabilities in a global energy market” (2013) // https

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Cost Allocation Model for Net-Zero Energy Buildings under Community-Based Reward Penalty Mechanism

.renene.2017.11.093 [20] Fridgen G., Kahlen M., Ketter W., Rieger A., Thimmel M. One rate does not fit all: an empirical analysis of electricity tariffs for residential microgrids. Applied Energy 2018:210:800–814. doi:10.1016/j.apenergy.2017.08.138 [21] Liang-Cheng Y., João F. D. R., Hai X. L. Analysis of feed-in tariff policies for solar photovoltaic in China 2011–2016. Applied Energy 2017:203:496–505. doi:10.1016/j.apenergy.2017.06.037 [22] Ritter M., Deckert L. Site assessment, turbine selection, and local feed-in tariffs through the wind energy

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Share of road transport in greenhouse gas emissions in Poland in 1988–2015

of pollutant emission inventories that may possibly be applied in the road transport: - the index of pollutant emission and fuel mass consumption, - the energy index of pollutant emission and energy consumption. The index of pollutant emission is defined as a derivative of pollutant emission, taken as a function of mass fuel consumption (m f ) of the variable mass fuel consumption [ Chłopek 1999 ]: (5) W = dm dm f $$\text{W}=\frac{\text{dm}}{\text{d}{{\text{m}}_{\text{f}}}}$$ The national annual emission of

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Small-scale cyclic deposition in the Frasnian (Upper Devonian) of the Holy Cross Mountains, Poland

transition on the South Polish carbonate shelf. Acta Palaeontologica Polonica 51, 4, 609-646. Plumley, W.J., Risley, G.A., Graves, R.W., Kaley, M.E., 1962. Energy index for limestone interpretation and classification. [In:] Ham, W.E., (Ed): Classification of Carbonate Rocks. American Association Petrological Geological, Memoir 1, 85-107. Préat, A., Mamet, M., 1989. Sédimentation de la plateforme carbonatée givétienne Franco-Belge. Bulletin des Centres Rechearche Exploration-Production Aquitaine 13, 47-86. Préat, A. & Racki, G

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