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12 ZNANOST NA DLANI SCIENTIFIC PAPER Z V E Z A S T R O J N I H I N Ž E N I R J E V S L O V E N I J E W W W. Z V E Z A - Z S I S. S I 2. Data OperatThe study is based on natural gas consumption data and corresponding weather related parameters for the region of Ljubljana, for a period since 2007 till Data were provided by the natural gas distribution company Energetika Ljubljana. Figure 1 shows examples of normalized natural gas (NNG) demand data for a typical winter season in daily resolution (upper plot), and two weeks of NNG demand in hourly resolution (lower plot). While the fluctuations in the upper plot are mainly caused by weather related conditions, the oscillations in the lower plot are a consequence of patterns of population behavior. Da NN a.. o r NN a Oct Nov Dec Jan Feb Mar Apr Date Jan 0 Feb 12 Feb Date Figure 1: Examples of normalized natural gas demand data in daily and hourly resolution 3. Forecasting requirements Forecasting requirements were defined for the winter seasons only, because natural gas consumption during the summer seasons is not complicated and doesn t require a sophisticated forecasting support. The forecasting requirement was defined with respect to the so called natural gas forecasting day (NGFD), spanning from 08:00 till 08:00+1 the next day, and since 2014 for the NGFD spanning from 06:00 till 06:00+1. The initial forecasting horizon was defined from 25 hours to 48 hours ahead. In 2012 the forecasting horizon was extended into short-term forecasts and thus comprised the full range from 1 to 48 hours ahead (in hourly resolution). Figure 2 illustrates the forecasting requirements, showing the forecasts generated for the next 48 hours ahead, and comparing past forecasts to the actual natural gas demand. a u de and ore a t Sun Mon Tue Wed Thu Fri Sat Sun Mon Tue ate da Figure 2: Forecasting requirements for short-term natural gas forecasting 4. Data analysis During the winter season, the outside temperature is the most influential factor affecting natural gas consumption. An online forecasting system requires temperature forecasts, which were in our case study provided by Slovenian Environment Agency (ARSO) in 6-hours intervals starting at 06:00 as follows: T6, T12, T18,, T72. Solar radiation also influences natural gas consumption but is currently not available as a forecast. Other weather related parameters do not have significant influences on natural gas consumption. Due to autoregressive behavior of natural gas consumption, past consumption has to be included as influential input, either as daily mean values (Y), or as hourly values (y). An important influence is represented by population related patterns, such as workdays, weekends and holidays, therefore these should be appropriately taken into account by the forecasting models. We encoded the holidays according to several simple rules, such as defining holiday as Sunday, and then statistically calculating the normalized weekly and daily natural gas consumption cycles, as shown in Fig Forecasting model A forecasting model was developed as a combination of separate forecasting models for each hour of the forecasting horizon (h = 1, 2,, 48 hours). Daily forecasts for the first NGFD, spanning over Weekly cycle Daily cycle Mon Tue Wed Thu Fri Sat Sun Day Hour Figure 3: Weekly and daily natural gas consumption cycles h = 1, 2,, 24 hours, and for the second NGFD, spanning over h = 25, 26,, 48 hours, are composed as a sum of corresponding hourly forecasts. Figure 4 shows the forecasting solution that is generating hourly and daily forecasts based on selected input data. Figure 4: Structure of the forecasting model Development of hourly forecasting models is based on a stepwise regression method which constructs the model by iteratively adding and removing regressors based on their statistical significance in a regression [16]. The method begins with an initial model and then compares the explanatory power of incrementally larger and smaller models. At each step, the p value of an F statistic is computed in order to test models both with and without a potential input. Tested inputs are iteratively added or removed from the model until the procedure converges to a locally optimal forecasting model with statistically significant input variables. Based on a wide pool of possible regressors, the stepwise regression method usually selects up to 20 different regressors for each hourly forecasting model. The advantage of using simple model structures is that such models are less prone to overfitting, compared to more complex models with hundreds of parameters (e.g. neural networks). The stepwise regression method also resolves the collinearity problem by reducing the available set of inputs to the relevant ones, and simultaneously defines relevant inputs and corresponding model parameters. Model development requires training of obtained model structures on several seasons of data, Z V E Z A S T R O J N I H I N Ž E N I R J E V S L O V E N I J E W W W. Z V E Z A - Z S I S. S I 22 23

13 Da NN a con t on o eca t ab. e o Oct Nov Dec Jan Feb Date o NN a con t on o eca t ab. e o 0 12 Jan 1 Jan 26 Jan 02 Feb Date

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19 V SREDIŠČU: AKADEMIJA STROJNIŠTVA 2016 Z V E Z A S T R O J N I H I N Ž E N I R J E V S L O V E N I J E W W W. Z V E Z A - Z S I S. S I SKUPNO DRUŽENJE Nadaljevanje začete diskusije o povezljivosti in tesnejšem sodelovanju se je nadaljevalo v 2. preddverju Cankarejvega doma, kjer so si vsi obiskovalci ogledali sekcijo skoraj šestdesetih posterjev, ki so nastali kot plod sodelovanja akademske sfere z gospodarstvom na področju razvoja in inovacij. Vsi posterji so bili objavljeni tudi v reviji Svet strojništva, ki je izšla na dan dogodka, prav vsi udeleženci pa so prejeli tudi izvod revije. Skupno neformalno druženje se je nadaljevalo ob pogostitvi in vedrem razpoloženju, to je bila hkrati tudi odlična priložnost navezovanja novih poslovnih stikov in sodelovanj. NAGRAJENCI AKADEMIJE STROJNIŠTVA 2016 NAGRADA ZA GLOBALNO PRODORNOST SLOVENSKEGA INŽENIRSTVA Aleksander Zalaznik, generalni direktor podjetja Danfoss Trata in višji podpredsednik Commercial Controls Aleksander Zalaznik, generalni direktor Danfoss Trate in višji podpredsednik Danfossove poslovnega področja Heating Commercial Controls, vodi družbo že od leta V času njegovega vodenja se je Danfoss Trata razvila v pomemben poslovni in tehnološki center za rešitve na področju regulacije prenosa toplote v ogrevalnih in hladilnih sistemih. Odlični poslovni rezultati, ki so rezultat zavzetih zaposlenih in zavezanosti vodstva k trajnostnemu razvoju poslovanja, kakovosti in inovativnosti, uvrščajo Danfoss Trato med vodilna podjetja v Evropi. Za svoje delo je prejel nagrado Časnika Finance za izjemne dosežke v gospodarstvu leta 2012 in nagrado Gospodarske zbornice Slovenije za izjemne gospodarske in podjetniške dosežke za leto Je tudi član Združenja Manager od leta 1998 in član upravnega odbora Združenja od 2008, aprila 2014 pa je bil izvoljen za predsednika Združenja. NAGRADA ZA GLOBALNO PRODORNOST SLOVENSKEGA INŽENIRSTVA dr. Hubert Kosler, direktor podjetja Yaskawa Ristro in Yaskawa Slovenija Dr. Hubert Kosler je že od samih začetkov zapisan vodenju. Že takoj po diplomi na Fakulteti za strojništvo je vodil projekte v ISKRI AVTOMATIKI TOZD AVN, od leta 1988 do leta 1990 je bil pomočnik stečajnega upravitelja in vodja oddelka za inženiring TOZDA AVN v stečaju, od leta 1990 je bil soustanovitelj in direktor podjetja MOTOMAN ROBOTEC Ribnica, ki jo danes poznamo pod imenom YASKAWA SLOVENIJA d. o. o. Svoje vodstvene sposobnosti je razširil in bil leta 1996 pobudnik ustanovitve proizvodnega podjetja YASKAWA RISTRO Ribnica in postal tudi njen direktor. Od leta 2009 je član upravnega odbora YASKAWA EUROPE GmbH, od leta 2010 direktor podjetja YASKAWA CZECH s.r.o. v Pragi. Za svoje delo je prejel številne nagrade: Nacionalno srebrno priznanje 2013 za inovacijo robotske varilne celice s sistemom strojnega vida MotoSENSE, nagrado GZS 2013 za izjemne gospodarske dosežke in bil je regijski finalist Gazela 2012 in Leta 2014 je bil izvoljen za izrednega člana Inženirske akademije Slovenije. NAGRADA ZA ŽIVLJENJSKO DELO Zasl. prof. dr. Jože Vižintin Zasl. prof. dr. Jože Vižintin je že celo življenje zapisan strojništvu. Na Fakulteti za strojništvo je diplomiral leta 1972 in doktoriral leta V rednega profesorja je bil izvoljen leta Na Fakulteti za strojništvo je ustanovil Center za tribologijo in tehnično diagnostiko ter Katedro za tribologijo in sisteme vzdrževanja. Štiri leta je bil prorektor za raziskovalno delo Univerze v Ljubljani in ustanovitelj Inovacijsko razvojnega inštituta Univerze v Ljubljani. Ustanovil je društvo za Tribologijo Slovenije in bil njegov predsednik 28 let. Je soustanovitelj Inženirske Akademije Slovenije, kateri je dvakrat tudi predsedoval. Sedaj opravlja funkcijo glavnega tajnika Akademije. Za svoje delo je dobil več nagrad: Ziosovo priznanje in Zoisovo nagrado za vrhunske znanstvene dosežke na področju strojništva, zlato plaketo Univerze v Ljubljani, nagrado ameriškega združenja inženirjev ASME, Society of Tribologists and Lubrication Engineers-STLE mu je podelilo naziv Fellow. 3. decembra 2015 mu je rektor Univerze v Ljubljani dr. Ivan Svetlik podelil častni naziv - zaslužni profesor Univerze v Ljubljani. Z V E Z A S T R O J N I H I N Ž E N I R J E V S L O V E N I J E W W W. Z V E Z A - Z S I S. S I 36 37

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