Wyniki 1-4 spośród 4 dla zapytania: authorDesc:"Igor PETROVIĆ"

Comparison of PV plant energy generation prediction tools with measured data

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The object of this research is to compare three of the most popular conventional analytical models used for estimation of electrical energy production of photovoltaic panels. From this analysis a single model will be selected with the best characteristics for implementation of modifications and corrections in order to get better energy production prediction results. Monthly and annual production results and errors will be the main criteria for the selection of a single model. Single prediction results of the selected model should be as accurate as possible in the smallest time periods, which are in this case monthly energy prediction results. This should guarantee that annual results are also rather accurate. Streszczenie. W artykule porównano trzy modele analityczne umożliwiające analizę energii elektrycznej wytwarzanej przez panele fotowoltaiczne. Analizuje się miesięczną i roczną produkcję energii na podstawie wybranych okresów czasowych. (Porównanie metod przewidywania produkcji enegii przez panele fotowoltaiczne) Keywords: PV plant, conventional analytical model, electrical energy production. Słowa kluczowe: ogniwa fotowoltaiczne, prognozowanie produkcji energii Introduction Accuracy of conventional analytical models used for estimation of electrical energy production of photovoltaic panels and systems is the main characteristic that determines tool expediency. Conventional analytical models are mathematical methods which use theoretical values and estimated relations between energy production and hydrological conditions in the surroundings of the production system ([1], [2]). These assumptions are made on perennial average values for a specific location. In average cases, error estimation from the modelled values and specific annual production can drop over 10%. The main task of this research is to take results of the conventional analytical model from the actual measured input data for a specific location (solar radiation and[...]

The Comparison of the Measured Clearness Index for Different Locations in the Moderate Continental Climate Region DOI:10.12915/pe.2014.03.027

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The object of this research is to compare clearness index for different locations in same climate region, based on measurements. The clearness index is used in conventional analytical modelling of PV resources. Since these models use average values for every climate and geographical region, these parameters are usually provided from generic data bases available from World Wide Web. New empirical average value for clearness index of the researched region can be calculated from results of this research, and used for better modelling of PV resources. Streszczenie. Celem pracy była analiza przejrzystości powietrza dla różnych lokalizacji ogniw fotowoltaicznych. Badano indeks przejrzystości dla różnych lokalizacji na przykładzie klimatu śródziemnomorskiego - Chorwacji. (Porównanie przejrzystości powietrza dla różnych lokalizacji ogniw fotowoltaicznych). Keywords: PV plant, conventional analytical model, Grimm's algorithm, irradiation measuring system. Słowa kluczowe: ogniwa fotowoltaiczne, przejrzystość powietrza, indeks przejrzystości doi:10.12915/pe.2014.03.27 Introduction When assesing PV system electrical energy production various conventional models are used for modeling light resources available in specified location as in [1]. One of these models, very often used in such assesments, is Liu- Jordan-Klein model which was used in this research. It is mathematical model of Sun virtual movement trough sky ([2]) and light dispersing when passing trough atmosphere ([3]), and calculates irradiation on sloped surface of PV modules. The clearness index is one of many parameters used in this model. In this research the average hourly changes of clearness index is provided for four different microlocations, all placed in one macroclimate region ([4], [5]). Mediterranean continental climate is described by average parameters inside the model such as Homer ([6], [7], [8], [9], [10], [11]), and is valid for locations on which this resear[...]

Sun trajectory modeling for specific location using PV measured data DOI:10.15199/48.2015.11.63

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In order to research the PV module characterization it was necessary to develop the Prototype PV characterization station. Among other possibilities derived from the measured results of Prototype PV characterization station it is also possible to model the Sun trajectory at installation location. Such measured results can be used to model Sun trajectory. Also, the Sun trajectory generated using presented model is verified with conventional analytical model Sun trajectory. Some conclusions for new approach are presented and discussed. Streszczenie. Przy charakteryzacji prototypu stacji fotowoltaicznej zalecane jest modelowanie trajektorioi słońca. Przedstawiono taki model wykonany na podstawie badań eksperymentalnych. Modelowanie trajektorii słońca w określonej lokalizacji na podstawie eksperymentu Keywords: analytical models, power system measurement, photovoltaic cells, Sun trajectory. Słowa kluczowe: modelowanie trajektorii słońca, stacja fotowoltaiczna Introduction When number of PV plants reach certain installed electrical production power it is common for the price of energy to drop. In such cases it is necessary to improve the efficiency of electrical energy production. The simplest way to improve such energy production is upgrading from the fixed PV system to single-axis or dual-axis tracking system, as described in [1, 2, 3]. When using single or dual-axis tracking system it is necessary to know Sun trajectory in order for control system to follow it during the day, as described in [4]. The main goal of this research is to show that measured results provided by prototype PV characterization station, described in detail in [5], can be used to describe Sun trajectory. The prototype PV characterization station is used for collecting the data significant for PV plant electrical energy production. These measured results, gained from prototype PV characterization station, and electrical energy production modeling results, gained[...]

Influence of ECG testing errors on Automatic ECG interpretation DOI:10.15199/48.2016.09.53

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The ECG testing is very common in health diagnose of a patient. Also, in present it is common to apply as many automated technology solutions as possible. Generally, this should insure better quality of gained diagnostic results. On the other hand, complex solutions invoke human error in procedure, which ultimately can provide inaccurate results. The influence of such errors on example of ECG testing is analyzed and compared to normal ECG test in this research, where six scenarios are deliberately forced to provide fault diagnose. Streszczenie. Do analizy sygnałów EKG stosuje się obecnie wiele metod automatyzacji. W artykule analizuje się możliwe błędy w interpretacji sygnałów EKG. Wpływ błędów na interpretację wyniku EKG w metodach automatycznej diagnozy Keywords: ECG, resting cardiograph, electrical measuring, automatic Słowa kluczowe: EKG, automatyczna diagnoza chorób serca.. Introduction Heart is active muscle which supports circulation of blood in the human body. During this activity heart generates certain flow of electrical charge, e.g. the electrical current dependent to state of the heart. Therefore, if one wants to deduct on heart status and quality, some of necessary input information can be measured trough electrical potential which emerges on the human body skin. Electrocardiography is set of measured electrical voltage gained from heart activity, all available in compact device electrocardiograph. The heart electrical activity was first noticed in 1856 by Koelliker and Muller, while the first capillary electrocardiograph record on a human was made in 1877 by Waller, like described in [1]. The first modern type electrocardiograph was constructed in 1903 by Willem Einthoven, like shown in [2]. Indications for conducting ECG procedure are any suspicions of cardiovascular disease, as provided in [3]. One of human body bioelectrical signals is ECG signal, as described in [4]. The ECG testing is actually a simple procedur[...]

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