Konvencionalni analitički modeli za procjenu proizvodnje električne energije redovito se koriste pri planiranju i projektiranju fotonaponskih elektrana, a metode procjene se temelje na matematičkim izračunima geometrije Sunčevog zračenja na bilo kojem mjestu na Zemlji, te snage izračunate iz višegodišnjih prosječnih vrijednosti i njihovih teorijskih odnosa. Problem procjene je da nije optimirana za određeno podneblje i nije potvrđena prema stvarnim rezultatima mjerenja. Općenito uobičajeni izračuni mogu dati relativno loše rezultate koji se pojavljuju na konkretnim mjestima instalacije fotonaponskog panela, a prosječno odstupanje je i do 10 %. Cilj ovog istraživanja je bio analizarati rad fotonaponskog panela u realnom okruženju i različitim režimima rada (fiksna instalacija i usmjeravanje) sa ciljem usporedbe prema predviđanjima konvencionalnih modela i stvaranjem poboljšanog modela. Istraživanje je napravljeno korištenjem podataka o uvjetima i rezultatima rada eksperimentalnog sustava za fotonaponsko karakteriziranje i komercijalne fotonaponske elektrane. Prema rezultatima mjerenja rada sustava za fotonaponsko karakteriziranje izrađen je detaljan analitički model za određivanje maksimalne proizvodene električne energije, koji je korišten za obradu svih mjerenih podataka za cijeli vremenski period. Za komercijalnu fotonaponsku elektranu napravljen je analitički model za procjenu proizvodnje energije. Temeljem usporedbe i analize konvencionalnog modela i rezultata mjerenja kreiran je unaprijeđeni model koji daje bolju točnost predviđanja proizvodnje energije. Unaprijeđeni model je provjeren primjenom na skup mjerenih podataka za godinu koja nije korištena za njegovo kreiranje.
The conventional analytical models are used for prediction of electrical energy production from photovoltaic plants in phases of planning and designing. In order to be able to model such photovoltaic plant it is necessary to access certain input data for planned location. Considering that no data bases are available for purpose of photovoltaic plant modeling, these input data must be provided from measured data bases for some other similar purposes. The most common provided similar data bases are hydrological data bases, although these data bases are rather rough and not exact enough for photovoltaic modeling. Additional problem refers to need for tilted surface irradiation modeling, considering that hydrological measured data are only for horizontal surfaces. Also, these models do not include all of the influences from surroundings, but only the dominant ones. In some cases influences that are often not dominant can become dominant for electrical energy production trough photovoltaic plant. The conventional modeling approach do not include U-I characteristic reconstruction for photovoltaic panels, but rather can calculate electric power at panel terminals from physical parameters of surroundings. Certain conventional models consist of some defects in modeling assumptions. By increasing the shift of observed year from average yearly values, modeled results become more uncertain. The main problem is linearization of equipment characteristics for photovoltaic plant. Shit of observed year from average values can significantly change empirical parameters. These models also have bad assessment of hourly temperature values for surroundings and for PN junction in photovoltaic panels. Increase of result inaccuracy can be noticed by increasing azimuth and slope of photovoltaic panels. Two theses are assumed in this research. The first thesis consists of assumption that corrections of conventional approach to photovoltaic modeling can be introduced by analyzing electrical energy production results for measured and modeled values. The second thesis is assumption that increase of accuracy on hourly basis will insure more accurate results on weekly, monthly and yearly time period. The electrical substitute model of photovoltaic panel is developed in order to perform the measurements of electrical energy production for prototype measurement station. From measured values of three electrical operating points the operating point of maximum power (MPP) is calculated for default conditions. Developed electrical substitute model consists of certain simplifications which are possible to introduce due to measurement procedures of prototype measurement station. Photovoltaic model is modeled by calculating the electrical energy production power from sky mapping results. From these results assessment and comparison of various modes of operation can be performed for future photovoltaic plant. The electrical substitute model can be used reversely to calculate the temperature of PN junction in photovoltaic panel from measured values. The influence on open-circuit voltage and dark current are taken into consideration. Irradiation on horizontal surface is measured directly on location, while the temperature is not measured and needs to be modeled. The improvement of conventional approach to modeling photovoltaic panels and plants is performed on measured results for real photovoltaic plant. Measured results from that plant extend through two years time period while connected to electrical distributional grid. The measured values also consist of nonelectrical parameters, horizontal irradiation and temperature on specified location of plant. Therefore, assessment of electrical energy production is enabled with usage of conventional analytical model in order to be able to compare them to measured results. Observed single year periods significantly deviates from multi-year average values for specified location. From selection of three different derivate models selection is performed and the most accurate model is selected for analysis. On that model improvements are introduced by comparing modeled and measured results for electrical energy production. Liu-Jordan-Klein model is used for translating irradiation from horizontal to tilted surface. Virtual Sun movement around the Earth is taken into consideration by introducing influence of declination and imperfect orbit. Modeling of global irradiation on tilted surface can be conducted using the estimated irradiation angle of incidence on horizontal or tilted surface on specific location on Earth. Calculation of irradiation value is conducted including corrections and irradiation component distribution while passing trough atmosphere. In atmosphere irradiation will dim and reflect which must be taken into consideration in assessment of irradiation on any tilted surface on Earth. Contributions of each component are implemented trough empirical relations and can increase deviations of modeled and measured results for electrical energy production of photovoltaic plant. Modeling of equipment characteristics is defined by photovoltaic panel catalogue data provided by manufacturer. However, these data are not exact for all working conditions of photovoltaic panels during one year period. For example, influence of irradiation on electrical energy production power is interpreted as linear characteristic and does not consider any nonlinearity. Influence of temperature of PN junction of photovoltaic panel is also implemented as linear function and is estimated from ambient temperature. Working conditions of photovoltaic panels are changing accordingly to ambient conditions, and respectively linear catalog data are also changed. The improved model is also taking into consideration these changes of ambient conditions changes. Improvements of conventional analytical model are made from analysis conclusions of modeled and measured electrical energy production results of photovoltaic plant. The modeled results are provided from hydrological measured input data. Irradiation on horizontal surface is translated on specified tilted surface using Liu-Jordan-Klein model. Electrical energy production power is estimated using that modeled irradiation result from photovoltaic plant equipment characteristics. Cumulative energy modeled in this way can be compared with measured results of photovoltaic plant electrical energy production. By concluding the characteristic relations between modeled and measured values some corrections for conventional analytical model are suggested. The improved model with recommended corrections electrical energy production results are calculated using the same input data. The corrections are acceptable if accuracy of modeled results is increasing toward measured results. By using iterative procedure the most accurate model is pursued. Finally, implemented corrections are provided in three stages. In first stage characteristic time periods of year are presented, symmetrically placed around each equinox and solstice. Duration of these time periods is 90 days. In second stage improved working conditions equipment characteristics are introduced, also taking into consideration characteristic time periods. Therefore, the linear catalogue characteristics of equipment are considerably improved. The third stage is referred to implementation of Liu-Jordan- Klein model corrections specifically for observed location of photovoltaic plant. These interventions are mainly referring to transparency factor and anisotropic coefficient, also defined with taking into consideration characteristic time periods. Verification of the improved model is presented on new set of measured data for new calendar year period which did not participate in improvements of conventional analytical model. The results of improved model were also more accurate in verification time period than results of original conventional analytical model. It is estimated that improved model, developed in this research, is relevant for years in time period from 2009. until 2014. Conclusion of this research is that comprehensive analyses were conducted on measured electrical energy production results, and also all important defects in conventional modeling approach. Implemented improvements are based on measured electrical energy production results for real photovoltaic plant, and therefore result in more accurate modeling than conventional approach. In further research some improvements are proposed for measuring and analysis of photovoltaic systems.