Preprint from the Conference “Photovoltaics in Europe: From Photovoltaic Technology to Energy Solutions", 7.-11.10.2002, Rome, Italy
GIS-BASED INVENTORY OF THE POTENTIAL PHOTOVOLTAIC OUTPUT IN CENTRAL AND EASTERN EUROPE 1
Marcel Šúri1,2, Ewan D. Dunlop1, Arwyn R. Jones1 European Commission Joint Research Centre, Institute for Environment and Sustainability, Italy 2 Institute of Geography, Slovak Academy of Sciences, Slovakia
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ABSTRACT: The paper presents quantification of global irradiation and assessment of electricity production potential of photovoltaic (PV) systems in urbanised areas of 10 EU Candidate Countries. The maps of monthly and annual means of global irradiation are calculated from clear-sky radiation and clear-sky index from a solar radiation model and other tools integrated within a geographical information system (GIS). The installed south-facing PV systems inclined at angles of 0, 15, 25 and 40° are considered in the calculation of potential PV electricity production. The potential PV output is overlaid by the CORINE Land Cover data – class “residential areas”. The total annual electricity generation potential is calculated, based on the assumption of the theoretical installation of one 1.5 kWp roof-installed PV system per 1 km2 of the residential area. The maps are presented on a level of administrative regions. Keywords: solar radiation, modelling, national programs, small grid-connected PV systems 1 INTRODUCTION In many countries there is a false belief that photovoltaic solar electricity can not make a significant contribution to our energy needs. This impression cannot be dispelled by hand waving arguments but by solid well-reasoned facts and calculations. This paper approaches the question "how much solar electricity can we really have" by calculating from existing data, experience and knowledge the potential solar resource for a rational development of solar electricity generation. For a given PV configuration the optimisation procedure aims to maximise energy yield over a planned period. Finding the optimum angle of the inclined solar panels is one of the steps in the design procedure. The input radiation is generally the weakest parameter especially in mountainous regions or in areas not satisfactorily covered by radiation measurements. The essential input needed for PV assessment is the annual mean of daily totals of global irradiation on the panel surface. Long-term measurements are available only for a limited set of meteorological stations. To obtain the irradiation values for larger regions, either the data from the closest station are used or spatially distributed data are computed using interpolation techniques, supplemented by satellite data or solar radiation models. At present for Europe, the spatially distributed solar radiation database is available at a continental level, computed within European Solar Radiation Atlas (ESRA) [1]. These data have a grid resolution of approximately 10x10 km. For regional studies, more spatial detail is needed as the solar radiation is significantly influenced by terrain effects of slope angle, aspect and topographic shadowing. Solar radiation models integrated within geographical information systems (GIS) provide a cost-efficient means for understanding the spatial and temporal variation of radiation [2]. A GIS is designed to manage, process, analyse and visualise georeferenced data. The objective of this work is to assess the potential electricity output of grid-connected roof photovoltaic systems in residential areas of 10 European Union Candidate Countries (Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia). Four alternatives are calculated – assuming the solar panels at inclination angles of 0, 15, 25 and 40°.
The PV energy yield estimation is based on a spatially distributed global irradiation database computed using solar radiation model and other GIS tools. 2 DATA AND METHODS The input raster data with a cell resolution of 1 km2 were integrated in a GIS project. The elevation data were derived from the USGS GTOPO30 digital elevation model. The latitude raster map was interpolated from distributed points using the regularised spline with tension [3]. The residential areas were selected from CORINE Land Cover database with a raster resolution of 250x250m. The administrative units were taken from the GISCO database (version ARNEV7) [4]. 2.1 Estimation of global irradiation Firstly, the estimation of clear-sky (potential) global irradiation on a horizontal plane was calculated. The real global irradiation on a horizontal plane is then estimated by multiplying the clear-sky values with a clear-sky index. These values are then used in the model for computation of global irradiation on inclined panels. The computation was done using the solar radiation model r.sun that has been implemented in the GRASS GIS [5]. The equations in the model were based on the results of ESRA [1]. The model can estimate beam, diffuse and reflected components of the clear-sky global irradiance and irradiation on a horizontal and inclined surfaces. The total daily irradiation values [kWh.m-2] were computed by the integration of the irradiance values [W.m-2] calculated for 15-minute intervals and summarised between the sunrise and sunset. The model accounts for sky obstruction by shadowing effects of the local terrain features. A brief overview of the irradiance calculation scheme of the model is provided below, more details can be consulted in [5]. Step 1 Clear-sky global irradiation on a horizontal plane The normal beam (direct) solar irradiance Bc0 is estimated from the extraterrestrial irradiance G0 = I0 ε that is modified by the atmospheric beam attenuation under cloudless sky [6]: Bc0 = G0 exp {-0.8662 TLK m δR(m)} (1)
Preprint from the Conference “Photovoltaics in Europe: From Photovoltaic Technology to Energy Solutions", 7.-11.10.2002, Rome, Italy
where ε is the solar eccentricity, I0 solar constant (1367 W.m-2), TLK is the air mass 2 Linke turbidity factor, m is the relative optical air mass and δR(m) is the Rayleigh optical thickness at air mass m. The beam irradiance on a horizontal plane Bch is calculated as: Bch = Bc0 sin h0 (2) where h0 is the solar altitude. The estimate of the diffuse clear-sky irradiance on a horizontal plane (Dch) is made as a product of the normal extraterrestrial irradiance G0, a diffuse transmission function Tn dependent on the Linke turbidity factor TLK, and a diffuse solar elevation function Fd dependent on the solar altitude h0 [6]: Dch = G0 Tn(TLK) Fd(h0). (3) The monthly means of the Linke turbidity factor TLK for 317 sites over the study area were extracted from the SoDa web database [7] and normalised to the sea elevation. The spatially distributed layers of TLKn were interpolated using the regularised spline with tension [3] and corrected against the sea elevation. The clear-sky global irradiance on a horizontal plane Gch [W.m-2] is given by the sum of its beam Bch and diffuse Dch components. By the integration of the 15minute irradiances for a representative day of each month [1, p. 108] the 12 data layers, each representing the monthly means of daily sums of horizontal global irradiation [kWh.m-2] were computed together with the 13th layer representing the annual mean of daily sums. Step 2 Global irradiation on a horizontal plane The global irradiation for overcast conditions was calculated using the clear-sky index kc and solar irradiation database published in ESRA [1]. For the study area the data from 182 meteorological station were available, comprising geographical position and monthly means of global (Ghs), beam (Bhs) and diffuse (Dhs) irradiation on a horizontal surface. The clear-sky irradiation values Ghc, Bhc and Dhc computed in the step 1 were added to this database and for each meteorological station the clear-sky index was computed: kc = Ghs/Ghc (4) The clear-sky index correlates with elevation, mostly in summer and winter, therefore to obtain spatially distributed data a multivariate spatial interpolation was used to account for changes in vertical dimension [8]. To obtain the accurate results a crossvalidation procedure was applied separately for each of the 12 monthly point data sets of kc. The monthly means of the daily sums of global irradiation for horizontal surface was calculated using the formula: Gh = kc Ghc (5) This approach enables to estimate the solar resource at high spatial detail, considering the shadowing effect of terrain features that can significantly modify its spatial pattern in a mountainous landscape. Step 3 Global irradiation on an inclined plane To compute global irradiation on inclined planes Gi at real (overcast) atmospheric conditions the beam and diffuse components for conditions of mean monthly cloudiness were estimated. The reason is that the ratio of diffuse component to global radiation is different for clear-sky and overcast conditions.
From the climatic database [1] the ratio Dhs/Ghs was calculated and raster maps were interpolated using multivariate spatial interpolation in the same way as it was done for the clear-sky index kc. The raster maps of diffuse and beam components of horizontal global irradiation for overcast conditions were computed: Dh = Gh Dhs/Ghs (6) Bh = Gh – Dh Global irradiance on an inclined panel Gi is a sum of the beam Bi, diffuse Di and reflected Ri components. The beam irradiance on a inclined panel Bi is calculated as: (7) Bi = Bh sin h0 / sin δexp where δexp is the solar incidence angle. The model for estimating the diffuse irradiance/irradiation on an inclined panel (Di) by Muneer [9] distinguishes between sunlit, potentially sunlit and shaded surfaces: a) for surfaces in shade (δexp < 0 and h0 >= 0): (8) Di = Dh F(γN) b) for sunlit surfaces and non-overcast sky (h0 in radians): Di = Dh F(γN) (1 - Kb) + Kb sin δexp / sin h0 if h0 >= 0.1 rad Di = Dh F(γN) (1-Kb) + Kb sin γN cos ALN/(0.1-0.008 h0) if h0 < 0.1 rad where ALN is an angle between the vertical plane containing the normal to the surface and the plane passing through the centre of the solar disc. In this context the Kb is a measure of the amount of beam radiation available and F(γN) is a function accounting for the diffuse sky irradiance distribution. The diffuse ground reflected irradiance received on an inclined surface (Ri) is proportional to the global horizontal irradiance Gh, to the mean ground albedo ρg (considered as a constant 0.15) and a fraction of the ground viewed by an inclined panel rg(γN): (9) Ri = ρg Gh rg(γN). Similarly as in the step 1, the irardiation values for inclined panels were computed by the integration of the 15-minute irradiances calculated between sunrise and sunset for a representative day of each month. The resulting solar database consists of raster maps representing 12 monthly means and 1 annual mean of daily sums of clear-sky global irradiation, Linke turbidity, clear-sky index and all components of overcast irradiation for horizontal panels, as well as those inclined at angles of 15, 25, and 40°. 2.2 Calculation of PV potential production The calculation is intended for the preliminary design by providing an order of magnitude estimates of the PV systems production. The essential input is the annual mean of daily sums of global irradiation available to solar panels. With the aim to maximise the annual electricity production the optimum panel slope angle at south orientation is determined from the maximum annual global solar irradiation computed at 0, 15, 25 and 40°. To compute the annual total electricity output from the PV system E [kWh] the following equation can be used [1]: E = 365 Pk ηp Gi,h (10) where Pk (in kW) is the peak power installed (1.5 kW in our case), ηp is the system efficiency (typical value 0.75) and Gi,h is the annual mean of daily global irradiation on the horizontal or inclined solar panel facing to the south.
Preprint from the Conference “Photovoltaics in Europe: From Photovoltaic Technology to Energy Solutions", 7.-11.10.2002, Rome, Italy
The results of this stage consist of maps of the annual average potential PV production in the targeted EU Candidate Countries [kWh] and total sum of electricity production, considering the defined array geometries of the grid-connected household installations. The PV output were overlain with the residential areas as mapped by CORINE Land Cover database [10] as discontinuous urban fabric (class 112) to extract the values relating only to the residential areas. In the final step, a theoretically homogeneous dispersion of 1 PV system per 1 km2 of residential area was assumed. The average and total annual PV production was calculated for administrative regions.
the more northerly countries these small systems provide an excess of 1 MWh per year.
3 RESULTS The maps reveal significant regional differences in available global irradiation, determined by latitude, terrain and local climatic conditions. When compared to the panels in a horizontal position, the annual average production of 1 PV system increases about 10, 14 and 15%, respectively for inclined panels at angles of 15, 25 and 40°, respectively (Fig. 1 and 2). Because of latitude, the change of inclination angle from 25 to 40° does not bring any significant increase of PV output in parts of Bulgaria, Romania, Slovenia and Czech Republic (Fig. 3). On the other hand in many regions (in Romania, Slovakia, Poland and in Baltic states) the panels inclined at angles steeper then 25° contribute to the PV yield by increase up to 40 kWh (up to 3.2%).
Figure 2: Average annual PV output of a 1.5 kWp system with panels inclined at angle of 25° [kWh]
Figure 1: Average annual PV output of a 1.5 kWp system with horizontal panels [kWh] It is noticeable from these maps that although the results for Bulgaria, Romania, Hungary, Slovenia, Slovakia and parts of the Czech Republic are more favourable, even in
Figure 3: Difference in average annual output of a 1.5 kWp PV system for an increase of panels inclination from 25 to 40° [kWh]
Preprint from the Conference “Photovoltaics in Europe: From Photovoltaic Technology to Energy Solutions", 7.-11.10.2002, Rome, Italy
The annual total yield calculated for the residential areas in individual administrative regions is presented in (Fig. 4 and 5). The scenario assumes a theoretical assumption of having homogeneously distributed 1.5 kWp PV systems at different inclination angles within the regions with density of one installation per one square kilometre.
systems on top of the bars) Fig. 4 can be used for regional planning as it gives an overview of the potential production pattern within a country that reflects the regional consumption needs as well. The energy yield is not the only factor taken into consideration in the state policy of support to PV installations. The prioritising of the less-favoured areas can help them to overcome social and economic limits and promote their development based on the sustainable energy production. Even given the lowest yield of 1200 kWh per year for the 1.5 kWp configuration (approx. 12 m2), this is still on average greater than 3 kWh per day, easily meeting the needs of a typical 4person house. 4 CONCLUSIONS The calculation of PV production potential is a basic but crucial step for analyses and forecasts of energy demand/supply patterns that take into account technical and also socio-economic data. In the approach described in this paper, the emphasis was placed on the calculation of the solar radiation resource at higher spatial resolution than available in ESRA database [1], based on use of more detailed digital elevation model and GIS. The PV output assessment is drafted to provide estimates for the planning phase. The results are a good basis for the national PV development programs. 5 ACKNOWLEDGEMENT
Figure 4: Total sum of annual PV electricity output for panel inclined at angle of 25° [MWh] The assumption defined above determines the total PV output per region by the solar potential as well as density of urbanized residential area. Therefore the most productive administrative regions are generally those with high population density and favorable climatic conditions (Fig. 4). The summarization on a national level (Fig. 5) gives an overview of the potential PV electricity production provided the installations are dispersed within the country homogeneously. 22 20
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Figure 5: Total annual PV output [GWh] on the country level. The 1.5 kWp systems homogeneously dispersed in residential areas (density 1 PV system/km2) assuming panels at angles 0, 15, 25 and 40° (total number of PV
This work has been carried out under the EC JRC Enlargement Action Programme as project number 52 entitled “Environment and the solar energy resource” in a co-operation with GeoModel s.r.o. 6 REFERENCES [1] K. Scharmer, J., Greif, J., eds., The European Solar Radiation Atlas. Vol. 2 (2000). [2] R. Dubayah, P. M. Rich, Int. Journal of Geographical Information Systems 9 (1995) 405. [3] H. Mitášová, L. Mitáš, Mathematical Geology 25 (1993) 641. [4] The GISCO (Geographic Information System of the European Commission) Database Manual (2001) [5] J. Hofierka, M. Šúri, Proceedings International GRASS Users Conference, Trento, (2002). [6] C. Rigollier, O. Bauer, L. Wald, Solar Energy 68 (2000) 33. [7] L. Wald, European Geophysical Society Meeting, XXV General Assembly, Nice, France (2000). [8] J. Hofierka, J. Parajka, H. Mitasova, L. Mitas, Transactions in GIS 6 (2002) 135. [9] T. Muneer, Building Services Engineering Research and Technology 11 (1990) 153. [10] Y. Heymann, Ch. Steenmans, G. Croisille, S. Bossard, CORINE Land Cover Technical Guide (1994).
