URUGUAY SOLAR AND WIND RESOURCE ASSESSMENT

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2 URUGUAY SOLAR AND WIND RESOURCE ASSESSMENT CASE STUDY ON RESOURCE ASSESSMENT AND THE EVALUATION OF RENEWABLE ENERGY POTENTIALS SECRETARY OF ENERGY. MINISTRY OF INDUSTRY, ENERGY AND MINING OF URUGUAY In 2005 a strong paradigm shift occurred in Uruguay in relation to energy. It shifted from being an issue that market response ould provide the anser, to an issue identified as being strategic and therefore subject to state planning. In 2008 the Executive Branch approved the Energy Policy ith a long-term vie of complementing both the technical and economic dimensions hilst maintaining a perspective on the geopolitical, environmental, social and ethical vision of Uruguay. The Energy Policy became a state policy in 2010 hen it as agreed by all the political parties represented in the Uruguayan Congress. It is based on four strategic areas that address: the institutional aspects; the supply of energy analysis; the demand side analysis; and the social aspects; it also sets specific targets for the short, medium and long term. The strategic area for energy supply sets a strong commitment for the incorporation of domestic energy sources, and particularly non-conventional reneable energy. In this context, Uruguay is in the process of developing specific actions that achieve the integration of ind poer, biomass and solar energy (designed to complement the use historically of hydraulic sources).by 2015 at least 50% of the energy ill be supplied from reneable sources and the share of reneables in the electricity generation mix ill exceed 90% ith at least 25% coming from nonconventional reneable sources. In light of these targets, Uruguay has approved a technical regulatory frameork aimed at ensuring a comprehensive integration of ind energy into the national energy mix (as far as is technically possible), and a policy frameork for Solar Thermal Energy. It has begun orking on measures to incorporate electrical poer through the use of photo-voltaic (PV) technology. SOLAR RESOURCE SURVEY IN URUGUAY The momentum gained by accessing the reneable energy sources in Uruguay has highlighted the need for increased knoledge about the solar resource available throughout the country. Quality information about the incident solar radiation is a key input in designing any equipment for the conversion of solar energy into useful energy (either electric or thermal). Moreover, in hat is essentially an agricultural country, a detailed knoledge of the solar resource is also useful for estimating crop yields, designing drying devices for vegetable products, or irrigation planning strategies. Figure 1: map of average annual irradiation for Uruguay The Secretary of Energy from the Ministry of Industry, Energy and Mining (DNE-MIEM) recommended the development of the solar programme. The institute in charge of the projects technical implementation as the University of the Republic (UDELAR), hile the main financers, DNE-MIEM and the Energy Efficiency Project (Global Environment Facility (GEF) operated by World Bank), covered the approximate project cost of USD Summary of the methodology used for the development of the Uruguay Solar Map The folloing description covers the steps taken to develop the first version of the Uruguay solar map. Four sets of irradiation and numerous series of heliophany (sunshine measurements) nationide ere analysed. To sets of national and to sets of regional irradiation data ere used as a basis for the solar map. The methodology consisted in using the Prescott-Angstrom correlation beteen the average and standard heliophany irradiation. The procedure involves analysing the spatial variation of the correlation coefficients, and then uses those local coefficients to estimate the irradiation from the heliophany. Monthly time series and one annual average map ere issued at a spatial resolution varying beteen 10 km and 30 km. The map provides information on the estimated mean daily radiation for each point of the territory ith a colour code, as ell as the average irradiation isolines.

3 Figure 2: Monthly average irradiation maps The uncertainty in the monthly values varies beteen 14% and 19%, ith the largest relative errors associated ith the inter months (less mean radiation). The mean daily values of global irradiation estimated nationide vary beteen 2.1 kwh/m 2 in June and 6.7 kwh/m 2 in January, ith an annual average of 4.4 kwh/m 2. These results ere compared ith daily averages for five seasons in the region and compared ith measurement points located in Argentina and Brazil. These estimates ere found to be consistent ith the measurements made, and ithin the expected margin of error. In addition, a second validation method involved using the UM-SBR model that enables average daily global irradiation for various points across the country to be estimated from both satellite data and using a physical model. Based on data models generated using the UM- SBR model, for a netork of points ith distances of about 110 km from one another, a solar map as produced using satellite information. The values ere compared ith the direct measurements. A very good concordance as obtained beteen the to solar maps, ithin the margin of error, for both models. IMPACT OF THE PROGRAMME The impacts of the resource survey programme can be divided into to levels, direct and indirect impacts: Amongst the direct impacts included are: Information ith regard to Uruguay s solar resource and its distribution both temporally and spatially is no available for use. Confirmation that Uruguay has an available solar resource that can be labelled as good or very good ithregards to international standards. This enables the government to develop measures for promoting the use and the commercial exploitation of this resource. The decision to implement the task using local technical resources has led to the building of the local human capacity tasked to conduct the solar survey. In the Solar Thermal Energy sector: The development of a regulatory frameork for the use of solar thermal energy to supply hot ater and

4 .evind.es maintain the temperature of simming pools (La No. 18,585 and Decree 451/2011, establishing the mandatory inclusion in ne developments ith intensive consumption sectors of domestic hot ater). The development of measures aimed at promoting the integration of solar thermal technology in the residential sector; the Solar Plan as launched in March This plan allos people in the residential sector to access financing for up to five years for the acquisition of solar panels, paying for the loan ith the savings made from their electricity bills after installing this technology. Measures to promote local manufacturing of solar panels. In the Solar PV Sector: Since mid-2010, micro generation activities can be connected to the electricity grid and the authorities are seeking to encourage the concept of a Prosumer, as in one ho is both a producer and a consumer. The adoption of measures to promote the incorporation of PV Solar Energy into the National Grid. A competitive process as announced in October 2012 to initially incorporate up to 36 MW capacity generated ith solar poer; as a reference the mean annual poer demand of Uruguay is 1050 MW. WIND RESOURCE SURVEY IN URUGUAY Since the late tentieth century the national academy had been testing and assessing ind resource models, and sharing the results. The measurement campaigns supporting those assessments ere performed in accordance ith best practices, but did not guarantee the compliance ith

5 .evind.es the country s regulatory requirements that ere in a sufficiently advanced stage. In 2006, Uruguay held the first tender to incorporate reneable energy sources (ind, biomass and small hydropoer plants (SHP)) into the national grid. The results ere imbalanced; being very successful in terms of biomass offers, but no bids ere received for solar heating and there as a notable absence of orld-class players for ind energy. The analysis of the results shoed the need for ind measurements developed under international standards. In 2007, folloing an assessment of potentially exploitable energy resources, DNE-MIEM decided to provide Uruguay ith a systematic survey of all natural energy resources. For ind energy, the state electricity company (UTE) and the UDELAR ere identified as strategic partners, primarily because of the existing skills in the University s School of Engineering. The Wind Map Project of Uruguay as funded by UNDP-GEF (United Nations Development Programme, Global Environment Fund). Folloing conversations ith private actors, DNE-MIEM developed the ind measures certification ith the support of orld class auditing firms. This as a key factor for Uruguay to receive substantial offers from international actors during the energy auctions of 2009, 2010 and The institute in charge of the technical implementation of the ind programme as the UDELAR. The approximate cost as USD 150,000 and the main financers ere UTE, DNE-MIEM, GEF and UNDP. Summary of the methodology used for the development of Uruguay s Wind Map A series of stages ere needed to estimate the ind energy resource, starting ith the visualisation of the Country s ind climate through to the development of a ind map. Weather information and measurements obtained from surface stations here sensors are located on a particular mast at a determined height above the ground should form a "long historical data series. For example, eather data is ordered in periods of one year, and a minimum dataset ould have at least three periods. To capture the ind characteristics of a region and ensure that the database does not have any seasonal bias over this minimal time period, data as collected tri-hourly, so that

6 WIND MAP OF URUGUAY in any 24 hour period, 6 measurements ere taken. This data as then used to build the ind map of Uruguay. The value of the ind map is in part don to its data quality and completeness, meaning that the time series cannot have blanks. As the ind map is deduced from eather information, it must be of a quality that ensures both the accuracy and a lo level of uncertainty in the atlas values. This means that time series must be continuous, simultaneous and mutually consistent. Also, it must be ensured that the database is consistent ith the physics that determines the climate of inds in the area studied. To achieve these characteristics, the first step is to conduct a quality analysis of the measured time series. This is possible by using statistical descriptors and multivariate statistical techniques. MULTIVARIATE ANALYSIS OF THE MEASUREMENTS The ind climate in Uruguay is determined by a number of atmospheric states and the occurrences of different factors or meteorological forcings. These meteorological factors can be sorted according to a geometric and a temporal scale. The scaling factors are called synoptic factors, hich have spatial scales in the order of hundreds of kilometres (km) and time scales of a fe days (for example a polar front, or succession of cyclonic or anticyclonic systems). Stopovers factors, or meso-scale, geometric scales sho scales in the order of the tens of km and time scales of hours(e.g. a sea breeze). A third category of meteorological factors are the micro scale lengths from hundreds of metres to a km, the most common being beteen the ind and hills, forests or buildings. Depending on the scale of the eather factor for a given situation, a certain correlation is established beteen the components of the ind speed vector registered at the different stations. Uruguay has used the methodology that identifies ind directions in hich the correlation becomes extreme. These vectors are determined from the principal components analysis of the observed correlation matrix (Preisendorfer, 1988; Jackson, 1991) 1. Uruguay as divided into three zones, for each major ind patterns ere identified and corresponded to the observations that are made at the associated eather stations. WEATHER STATIONS UTILISED A monitoring netork able to cover the different eather patterns found in Uruguay as established to collect the 1 Preisendorfer R.W. (1988), Principal component analysis in meteorology and oceanography, Elsevier, Amsterdam, pp. 436

7 necessary information to feed and verify the model used for the ind potential evaluation. For the construction of the ind map, a total of 27 measurement stations ere used: Nineteen ere installed by the state poer company UTE Six ere maintained by the Ministry of Defence (National Service of Meteorology and Oceanography, Hydrography and Meteorology of the Navy, SOHMA) Three ere installed by the School of Engineering of the University of the Republic. DESCRIPTION OF THE NUMERICAL MODEL The ind map in Uruguay as developed using a conservation of mass numerical model, hich solves the micro-scale forecast flo, having a scale from hundreds of metres to a fe km and using ind-generated measurements series from eather stations. This alloed the model to generate a time series of ind speed in areas here there as no previous meteorological records. The model follos the methodology proposed by Sherman, , hich adjusts the ind velocity field using as the orking equation that of the conservation of mass. Essentially, the numerical model uses interpolation to determine the volume of ork as an enclosure beteen the floor and a varying height above the ground that could be the height of the boundary layer or the height of the mixture layer. The program algorithm is based on the Finite Element Method, hich allos easy determination of boundary conditions and complex topography.the initial field speed is determined using a relation that eights the instantaneous ind records inversely proportional to the distance. The model inputs the time series of measurements from each station, adjusted to a common height and roughness of ground in all directions. From these data, the model extrapolates in height the series at each station using information of the surface roughness by the logarithmic la to approximately 120 meters. The roughness of the stations for each direction is entered as an input to the model to perform the vertical extrapolation. In this approach it as assumed that the atmosphere is kept in the neutral state. The information on the topography of Uruguay as obtained from the database: SRTM data V1, 2004, International Centre for Tropical Agriculture (CIAT). In this database are available values of terrain elevations on a grid ith a pitch of 90 m. WIND PRODUCTION TOOL In November 2011, the National Energy Authority made available a tool that calculates the energy delivered by a ind turbine in Uruguay, based on the poer curve of a ind turbine and the ind resource in a particular area. Although there are some turbine curves provided ith the tool, it is also possible for users to input poer curves of their on. Furthermore, the tool provides information of the ind resource in the country obtained from the ind map, so the estimates of energy that are delivered are for specific sites in Uruguay. This tool is intended to provide guidance on the potential value of ind poer generation in Uruguay and does not pretend to perform an adjusted calculation for a specific situation. In the case of specific projects, it is highly advisable to seek the advice of experienced staff to evaluate the resource as ell as other aspects of the installation. The folloing link provides access to the described tool as ell as the instructions..energiaeolica.gub.uy/index.php?page=herramientaproduccion-eolica IMPACT OF THE PROGRAMME The impacts of the ind resource programme survey can be divided into to levels; direct and indirect: The direct impacts that require a mention are: From the processed information it is possible to obtain today information about the average ind regime at 15 m, 30 m, 50 m and 90 m high. The analysis of this information demonstrates that Uruguay presents conditions far superior to those previously inferred 3. The international certification provided ith the measured data and the processed information, adds security and assurance to companies hen they decide to invest and take commercial decisions. A reduction in risk for the institutions that finance project development. Uruguay has outstanding ind resource availability and can make an environmentally and socially sustainable utilisation of this reneable resource, but also produce energy under economically competitive conditions. It should be noted that the incorporation of ind energy in Uruguay is already pushing don supply costs. The indirect impacts that are examples are as follos: The development of local labour resources and human capacity associated ith the task of surveying the natural resources. The government target to incorporate ind energy in the national electricity mix in the short term as increased to a range of 25% to 30% ind energy in the electrical grid by 2015.The installation targets have progressed from 300 MW in 2008 to 500 MW in 2010 and reaching MW in This current progression of ind energy in the electricity mix as not foreseeable just five years ago. The increase in the number of high quality, competitive bids received folloing the publication of the Wind Map of Uruguay. 2 Sherman, C.A., (1978).,A mass-consistent Model for Wind Fields over Complex Terrain, J. Appl. Meteor., Vol. 17, pp energiaeolica.gub.uy

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