<p>This thesis assignment at C-level is focused on calculation models and prediction methods</p><p>whish can be used in the stage we call ”prospecting” of possible windmill locations. The</p><p>location is southeast of Halmstad at the Farm “Stjernarpsgods”. The rapport has two main</p><p>areas directed towards this task. The areas are a study of literature and a description of</p><p>methods used in the project. The “prospect” project description is aimed towards calculations</p><p>of the energy carried by the wind and transformed to electricity by windmills.</p><p>With a relatively simple algorithm of mean wind speed data from the MIUU - model, Cp and</p><p>rotor area from a turbine with 90 m diameter, the calculated production is 6 638 MWh. When</p><p>the same mean wind speed is used in the second type of calculation, Weibull distribution</p><p>(with a calculated A and the form value c set to 2) and the power curve for Vestas V90 taken</p><p>from WindPro, the production was 6 873 MWh. The third alternative uses collected data from</p><p>a local mast at a distance of 18km´s from the site. This data is normalized and used to</p><p>calculate with Weibull distribution the production to 7 443 MWh. Finally a reference</p><p>calculation is done using WindPro and the official SMHI wind data from Halmstad and</p><p>Ringhals. In this case the production was calculated to 5 725 MWh. The difference is a 30</p><p>procent increase from the lowest to the highest production value. Comparing calculations at</p><p>different heights shows that the difference in result is very small at a height of 50 meters, but</p><p>increase with increasing height.</p><p>The Pay-off time was calculated with 3 different energy prediction models. The result was</p><p>Pay-off times off 7, 5 – 9 – 11, 4 years, with the price of electricity at 0, 60 Sek/kWh.</p><p>The environmental consequence analysis which is presented in appendix 1 is mainly focused</p><p>on landscape impact, whish in this case means, that the windmills are clearly visible from</p><p>west and southwest.</p><p>The conclusion is that the value of wind measurements and understanding of sources of error</p><p>is important, and that no investment should be done without proper wind measurements on</p><p>site.</p>

This thesis assignment at C-level is focused on calculation models and prediction methods whish can be used in the stage we call ”prospecting” of possible windmill locations. The location is southeast of Halmstad at the Farm “Stjernarpsgods”. The rapport has two main areas directed towards this task. The areas are a study of literature and a description of methods used in the project. The “prospect” project description is aimed towards calculations of the energy carried by the wind and transformed to electricity by windmills. With a relatively simple algorithm of mean wind speed data from the MIUU - model, Cp and rotor area from a turbine with 90 m diameter, the calculated production is 6 638 MWh. When the same mean wind speed is used in the second type of calculation, Weibull distribution (with a calculated A and the form value c set to 2) and the power curve for Vestas V90 taken from WindPro, the production was 6 873 MWh. The third alternative uses collected data from a local mast at a distance of 18km´s from the site. This data is normalized and used to calculate with Weibull distribution the production to 7 443 MWh. Finally a reference calculation is done using WindPro and the official SMHI wind data from Halmstad and Ringhals. In this case the production was calculated to 5 725 MWh. The difference is a 30 procent increase from the lowest to the highest production value. Comparing calculations at different heights shows that the difference in result is very small at a height of 50 meters, but increase with increasing height. The Pay-off time was calculated with 3 different energy prediction models. The result was Pay-off times off 7, 5 – 9 – 11, 4 years, with the price of electricity at 0, 60 Sek/kWh. The environmental consequence analysis which is presented in appendix 1 is mainly focused on landscape impact, whish in this case means, that the windmills are clearly visible from west and southwest. The conclusion is that the value of wind measurements and understanding of sources of error is important, and that no investment should be done without proper wind measurements on site.

Detaljerad information om vindförhållandena på en site är en nödvändighet för att göra beräkningar av lönsamhet i ett vindkraftsprojekt. Mätningarna behöver vara kontinuerliga och så korrekta som möjligt. Därtill bör de göras under minst ett års tid eftersom vindförhållandena på en plats är säsongsberoende. Under vintertid och framför allt på högre latituder eller altituder, kan mätutrustning påverkas av nedisning. En nedisad anemometer kan ge databortfall eller felaktiga mätningar. Identifiering av felaktiga data är en viktig del av analyseringsarbetet eftersom risken annars är att vindförhållandena på platsen underskattas. Då instrumentet är helt fastfruset kan en enklare analys av data göras genom att titta på standardavvikelsen av vindhastigheten. Svårigheten i detektionen är vid lätt till måttlig nedisning då vindstyrkan, och även standardavvikelsen, kan se normal ut trots att felaktiga värden redovisats. I detta arbete analyseras 1 Hz data från skålkorsanemometer för att söka ett matematiskt sätt att avgöra om lätt till måttlig nedisning påverkat instrumentet under mätperioden. I ett experiment har olika typer av nedisning simulerats på skålkorsanemometrar. Därefter har vindhastighetsfördelningen för en ”nedisad” anemometer kunnat jämföras med fördelningen uppmätt med en anemometer som varit opåverkad under samma mätperiod. I denna jämförelse har visats att trots en differens i medelvind-hastighet på upp till 15 % under mätperioden syns ingen, för detektion av nedisning, användbar skillnad i någon av de statistiska parametrar som jämförts i arbetet. Förutom analys av mätdata från egna experiment har även data från Suorva samt från en höghöjdsmast i Norrland analyserats. För analys av mätdata från masten i Norrland har ett en algoritm utarbetats för automatisk detektion av tidpunkter med instrumentell nedisning. Isdetektionen baseras på antaganden om standardavvikelse av vindhastighet och vindriktning, förändring av vindriktning samt en regression mellan vindhastigheten på två höjder. / Detailed information about the wind conditions on a site is a necessity for calculations of profitability from a wind power project. Hence the continuity and the correctitude of the measurements are crucial when making the site evaluations. Due to the season dependence of the wind conditions the measurements also needs to be done for at least a whole year. During wintertime and particularly on higher altitudes and/or latitudes the instruments may be affected by icing. An iced up anemometer often underestimates the wind speed and severe icing can lead to instrument breakage and loss of data. Identification of inaccurate measurements is of great importance in the analysis of the site’s energy potential. The difficulty in detecting light to moderate icing lies in that the wind speed and the standard deviation of the wind may seem normal, although the anemometer is underestimating the wind speed due to icing. In this thesis 1 Hz data from cup anemometers are analysed in search for a mathematical way to determine whether the instrument has been affected by icing during the measurement. An experiment has been performed simulating different types of icing on anemometers. The wind velocity distribution of an “iced up” anemometer has been compared to the wind velocity distribution of an unaffected anemometer for the same measuring period. Also the turbulence intensity and the change of mean wind velocity between observations have been evaluated. The comparison of these statistical variables between the instruments has showed that none of them are applicable for detection of icing. In addition to analysing data from the experiment a pre-study on the subject has been made analysing measurements with possible icing from the Suorva valley. Also, the results from the experiment have been compared to results from a conventional measuring mast placed in the northern part of Sweden. For the analysis of the mast data an algorithm for detection of icing during measurements has been implemented. This automatic detection of icing is based on assumptions about the standard deviation of wind speed, the standard deviation of the wind direction, the change of wind direction and regression between wind velocities of two heights.

Purpose – The purpose of this thesis was to facilitate the search for echoes caused by fixed objects, so called fixed echoes, when using SODAR-technique for wind measurements. Furthermore, it was investigated how fixed echoes in measurements can change based on different conditions such as: the angle of the sound beam towards the object causing the echo, the output frequency of the instrument, the air temperature and relative humidity. Method – Data was recorded on a test site in southern Sweden during February - April 2017 using two different SODAR-instruments, AQ500 and AQ510, manufactured by AQSystem. Experiments were conducted by installing the instruments at different distances and in different angles next to a met mast. The data recorded was examined for fixed echoes both by using Excel and manually and compared for correlation with the parameters mentioned. A software that uses the r-squared value for a power function adapted to the collected data was developed to detect fixed echoes. Findings – The result of the study showed that the angle of the SODAR-instrument sound beam direction compared to the met mast has a relatively high impact on the number of fixed echoes that can be easily detected. When a sound beam is aimed directly at the fixed object the echoes increased significantly compared to when the sound beams were aimed next to the mast. AQ510, that uses a higher measurement frequency than the AQ500, was less susceptible to fixed echoes when doing simultaneous measurements. Both temperature and relative humidity showed low correlation to the number of fixed echoes so the implication was that these atmospherical parameters do not affect the emergence of fixed echoes. The r-squared value for a power function adapted to the wind data turned out to be a good measure for the magnitude of a fixed echo. When the correlation coefficient of the r-squared value and the percentage of wind profiles that contained fixed echoes were calculated the value was 0,995 which is a strong positive correlation. The r-squared value is compared with a threshold value (which depends on the number of wind profiles in the data to be analysed) to determine if a fixed echo is causing disturbance. Another control is also made in the software where the measured wind values are compared with the values from the power function to find minor deviations possibly caused by fixed echoes. Implications – When the result of the thesis is considered it can help the person installing the instruments as well as the developers of the SODAR-instruments. The person installing the system can notice that fixed echoes can be decreased by rotating the instrument. The result showed the developer that by carefully selecting the right frequency the number of fixed echoes can be decreased. If neither the temperature nor the relative humidity has any impact on fixed echoes it shows the developer that the instrument can be used in varying climates. The result of the study can also be of service to wind analysts using SODAR-equipment. The software developed can be used to find fixed echoes in a more efficient way than was previously possible. Limitations – The data recordings took place during a limited period during late winter, early spring in the southern parts of Sweden which means that neither extremely high or low temperatures were measured during the campaign. The thesis is further limited by only using ”multiple axis” SODAR-instruments from AQSystem. Keywords – SODAR, wind measurements, fixed echoes, measurement instrument. / Syfte – Syftet med detta examensarbete var att underlätta sökandet efter ekon från fasta objekt, så kallade "fasta ekon", vid vindmätning med SODAR-teknik. Vidare var syftet att utreda om fasta ekon framträder olika under olika förutsättningar som: mätinstrumentets ljudlobsvinkel mot objektet som ger upphov till eko, mätfrekvens, luftens temperatur och den relativa luftfuktigheten.  Metod – Data samlades in med två olika SODAR-instrument, AQ500 och AQ510, från företaget AQSystem på en testplats i södra Sverige, februari – april 2017. Data samlades in genom att installera instrumenten på olika avstånd, samt roterat åt olika riktningar, från ett stationärt objekt (en ca 100 m hög mast). Denna data genomsöktes sedan, både manuellt och med hjälp av Excel, efter fasta ekon och jämfördes med tidigare nämnda parametrar. En mjukvara som kan användas för att detektera fasta ekon utvecklades. Mjukvaran använder r-kvadratvärdet för en potensfunktion anpassad till insamlade data för att avgöra storleken på ett eventuellt fast eko. Resultat – Studiens resultat visade att SODAR-instrumentets ljudlobsvinkel mot ekoalstrande objekt hade relativt hög påverkan på fasta ekons styrka. När varsin ljudlob på instrumenten riktades direkt mot masten ökade det fasta ekot jämfört mot när ljudloberna var riktade vid sidan av masten. AQ510, som mäter med en högre frekvens än AQ500, påverkades mindre av fasta ekon än vad AQ500 gjorde vid simultana mätningar. Både luftens temperatur och den relativa luftfuktigheten hade svag korrelation med fasta ekons styrka. Därför drogs slutsatsen att just dessa atmosfäriska parametrar ej påverkar hur fasta ekon uppstår. r-kvadratvärdet för en potensfunktion anpassad till vinddata visades vara ett bra mått på magnituden av ett fast eko. När korrelationskoefficienten för r-kvadratvärdet och andelen vindprofiler innehållande fasta ekon i vinddata beräknades antog den värdet 0,995 vilket visar på en stark positiv korrelation. r-kvadratvärdet jämförs med ett tröskelvärde (som beror av antalet vindprofiler i data som analyseras) för att avgöra om ett fast eko orsakar störningar. En kontroll görs även där det de uppmätta vindvärdena jämförs med potensfunktionens värden för att hitta mindre avvikelser som kan ha orsakats av fasta ekon. Implikationer – Om examensarbetets resultat tas i beaktning kan det underlätta för både installatörer och utvecklare av SODAR-instrument. För installatören visar resultatet att fasta ekon kan minskas genom att rotera mätinstrumentet. För utvecklaren visar resultatet att fasta ekon kan minskas genom att välja en lämplig mätfrekvens. Om varken luftens temperatur eller den relativa luftfuktigheten påverkar fasta ekon nämnvärt kan detta visa på att vindmätning med SODAR-instrument är brukbart i varierande klimat. Även analytiker kan ha nytta av examensarbetets resultat i form av den mjukvara som utvecklats. Mjukvaran kan användas för att på ett mer effektivt sätt än tidigare upptäcka fasta ekon. Begränsningar – Datainsamlingen genomfördes under en begränsad period under sen vinter till tidig vår i södra Sverige. Därför har varken exceptionellt låga- eller höga temperaturer mätts upp. Examensarbetet begränsas ytterligare av att endast mätinstrument från företaget AQSystem av typen "multiple axis" har använts. Nyckelord – SODAR, vindmätning, fasta ekon, mätinstrument. / <p>Presentationen har redan skett.</p>