Wind farms are costly projects and prior to the construction, comprehensive wind resource assessment processes are carried out in order to predict the future energy yield with a reliable accuracy. These estimations are made to constitute a basis for the financial assessment of the project. However, predicting the future always accommodates some uncertainties and sometimes these assessments might overestimate the production. Many different factors might account for a discrepancy between the pre-construction wind resource assessment and the operational production data. This thesis investigates an underperforming wind farm in order to ascertain the reasons of a discrepancy case. To investigate the case, the relevant data and information along with the actual production data of three years are shared with the author. Prior to the construction, a wind resource assessment was carried out by an independent wind consultancy company and the work overestimated the annual energy production (AEP) by 19.1% based on the average production value of available three years. An extensive literature review is performed to identify the possible contributing causes of the discrepancy. The data provided is investigated and a new wind resource assessment is carried out. The underestimation of the wind farm losses are studied extensively as a potential reason of the underperformance. For the AEP estimations, WAsP in WindPro interface and WindSim are employed. The use of WindSim led to about 2-2.5% less AEP estimations compared to the results of WAsP. In order to evaluate the influence of long term correlations on the AEP estimations, the climatology datasets are created using the two different reanalysis datasets (MERRA and CFSR-E) as long term references. WindSim results based on the climatology data obtained using the MERRA and CFSR-E datasets as long term references overestimated the results by 10.9% and 8.2% respectively.

Wind power is seen as one of the most effective means available to combat the twin crises of global climate change and energy security. The annual market growth has established wind power as the leading renewable energy technology. Due to the availability of sparsely populated and flat open terrain, the Yucatán Peninsula located in eastern México is a promising region from the perspective of wind energy development but no comprehensive assessment of wind resource has been previously published. A basic requirement when developing wind power projects is to study the main characteristic parameters of wind in relation to its geographical and temporal distribution. The analysis of diurnal and seasonal wind patterns are an important stage in the move towards commercial exploitation of wind power. The research developed during the PhD has comprehensively assessed the wind behaviour over the Yucatán Peninsula region covering long term patterns at three sites, a spatial study using short term data for nine sites, a vertical profile study on one inland site and an offshore study made on a pier at 6.65km from the North shore. Monthly trends, directional behaviours and frequency distributions were identified and discussed. The characteristics of the wind speed variation reflected their proximity to the coast and whether they were influenced by wind coming predominantly from over the land or predominantly from over the sea. The atmospheric stability over the eastern seas was also analysed to assess thermal effects for different wind directions. Diurnal wind speed variations are shown to be affected in particular by the differing wind conditions associated with fetches over two distinct offshore regions. Seasonal behaviour suggests some departure from the oscillations expected from temperature variation. The offshore wind is thermally driven suggesting largely unstable conditions and the potential development of a shallow Stable Internal Boundary Layer.

Wind resource assessment studies have been conducted in the Israeli side and the Palestinian side before; however, the previous studies were restricted with the political border either Palestinian or Israeli except one of them that was based on measurements dated to 1940-1983 (R. Shabbaneh & A. Hasan, 1997). Moreover, the studies were performed years ago, with simple techniques and based on old data (R. Shabbaneh & A. Hasan, 1997). Hence, the needs for a new study that is based on updated data, and using updated model is highly demanded. This study is intended to perform wind resource assessment in Palestine/Israel; the study has used two stages of assessment, primary one based on reference station data on both sides, Israeli and Palestinian. The second stage of wind resource assessment is based on WindPRO software. The wind resource assessment ends up with identifying sites with higher potential that are situated in four selected sites, North of Palestine/Israel, North of West-bank, Jerusalem, and Eilat, the higher potential was in Eilat area bearing mean wind speed of 9.88m/s at 100 m hub height.Moreover, the study recognized the importance of political situation assessment due to the Israeli-Palestinian conflict. Based on conducted survey, the political situation assessment concluded that international non-governmental organizations seem to be most capable of starting up wind power project in Palestine/Israel. Furthermore, the study concluded that supportive policies from both the Israeli and Palestinian governments are crucial to promote wind power projects in the region.

Impulsionado pela mecânica de leilões de energia, o aproveitamento energético de recursos eólicos no Brasil atravessa um momento de expansão em participação na matriz de energia elétrica nacional. Não obstante, o desempenho da geração dos parques eólicos que estão em operação foi monitorado e apresentou, em média, resultados aquém daquilo que fora confiado ao Sistema Interligado Nacional, revelando que as estimativas de geração projetadas e declaradas por alguns dos projetos vencedores dos processos licitatórios podem ter sido supervalorizadas. Tal cenário provocou a exigência de medidas mais conservadoras para participação nos leilões de energia, como a já vigente adoção do P90 no cálculo da Garantia Física e o aumento da duração da campanha de medição anemométrica, a entrar em rigor a partir de 2017. Sendo o vento uma variável estocástica, existem incertezas intrínsecas à Avaliação de Recursos Eólicos que influenciam no processo de estimação da geração por um parque eólico e que devem, desta forma, ser identificadas, quantificadas e reduzidas, na medida do possível. Nesse sentido, este trabalho estuda a influência da duração da campanha de medição anemométrica na Avaliação de Recursos Eólicos com base na aplicação do método MCP ferramenta imprescindível no processo de caracterização do regime eólico no longo prazo com vistas para aprimorar a exatidão das previsões de geração pela fonte eólica. Para tanto, foram utilizadas quatro bases de dados contendo séries temporais de velocidade e direção do vento referentes a uma região de interesse. Inicialmente, nove diferentes métodos MCP foram testados e comparados, sendo que o método Vertical Slice aplicado com auxílio do software Windographer destacou-se dos demais e mostrou-se mais aderente aos dados utilizados conforme as métricas de Erro Absoluto Médio e Raiz Quadrada do Erro Quadrático Médio. Posteriormente, as bases de dados foram configuradas para simular campanhas de medição anemométricas com durações que variavam de 2 a 6 anos, de modo a avaliar o comportamento da incerteza relativa à caracterização histórica de recursos eólicos e analisar em que medida esta incerteza impacta no cálculo da estimativa de geração de eletricidade por um conjunto de aerogeradores hipoteticamente dispostos naquele local de interesse. Foi possível verificar que, para os dados e casos analisados, à medida que se aumentou a duração da campanha de medição anemométrica, a incerteza da caracterização histórica de recursos eólicos sofreu queda significativa; determinando, por conseguinte, redução da incerteza total que permeia a geração eólica. Ademais, a quantidade de energia estimada para o parque eólico hipotético exemplificado também decresceu, permitindo melhora na acurácia da previsão de geração e beneficiando a confiabilidade da fonte eólica no sistema elétrico brasileiro. / Driven by the energy auctions system, the energetic harnessing of wind resource in Brazil is now going through a phase of expansion in participation in the national electric energy mix. Nevertheless, the performance of power generation of in-operation wind farms was monitored and the results proved to be, on average, below what was initially entrusted to the National Grid System, indicating that the energy production estimations projected by some energy auctions winners could have been overestimated. This scenario has caused the requirements for participating in the energy auctions to be more conservative, with measures such as the adoption of the P90 on the calculation of the physical guarantee and the increase of the wind measurement campaigns time span the latter to be enforced as of 2017. The wind is a stochastic resource, hence there are uncertainties intrinsic to the Wind Resource Assessment that influence a wind farms power generation estimation and that need to be properly identified, quantified and reduced, as far as possible. In this respect, the influence of a wind measurement campaigns time span on the Wind Resource Assessment based on MCP methods an important tool in the process of characterizing the long-term wind regime was studied in order to detect the potential of enhancing the accuracy of wind power generation forecasts. For this purpose, four databases containing time series of wind speed and direction belonging to a target site were used. Firstly, nine different MCP methods were tested and compared, of which the Vertical Slice method implemented on the software Windographer outperformed all the others according to the Mean Absolute Error and Root Mean Square Error metrics. Subsequently, the databases were set to simulate campaigns with time spans varying from 2 to 6 years, in such a way to evaluate the behavior of the uncertainty in the long-term wind speed and to analyze how this uncertainty impacts the calculation of the energy production estimation of an array of wind turbines hypothetically placed on that target site. From the analyzed data and cases, it was verified that, as the wind measurement campaigns time span was increased, the uncertainty in the long-term wind speed was significantly diminished, thereby reducing the overall uncertainty that pervades the wind power harnessing. Furthermore, the energy production estimation of the exemplified hypothetical wind farm also decreased, allowing an improvement on the accuracy of the energy generation prediction and benefiting the reliability of wind power in the Brazilian electric system.

Recently wind resource assessment studies have become an important research tool to identify the possible wind farm locations.  In this thesis work technical analysis was carried out to determine the wind resource potential of two candidate sites in Eritrea with help of suitable software tools. The first site is located along the Red Sea cost which is well known for its wind resource potential, whereas the second site is located in the central highlands of Eritrea with significant wind resource potential. Detailed wind resource assessment, for one year hourly weather data including wind speed and wind direction, was performed for the two candidate sites using MS Excel and MATLAB. The measured wind data at Assab wind site showed that the mean wind speed and power density was 7.54 m/s and 402.57 W/m2 , whereas the mean wind speed and mean power density from Weibull distribution was 7.51 m/s and 423.71 W/m2 respectively at 80m height. Similarly, the measured mean wind speed and mean power density at Dekemahre wind site was obtained to be 5.498 m/s and 141.45 W/m2, whereas the mean wind speed and mean power density from Weibull distribution was 5.4859m/s and 141.057W/m2 respectively. Based on the analysis results Assab wind site classified as wind class-III and Dekemhare as wind class-I.  Wind farm modeling and Annual Energy Production (AEP) estimation was performed for E-82 & E-53 model turbines from Enercon Company with the help of MATLAB and Windpro software. The analysis revealed that Assab wind farm was an ideal site for wind energy production with capacity factor (CF) 53.4% and 55% for E-82 and E-53 turbines respectively. The gross and net AEP for turbine E-82 at Assab wind farm was 469.5 GWh and 446.025 GWh respectively with 95% park efficiency. Similarly, the analysis showed that the CF in Dekemhare site was very low with typical value 14.2% and 15.26% for E-82 and E-53 turbines respectively. The gross and net AEP of that site for model turbine E-53 was 53.5 GWh and 50.825 GWh respectively with 5% wake loss. Finally, a simplified economic analysis was carried out to determine the economic feasibility of possible wind power projects in both sites by assuming investment cost 1600 €/kW for E-82 turbine and 2000 €/kW for E-53 turbine. The total wind farm investment cost was found to be 215.85 and 107.93 Million Euro for E-82 and E-53 model turbines respectively. The levelized cost of energy at Assab and Dekemhare wind farm for E-82 model turbine was 0.0307 €/kWh and 0.5526 €/kWh respectively. The analysis result show that the levelized cost of energy in Dekemhare wind fasrm was much higher than that of Assab wind farm.

Impulsionado pela mecânica de leilões de energia, o aproveitamento energético de recursos eólicos no Brasil atravessa um momento de expansão em participação na matriz de energia elétrica nacional. Não obstante, o desempenho da geração dos parques eólicos que estão em operação foi monitorado e apresentou, em média, resultados aquém daquilo que fora confiado ao Sistema Interligado Nacional, revelando que as estimativas de geração projetadas e declaradas por alguns dos projetos vencedores dos processos licitatórios podem ter sido supervalorizadas. Tal cenário provocou a exigência de medidas mais conservadoras para participação nos leilões de energia, como a já vigente adoção do P90 no cálculo da Garantia Física e o aumento da duração da campanha de medição anemométrica, a entrar em rigor a partir de 2017. Sendo o vento uma variável estocástica, existem incertezas intrínsecas à Avaliação de Recursos Eólicos que influenciam no processo de estimação da geração por um parque eólico e que devem, desta forma, ser identificadas, quantificadas e reduzidas, na medida do possível. Nesse sentido, este trabalho estuda a influência da duração da campanha de medição anemométrica na Avaliação de Recursos Eólicos com base na aplicação do método MCP ferramenta imprescindível no processo de caracterização do regime eólico no longo prazo com vistas para aprimorar a exatidão das previsões de geração pela fonte eólica. Para tanto, foram utilizadas quatro bases de dados contendo séries temporais de velocidade e direção do vento referentes a uma região de interesse. Inicialmente, nove diferentes métodos MCP foram testados e comparados, sendo que o método Vertical Slice aplicado com auxílio do software Windographer destacou-se dos demais e mostrou-se mais aderente aos dados utilizados conforme as métricas de Erro Absoluto Médio e Raiz Quadrada do Erro Quadrático Médio. Posteriormente, as bases de dados foram configuradas para simular campanhas de medição anemométricas com durações que variavam de 2 a 6 anos, de modo a avaliar o comportamento da incerteza relativa à caracterização histórica de recursos eólicos e analisar em que medida esta incerteza impacta no cálculo da estimativa de geração de eletricidade por um conjunto de aerogeradores hipoteticamente dispostos naquele local de interesse. Foi possível verificar que, para os dados e casos analisados, à medida que se aumentou a duração da campanha de medição anemométrica, a incerteza da caracterização histórica de recursos eólicos sofreu queda significativa; determinando, por conseguinte, redução da incerteza total que permeia a geração eólica. Ademais, a quantidade de energia estimada para o parque eólico hipotético exemplificado também decresceu, permitindo melhora na acurácia da previsão de geração e beneficiando a confiabilidade da fonte eólica no sistema elétrico brasileiro. / Driven by the energy auctions system, the energetic harnessing of wind resource in Brazil is now going through a phase of expansion in participation in the national electric energy mix. Nevertheless, the performance of power generation of in-operation wind farms was monitored and the results proved to be, on average, below what was initially entrusted to the National Grid System, indicating that the energy production estimations projected by some energy auctions winners could have been overestimated. This scenario has caused the requirements for participating in the energy auctions to be more conservative, with measures such as the adoption of the P90 on the calculation of the physical guarantee and the increase of the wind measurement campaigns time span the latter to be enforced as of 2017. The wind is a stochastic resource, hence there are uncertainties intrinsic to the Wind Resource Assessment that influence a wind farms power generation estimation and that need to be properly identified, quantified and reduced, as far as possible. In this respect, the influence of a wind measurement campaigns time span on the Wind Resource Assessment based on MCP methods an important tool in the process of characterizing the long-term wind regime was studied in order to detect the potential of enhancing the accuracy of wind power generation forecasts. For this purpose, four databases containing time series of wind speed and direction belonging to a target site were used. Firstly, nine different MCP methods were tested and compared, of which the Vertical Slice method implemented on the software Windographer outperformed all the others according to the Mean Absolute Error and Root Mean Square Error metrics. Subsequently, the databases were set to simulate campaigns with time spans varying from 2 to 6 years, in such a way to evaluate the behavior of the uncertainty in the long-term wind speed and to analyze how this uncertainty impacts the calculation of the energy production estimation of an array of wind turbines hypothetically placed on that target site. From the analyzed data and cases, it was verified that, as the wind measurement campaigns time span was increased, the uncertainty in the long-term wind speed was significantly diminished, thereby reducing the overall uncertainty that pervades the wind power harnessing. Furthermore, the energy production estimation of the exemplified hypothetical wind farm also decreased, allowing an improvement on the accuracy of the energy generation prediction and benefiting the reliability of wind power in the Brazilian electric system.

The wind power prediction plays a vital role in a wind power project both during the planning and operational phase of a project. A time series based wind power prediction model is introduced and the simulations are run for different case studies. The prediction model works based on the input from 1) nearby representative wind measuring station 2) Global average wind speed value from Meteorological Institute Uppsala University mesoscale model (MIUU) 3) Power curve of the wind turbine. The measured wind data is normalized to minimize the variation in the wind speed and multiplied with the MIUU to get a distributed wind speed. The distributed wind speed is then used to interpolate the wind power with the help of the power curve of the wind turbine. The interpolated wind power is then compared with the Actual Production Data (APD) to validate the prediction model. The simulation results show that the model works fairly predicting the Annual Energy Production (AEP) on monthly averages for all sites but the model could not follow the APD trend on all cases. The sensitivity analysis shows that the variation in production does not depend on ’the variation in roughness class’ nor ’the difference in distance between the measuring station and the wind farm’. The thesis has been concluded from the results that the model works fairly predicting the AEP for all cases within the variation bounds. The accuracy of the model has been validated only for monthly averages since the APD was available only on monthly averages. But the accuracy could be increased based on future work, to assess the Power law exponent (a) parameter for different terrain and validate the model for different time scales provided if the APD is available on different time scales.

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