The Swedish Wind Energy Association (SWEA, 2019) reported the wind power project's total investment cost between 2017 and 2021 was over SEK 72 billion. They predicted that at project completion, the total production will be approximately 22.4 TWh per year. Due to project size, complexity, and long-term contracts commitments, almost all wind power project developers outsource some or most of their project activities to different subcontractors, after which they perform monitoring activities of the project process. Therefore, the pre-qualification stage and subcontractors’ evaluation become essential parts of every project. Most corporates and authorities are usually awarding projects to subcontractors with offers based on the most competitive price advantage. This approach results in high risks that can affect the delivery time, the overall cost, and the quality of wind power projects.This research paper aims to use a multi-criteria analysis to identify and select the most adequate subcontractor. To achieve the research purpose, a sample of five subcontractors nominated by a windpower developer were evaluated in a selection phase under nine criteria: (1) management capability, (2) product or service quality, (3) planning and capabilities, (4) quality assessment,(5) environmental management, (6) health and safety measures, (7) financial strength, (8) contract insurances and guaranties, and (9) cost. After the evaluation and the ranking of companies, a result of the most adequate subcontractor for the project offer was presented. At the end of this study, a comparison analysis was followed at the final stage which compared the method with a similar procurement approach used by one corporate where it showed that this paper’s method can uncover critical aspects with subcontracts which can alter the selection process.

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.

Vietnam has fundamental advantages to implement the wind power project. Because of being surrounded by sea areas, wind power projects in Vietnam have a promise future. However, implementing an ecotechnic analysis of a wind power project has a fairly challenge because of seasonal change as well as input data’s fluctuation. The paper presented a method based on Matlab programming utilized for ecotechnic analysis the wind power projects. The math diagram built with the consideration of all input data’s changing will be shown to make the ecotechnic analysis easier and faster. The results deducted from Matlab programming will be compared with ones made by expertise method. The conclusion about advantages of method is pointed out to help project managers have another choice in making ecotechnic analysis of wind power project. / Việt Nam có những thuận lợi cơ bản để thực thu các dự án điện gió. Do đặc điểm địa lý, bao quanh bởi khá nhiều các vùng biển, các dự án điện gió của Việt Nam có tính khả thi và một tương lai đầy hứa hẹn. Tuy vậy, thực thi các phân tích kinh tế kỹ thuật của một dự án điện gió có thách thức không nhỏ bởi những thay đổi của yếu tố mùa cũng như những thay đổi của các yếu tố đầu vào. Bài báo giới thiệu một phương pháp dựa vào quá trình lập trình trên Matlab, ứng dụng để phân tích kinh tế kỹ thuật các dự án điện gió. Lưu đồ thuật toán được xây dựng có xem xét đến sự thay đổi của các yếu tố đầu vào sẽ giúp quá trình phân tích nhanh hơn và dễ dàng hơn. Các kết quả thu được sẽ được so sánh với các kết quả được tiến hành theo phương pháp chuyên gia. Kết luận về những ưu điểm của phương pháp cũng được đưa ra để giúp các nhà quản lý các dự án điện gió có được lựa chọn nữa trong tiến hành phân tích kinh tế kỹ thuật các dự án điện gió.