Browsing by Author "Paaso, Sakarias"

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Comparing Wind Power Generation Revenues at Seven Different Locations in Finland
(2020-11-27) Paaso, Sakarias
Insinööritieteiden korkeakoulu | Bachelor's thesis
Mixed integer linear programming based algorithms for wind farm layout optimization
(2022-08-22) Paaso, Sakarias
Sähkötekniikan korkeakoulu | Master's thesis
Wind power is an increasingly important source of energy in electricity generation. In industrial scale applications, it is usually installed in wind farms that consist of multiple wind turbines. When installing many wind turbines in an area, determining the placement and number of turbines (layout) is a complex problem due to for example, shadowing effects between wind turbines and varying wind conditions inside the wind farm. Additionally, the decision about the layout is a major factor in determining the profitability of the wind farm for example through its effect on the energy production of the wind farm and the number of turbines to be purchased. In this thesis, novel mixed integer linear programming based algorithms and a model are developed for optimizing the layout of a wind farm. The basic model for the optimization maximizes the revenue of the wind farm considering among others the shadowing effects between wind turbines. The model can also easily incorporate many features that are relevant in real world applications, such as existing wind farms. Of the algorithms formulated, two (BMD and BMS) are designed for refining the results of the basic model, one (Add-1) is for determining the optimal number of turbines and two (RF and DF) are designed for improving a given input layout. The methods developed for layout optimization are shown to perform at least as well as other algorithms formulated in the existing literature in the selected example cases in which the comparison was possible. It is also shown that the methods perform strongly in real world applications and provide up to 2.88 % increase in the annual energy production compared to the existing wind farms with the input wind data and assumptions about for example the wake loss model. Importantly, the time taken for optimization in all the examined cases is shown to be such short that the methods can be concluded to be useful in practical applications.
Wind power revenue potential: Simulation for Finland
(2021-05-31) Paaso, Sakarias; Khosravi, Ali
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Potential revenue from wind power generation is an important factor to be considered when planning a wind power investment. In the future, that may become even more important because it is known that wind power generation tends to push electricity wholesale prices lower. Consequently, it is possible that if a region has plenty of installed wind power capacity, revenue per generated unit of electricity is lower there than could be assumed by looking at the mean electricity wholesale price. In this paper, we compare 17 different locations in Finland in terms of revenue from wind power generation. That is done by simulating hourly generation with three different turbine types at two different hub heights and multiplying that by the hourly electricity spot price for years 2018 and 2019. Estimated revenues differ greatly between locations and turbine types, major factor being technical potential i.e., the amount of electricity generated. Differences between revenues per generated MWh seem to be small, however, the smallest figures being on the western coast where installed capacities are also the largest in Finland.