Decentralized wind power as part of the relief for an overstrained grid. A case study on Northern Senja, Norway

• Main Author: Bednorz, Paul
• Format: Master Thesis
• Language: English
• Published: UiT The Arctic University of Norway 2019
• Subjects: Wind power assessment; Wind speed interpolation; Geographical information system; VDP::Technology: 500::Environmental engineering: 610; VDP::Teknologi: 500::Miljøteknologi: 610; EOM-3901; Norway; Senja; Northern Norway
• Online Access: https://hdl.handle.net/10037/16583

The most significant factor in wind turbine siting is the wind conditions. Those often determine the economic and ecologic success of a project. Especially in topographically complex areas micro siting can be difficult and costly. Small and medium scale projects often lack the knowledge and resources for an extended in situ assessment. A combination of modelled wind data and the use of a geographic information system (GIS) could be an economical competitive approach to find and compare different wind power sites over a larger defined region. This thesis looks at the small community of Northern Senja, a sparsely populated island in Northern Norway. It evaluates the possibility of community scale wind power (maximum 1MW nominal power) with the help of numerical weather prediction (NWP) wind data. The challenge therein lies in the incapability of mesoscale data to predict the influence of the island’s highly complex topography on the wind flow. This mesoscale data is therefore interpolated to a finer grid and corrected for the effect of using a smoothed terrain model. Production maps for a set of predetermined turbines are created with these corrected data and – together with non-wind related criteria – suitable wind power sites determined. One idea behind this approach is to use free accessible satellite data and to work economical on computational resources. It is possible to correct the wind speed for height differences, but the method seems to underestimate the shear effects of the complex topography that leads to a probable overestimation of the expected production. Better tuning with the help of real life measurements, which currently are lacking, and an improved implementation of orographic roughness are proposed to resolve that challenge.