Optimal Placing of Wind Turbines: Modelling the Uncertainty

Abstract

Abstract-When looking at the optimal place to locate a wind turbine, trade-offs have to be made between local placement and spreading: transmission loss favours local placements and the correlation between the stochastic productions of wind turbines favours spreading. In this paper steps are described to determine the locations of new wind mills that minimize energy loss on the High Voltage power grid. A vindication of the used power grid model is provided, the simulation procedure for stochastic wind power is described and the required mathematical optimization models are described as well as implemented. Results are shown and their relation to real life problems is discussed. The analysis leads to the observation that in reality the entire Dutch coast is popular to locate wind turbines but the only region where this leads to actual reduction of the losses is the North (Groningen and Friesland). Next to this, at the current share of wind energy in the total network load, a spreading strategy to reduce variance of total wind power production does not seem advisable. At higher penetration (30% or more) spreading will become important.

A statistical Time-Of-Use tariff based wind resource clustering approach using Self-Organizing Maps

“…Despite the small dimensions of the island in this case study, 175 by 80 km, the similarity in the results shows that clustering is a viable data reduction approach for the geospatial optimization of wind energy. Leenman and Phillipson (2015) presented a technique for the optimal allocation of wind energy in order to reduce transmission line losses. The proposed methodology is applied for a Dutch case study with data collected from 50 weather stations for a period of 10 years.…”