Improved planning of wind farms using dynamic transformer rating

Abstract: Due to the increase in electrical demand and renewable penetration, electrical utilities need to improve and optimize the grid infrastructure. Fundamental components in this grid infrastructure are transformers, which are designed conservatively on the base of a static rated power. However, load and weather change continuously and hence, transformers are not used in the most efficient way. For this reason a new technology has been developed: Dynamic transformer rating (DTR). By applying DTR, it is possible to load transformers above the nameplate rating without affecting their life time expectancy. This project goes one step further and uses DTR for the short term and long term wind farm planning. The optimal wind farm is designed by applying DTR to the power transformer of the farm. The optimization is carried out using a Mixed-Integer Linear Programming (MILP) model. In respect of the transformer thermal analysis, the linearized top oil model of IEEE Clause 7 is selected. The model is executed for 4 different types of power transformers: 63 MVA, 100 MVA, 200 MVA and 400 MVA. As result, it is obtained that the net present value for the investment and the capacity of the wind farm increase linearly with respect to the size of the transformer. Then, a sensitivity analysis is carried out by modifying the wind speed, the electricity price, the lifetime of the transformer and the selected weather data. From this sensitivity analysis, it is possible to conclude that wind resources and electricity price are key parameters for the feasibility of the wind farm.