Wind Farm Modeling in DIgSILENT PowerFactory® and Load Flow Analysis of Internal Collector Network

Abstract: The purpose of this study is to model an operational wind farm in DIgSILENT PowerFactory® using manufactures specifications and investigate the active power energy losses. The model is tested with the operational recorded data from the wind farm and is validated. Meeting the increased demand for renewably generated electricity drives the growth in wind energy which in turn gradually decrease the suitable locations to construct wind farms. On the other hand, the market forces persuade the wind farm developers to maximize the return on investments. Therefore, it is imperative to have optimized wind farm designs as well as accurate financial prognosis. Accurate models are important to estimate the wind farm characteristics while realistic loss estimations are needed for precise financial forecasting. One of the major components of the wind farm is the internal collector network through which the generated electricity is fed to the national electricity grid. With this study, modeling of internal collector network of an operational wind farm is carried out and the capability of the wind farm to maintain the stipulated voltage levels at the point of common coupling is examined together with the amount of cable loading. In addition, the active power energy losses, the impact of the internal collector network arrangement to the active power energy losses are investigated and a proposal to reduce the cost of cable laying for 4 cable sections is proposed for future wind farm designs. The findings of this report show that the internal collector network of the considered wind farm can maintain required voltage levels at the medium voltage busses of the network for different grid voltage levels. The operational data of power loss of the cables of the network match with the simulated results but the total loss does not. The reasons behind this mismatch could be the limited amount of operational data and measurement errors. Further analysis and comparison are suggested with larger sets of data together with the respective list of events to increase number of data points for the simulation.