Predictive Decision Support to Protect Power Systems against Wind Farm Drop Outs

A predictive decision support algorithm for power systems with a high share of renewable generation is presented. We consider a scenario where, e.g. within 1 hour, the renewable share is first gradually increased and compensated by secondary reserve. Then, a sudden disconnection of one or several wind farms occurs, e.g., because of violated fault ride through requirements. This disconnection has to be compensated by primary reserve. For this scenario, the proposed algorithm provides suggestions how to distribute the secondary reserve such that the subsequent wind farm drop out does not lead to an unacceptable power flow. The algorithm is based on novel power flow optimization techniques. Hence, it only considers the steady-state power flow after the wind farm drop out but does not consider constraints on the transient dynamics. The algorithm is illustrated in a practical simulation example.