Efficient estimator of probabilities of large power spills in an stand-alone system with wind generation and storage

The challenges of integrating unpredictable wind energy into a power system can be alleviated using energy storage devices. We assessed a single domestic energy system with a wind turbine and a battery. We investigated the best operation mode of the battery such that the occurrence of large power spills is minimized. To estimate the small probability of large power spills, we used the splitting technique for rare-event simulations and to do so, we formulated an appropriate Importance Function such that the workload of the probability estimator is reduced compared to the conventional Crude Monte Carlo estimator. We find that the ramp constraint imposed on the charging/discharging rate of the storage device plays a major role in minimizing large power spills. A new charging strategy for the battery is applied to reduce the large power spills further which results in a trade-off between reductions in large and average power spills, respectively.