Determining the flexibility of power systems with high share of wind generation using artificial neural networks

Integration of renewable energy sources in the electric power system (EPS) can introduce some uncertainties to the EPS operation. In this case, normal and secure operation of the system requires information about its flexibility. This paper explores the flexibility of the EPS with high share of wind generation supported by the battery energy storage system using artificial neural networks. The flexibility metric is expressed as the difference between the desired (target) loads at the considered nodes and the largest loads that the EPS can handle. In this study, the flexibility of a 6-node EPS is calculated for the ten minutes ahead operational point.