A risk-based strategy for power system optimization

This paper introduces a risk-based method to optimize the planning of power systems. This works uses the formulation of Energy Hub previously presented in the literature, as an interface among energy producers, consumers and the transportation infrastructure. Risk factors such as demands, operating and maintenance cost or power cost are considered in the optimization of the system. Mitigation actions reduce the risk impacts that may affect the system. A model predictive control approach is used to optimize the demand satisfaction and to determine the set of mitigation actions to be executed. An example of a hybrid storage system is considered. In particular, the architecture incorporates a wind generator, a Combined Heat and Power Plant (CHPP) and an intermediate hydrogen storage. A set of possible risks has been identified in the system in order to select the mitigation actions that reduce the impacts of these risks. Different simulations are executed to illustrated the benefits of the proposal.