Probabilistic security-constrained optimal power flow including the controllability of HVDC lines

In this paper we propose a security-constrained optimal power flow (SC-OPF) algorithm which incorporates the stochastic infeed of renewable sources, such as wind, as well as the controllability of HVDC lines. We extend our earlier work on SC-OPF problem and incorporate corrective control actions emanating form the controllability of the AGC lines. This is achieved by appropriately adjusting the HVDC setpoint after a component outage. The overall problem is formulated as chance constrained optimization program. We solve it using a scenario based methodology, which offers a-priori guarantees regarding the probability of constraint satisfaction. Moreover, we exploit recent developments in sampling based optimization allowing us to identify more optimal solutions in term of cost. To demonstrate the efficiency of our approach and the improvement in terms of cost due to the controllability offered by the HVDC lines, we apply to an IEEE benchmark network.