An Optimal Power Flow Algorithm to Achieve Robust Operation Considering Load and Renewable Generation Uncertainties

Abstract

Consideration of uncertain injections in optimal power flow (OPF) calculation is increasingly important because more renewable generators, whose outputs are variable and intermittent, are connected into modern power systems. Since it is often difficult to predict the variations of both load and renewable generator output accurately, this paper proposes an OPF algorithm to make optimized results not only have a high probability to achieve minimized generation cost, but also robust to the uncertain operating states. In this paper, the objective of the OPF is to minimize the generation cost of the scenario which has the largest probability to appear in the future. In order to make the OPF result be able to accommodate other possible scenarios, the OPF constraints are modified. Considering the probabilistic distributions of both load and renewable energy output, the modified constraints are derived from Taguchi's orthogonal array testing and probabilistic power flow calculation. The effectiveness of the proposed OPF method is demonstrated by the cases up to the system with 2736 buses.