Analytic Corrective Control Selection for Online Remedial Action Scheme Design

What is it about?

Cyber attacks and other unpredictable events cannot be accounted for with traditional look-up tables used for remedial action schemes (RAS); such contingencies have dynamic trajectories that are difficult to characterize and plan for. Online RAS schemes are needed to compute the most effective corrective actions in these situations but need to be fast and accurate to perform necessary calculations in real-time. Therefore, this paper develops an analytic corrective control selection algorithm that reduces the corrective control search space using clustering and factorization techniques, based on controllability analysis, and finds the minimum, most effective set of corrective controls to respond to the contingency.

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Why is it important?

Cyber attacks can have severe consequences in the grid and current response mechanisms do not account for them. Different approaches, such as online RAS, need to be investigated and new techniques must be applied to increase feasibility and efficiency. This work, the analytic corrective control selection algorithm, develops an effective method for identifying critical controls that allow for fast calculation and deployment to best combat any given contingency.