Robust reserve operation in power systems using affine policies

A new scheme is presented for operating electrical reserves in constrained power systems in the face of a large uncertain future wind infeed. The approach uses robust optimization with linear decision rules to determine, via a constrained convex optimization, how power system entities such as generators and storage units should act on prediction errors once they become known. These rules are specified such that the power network constraints, namely matching supply and demand, respecting transmission line ratings, and the operating limits of individual power system entities, are satisfied for all possible realizations of the prediction error. The error is assumed to be bounded and may be correlated spatially and/or temporally. The decision rules are demonstrated and compared with simpler modes of reserve operation, and cost reductions are reported. Efficient prices for such “policy-based reserves” are derived, and it is concluded that they are of particular interest to grids where both a large wind infeed and a large storage capacity are present.