Frequency Stability Constraints in Economic Dispatch: Electricity Market Insights using a Neural Network Surrogate Modeling Approach

A Frequency Stability-Constrained Optimal Power Flow (FSC-OPF) problem is proposed that enforces frequency stability constraints using Neural Network (NN) surrogate models. In the context of wholesale electricity markets, pricing structures are analyzed along with their dependencies on the selected input features to the NN surrogate model. An important insight identifies a trade-off between the effectiveness of the NN surrogate model and sensible locational pricing structures. The numerical results represent frequency stability using frequency nadir limits and identify trends in prices, dispatch, and profits that follow from different selected input features. NN surrogate models for frequency stability are validated by ensuring that the resulting FSC-OPF solution is stable over randomly generated load samples using a small Hawaii test case.