Distributed control of generation in a transmission grid with a high penetration of renewables

Deviations of grid frequency from the nominal frequency are an indicator of the global imbalance between generation and load. Two types of control, a distributed proportional control and a centralized integral control, are currently used to keep frequency deviations small. Although generation-load imbalance can be very localized, both controls primarily rely on frequency deviation as their input. The time scales of control require the outputs of the centralized integral control to be communicated to distant generators every few seconds. We reconsider this control/communication architecture and suggest a hybrid approach that utilizes parameterized feedback policies that can be implemented in a fully distributed manner because the inputs to these policies are local observables at each generator. Using an ensemble of forecasts of load and time-intermittent generation representative of possible future scenarios, we perform a centralized off-line stochastic optimization to select the generator-specific feedback parameters. These parameters need only be communicated to generators once per control period (60 minutes in our simulations). We show that inclusion of local power flows as feedback inputs is crucial and reduces frequency deviations by a factor of ten. We demonstrate our control on a detailed transmission model of the Bonneville Power Administration (BPA). Our findings suggest that a smart automatic and distributed control, relying on advanced off-line and system-wide computations communicated to controlled generators infrequently, may be a viable control and communication architecture solution. This architecture is suitable for a future situation when generation-load imbalances are expected to grow because of increased penetration of time-intermittent generation.