Justin Hughes with adviser A. Domínguez-García
We discuss a framework for coordinating the response of distributed energy resources (DERs) connected to electric power distribution networks to provide frequency regulation services. These resources include plug-in electric vehicles, thermostatically controlled loads, and micro-turbines. In this framework, we consider an agent or aggregator that participates in the real-time market by submitting an offer to provide frequency regulation services. If the offer is accepted, the aggregator needs to coordinate the response of a set of DERs. The DERs are compensated through bilateral contracts, the terms of which are negotiated in advance. The DER coordination problem the aggregator is faced with is cast as a stochastic optimal control problem. This can be sub-optimally solved using model-predictive control techniques driven by regulation signal forecasts. Using numerical simulation, we study the performance of this approach with different forecasting techniques and its sensitivity with respect to operational costs of generation and storage.
Figure 28 shows numerical time series results from our simulation studies. From left to right: optimal input signals, regulation signal reference and actual regulation responses, and state of charge for energy limited resource.
This work was supported in part by PSERC and NSF.