Demand Response & Ancillary Services

Development of a distributed control framework to coordinate multiple buildings as flexible energy resources for ancillary services

The future electric grid is envisioned with a new ancillary services structure where large single generation units will be displaced with many distributed assets as flexible reserves. This shift requires coordination and control of these distributed assets to achieve a coherent response and to guarantee grid stability. To address this challenge, we propose a real-time distributed controller for managing flexible building HVAC loads in order to provide ancillary services to the grid.

An aggregator is an entity that coordinates multiple buildings in the ancillary market. We define as fleet a group of buildings a participating in the ancillary services under a particular aggregator. The dynamic thermal model structure developed for Objective 1 is used to forecast available flexible load (load that can be shed without degrading quality of service) of an individual building for the next 24 hours. The aggregator collects all the flexibility forecasts from individual buildings in the fleet, compute an aggregate flexibility, and bid on the ancillary services market. From the grid operator’s perspective, the aggregator is a single flexible resource with a very large demand response capacity. The aggregation, bidding, and pricing dynamics are important aspects of the ancillary services market; but within the BuildingControls project, we assume those mechanisms are in place, and they are beyond our scope. The contribution of the BuildingsControl project will be a distributed iterative control architecture to coordinate the fleet in real-time to robustly serve the regulation/demand response request from the grid operator. The fast response time required by the grid ancillary services and the scale of the problem prohibits a centralized solution. In our distributed framework, each building iterates its local optimization problem as a response to the actuation signal from the aggregator in a decentralized fashion, while ensuring the quality of service (e.g. zone temperature) is within acceptable limits.