Peak electricity demand, particularly to facilitate cooling in buildings, imposes a strain on aging electricity grid infrastructure, and leaves the grid particularly susceptible to brownouts and blackouts. In response, incentives have been implemented to reduce or shift electricity use during anticipated peak-demand periods, including time-of-use pricing, and recent advancements in automated demand-response (DR) implementations have been demonstrated to actively monitor peak-demand notifications and adjust building operations accordingly. However, there is a lack of field evidence to substantiate the load reduction potential of common automated DR sequences with coincident peak pricing, and discussion on the shortcomings and areas for optimization of these strategies. This research evaluates the zonal behavior of a typical DR strategy by utilizing a closed-feedback loop approach to actively monitor and automatically respond to peak-demand events; this implementation incorporates real-time electricity demand data and BAS interoperability in-situ, and is deployed on an office building in Ottawa, Canada. In the anticipated three-hour long peak-demand events which occurred every day from July 26th to July 28th, 2023, 12 of the 27 thermal zones consistently could not sustain air temperature free float for the entire curtailment duration; the reasons and their time-variant impact to cooling demand reduction are discussed.
| File Size : | 1
file
, 4.8 MB |
| Note : | This product is unavailable in Russia, Belarus |
| Number of Pages : | 10 |
| Product Code(s) : | D-CH-24-C066 |
| Published : | 2024 |
