What happened
The General Services Administration and the Department of Energy tested Logical Buildings' operator-in-the-loop software at 20 Washington Place in Newark, New Jersey. The evaluation ran from July 2021 through November 2022. The software sends alerts to building staff, who decide whether to act. Pacific Northwest National Laboratory reports that the vendor's machine learning drives its predictive alerts. In the summers of 2021 and 2022, the vendor called seven demand response events each year to cut the building's capacity and transmission charges. In 2022 its predictions matched the days that set those charges, and in 2021 they matched only some. PNNL estimated savings of $20,000 for 2022, a payback under one year. Staff could not act on 29 load management alerts within the required 15 minutes and switched them off. The vendor made no energy efficiency recommendations. The savings must still be confirmed on later bills. GSA and the Department of Energy funded the evaluation.
Sources
-
Evaluation report, by an evaluator that the makers or users commissioned.
Myer, M. Operator-in-the-Loop Grid-Interactive Efficient Building Evaluation. Pacific Northwest National Laboratory for the U.S. General Services Administration and the U.S. Department of Energy, GSA Proving Ground report GPG-055, April 2025.
These ICAP-related events resulted in $20,000 in savings for 2022.
Load management was not successful for the operator-in-the-loop option.
Details
AI system
- Workflow
-
The vendor metered the chillers and the utility meter and sent the data to its cloud. Staff received notice the day before and the morning of each demand response event. Staff shed load during the predicted hours.
Money
- Kind of value
-
Savings in capacity and transmission (ICAP) charges for 2022 from demand response on the predicted days
- Amount
-
Estimate: $20,000
- Recipients and payers
-
U.S. General Services Administration
Follow-up
- Conditions for replication
-
Staff get notice early enough to act, since alerts needing a 15-minute response went unanswered. The predicted hours coincide with the hours that the grid operator and the utility use to set the charges.
Entry details
- Sector
-
Energy (building demand response).
- Purpose
-
Logical Buildings built SmartKit AI to monitor building loads and alert staff when to shed load for demand response and load management.
Not yet checked: model, release, provider, role, configuration, inputs and outputs, autonomy, human oversight, AI contribution, beneficiaries, reach, distribution and access, duration, every measurement question, currency and prices, period and unit, realization, gross or net, included costs, comparison, method, return and payback, ownership and control, dependencies, cross-border connections, geopolitical implications, replication attempts, availability, institutional decision, grounds, action and result, success criterion, every evidence question, observed or intended, alternative assessments, related entries, other identifiers, category mappings.
Cite this record
Peter H. Vartanian. (2026). SmartKit AI alerts cut a Newark federal building's capacity charges (AIBD-0911). Artificial Intelligence Benefits Database, edition of 31 October 2026. https://petervartanian.xyz/aibd/records/AIBD-0911.html (archived at https://doi.org/10.7910/DVN/AADSII, version 4.0)