Benson Lab Sally Benson

COOLER

COOLER (Chilled Water Optimization for Lower Energy and Resilience) reimagines how buildings interact with Stanford’s evolving district energy system. It integrates proactive demand response and smarter energy decisions, spanning individual zone control to campus-wide systems including chilled water loops, heat recovery chillers, and thermal energy storage. 

COOLER leverages AI and distributed sensing to close operational gaps, forecast building loads, and coordinate flexible energy resources across temporal and spatial scales. These capabilities support energy efficiency, system resilience, and climate goals in a dynamic campus environment. The project explores three key thrusts as explained below.

 

Flexibility-Informed Operations

Focus Area

Leverages temperature-linked cooling consumption data and predictive algorithms to shape smarter, adaptive building performance.

Flexibility-Informed Planning

Focus Area

Identifies key building characteristics that drive flexibility to reduce infrastructure needs and improve energy reliability during extreme events.

Compensating for Flexibility

Focus Area

Reshapes demand curves with modest interventions, and measures cost of flexibility through expert interviews and contingent valuation surveys.

Selected Publications

  1. A Naeem et al. (2025). EnergyPlus as a computational engine for commercial building operational digital twins. Energy and Buildings.
  2. M Hu, SM Benson, JA de Chalendar (2024). Identifying suitable thermal response models for demand response management in multi-zone commercial buildings. Proceedings of ASim Conference.
  3. A Naeem, SM Benson, JA de Chalendar (2023). Data-driven characterization of cooling needs in a portfolio of co-located commercial buildings. iScience.
  4. JA de Chalendar, A Keskar, JX Johnson, JL Mathieu (2023). Living Laboratories Can and Should Play a Greater Role to Unlock Flexibility in US Commercial Buildings. Joule.
  5. M Hu, R Rajagopal, JA de Chalendar (2023). Empirical Exploration of Zone-by-zone Energy Flexibility: a Non-intrusive Load Disaggregation Approach for Commercial Buildings. Energy and Buildings.
  6. RC Triolo, R Rajagopal, FA Wolak, JA de Chalendar (2023). Estimating demand flexibility in a district energy system using temperature setpoint changes from selected buildings. Applied Energy.
  7. JA de Chalendar, C McMahon, L Fuentes Valenzuela, PW Glynn, SM Benson (2022). Unlocking Demand Response in Commercial Buildings: Empirical Response of Commercial Buildings to Daily Cooling Set Point Adjustments. Energy and Buildings.

Additional Resources

Learn more about Cooler Project at:

  1. Energy Analytics Dashboard
  2. Published Datasets
  3. Published Source Codes: Energy Models, Temperature Setback Experiments

For more information, contact Aqsa Naeem.