Experimental validation dataset for distributed MPC for peak load management
Description
This dataset contains the experimental data used for the validation of the penalty-based distributed model-based predictive control (MPC) framework. The dataset includes time-series measurements of indoor air temperature, outdoor air temperature, solar radiation, and HVAC power consumption collected at 5-minute intervals during the experimental validation period. The data support the results presented in the associated manuscript and are provided to facilitate the reproducibility of the experimental findings.
Files
Steps to reproduce
The dataset was collected during the experimental validation of a penalty-based distributed model-based predictive control (MPC) framework for coordinated HVAC operation in a dual-zone experimental chamber. Indoor air temperature and HVAC power consumption were measured at 5-minute intervals throughout the experimental period. Indoor air temperature was measured using Arduino-based temperature sensors, while HVAC power consumption was monitored using smart power meters. Outdoor air temperature and solar radiation data were obtained from the Korea Meteorological Administration (KMA). The collected data were used to evaluate the thermal performance, energy consumption, and peak-load management performance of the proposed control strategy. The data included in this dataset correspond to the experimental validation results reported in the associated manuscript.
Institutions
- Inha UniversityIncheon, Incheon
- Purdue University West LafayetteIndiana, West Lafayette