skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Learning-Based Demand Response in Grid Interactive Buildings via Gaussian Processes

Journal Article · · Electric Power Systems Research

This paper presents a predictive controller for a grid-interactive multi-zone building where the temperature dynamics are learned via Gaussian Process (GP) regression. We investigate the development of a learning-based predictive control with two main objectives: (i) continuously learn the temperature dynamics of the building based on data; and, (ii) use the learned dynamics to solve a multi-objective predictive control problem to guarantee occupants' comfort and energy efficiency during normal conditions and demand response events. We leverage the probabilistic non-parametric properties of GPs to estimate the (unknown) non-linear temperature dynamics of the building and to incorporate the uncertainty of those predictions in a multi-objective optimization problem. The GP-based predictive control is solved via a zero-order primal-dual projected-gradient algorithm. We evaluate numerically the performance of the proposed controller using a five-zone commercial building.

Research Organization:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office
DOE Contract Number:
AC36-08GO28308
OSTI ID:
1882679
Report Number(s):
NREL/JA-5D00-83774; MainId:84547; UUID:7ce5d4d4-3e0f-43e8-abe0-9a3a73a4348d; MainAdminID:65136
Journal Information:
Electric Power Systems Research, Vol. 211
Country of Publication:
United States
Language:
English

References (7)

All you need to know about model predictive control for buildings journal January 2020
Gaussian process model predictive control of unknown non‐linear systems journal February 2017
Data-Driven Model Predictive Control with Regression Trees—An Application to Building Energy Management journal January 2018
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning: Principals, Recent Advances, and Applications journal September 2020
Coordinating the operations of smart buildings in smart grids journal October 2018
Deep Reinforcement Learning for Joint Datacenter and HVAC Load Control in Distributed Mixed-Use Buildings journal July 2021
Multi-Agent Deep Reinforcement Learning for HVAC Control in Commercial Buildings journal January 2021