SYSTEMS AND METHODS FOR MODELING ENERGY CONSUMPTION AND CREATING DEMAND RESPONSE STRATEGIES USING LEARNING-BASED APPROACHES

Patent №

US 9,817,375

Granted

2017-11-14

Filed 2015

Owner

THE BOARD OF TRUSTEES OF THE UNIVERSITY OF ALABAMA

Lab

AI components

3

ml · planning · evo

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

14632009

According to various implementations, a demand response (DR) strategy system is described that can effectively model the HVAC energy consumption of a house using a learning based approach that is based on actual energy usage data collected over a period of days. This modeled energy consumption may be used with day-ahead energy pricing and the weather forecast for the location of the house to develop a DR strategy that is more effective than prior DR strategies. In addition, a computational experiment system is described that generates DR strategies based on various energy consumption models and simulated energy usage data for the house and compares the cost effectiveness and energy usage of the generated DR strategies.

Machine learningPlanningEvolutionary computationG05B 13/04F24F 11/30F24F 11/46F24F 11/62F24F 11/66G06N 3/084G06N 3/006

AI classification

Evolutionary computation1.00
Machine learning1.00
Planning1.00
AI hardware0.10
Knowledge representation0.07
Speech0.01
Natural language0.00
Vision0.00

Ownership

THE BOARD OF TRUSTEES OF THE UNIVERSITY OF ALABAMA

assignment · 356770037

Assignors

LI, SHUHUI, SUN, MIN, ZHANG, DONG

On an employer assignment, the assignors are typically the inventors.

© 2026 NYSGPT2525 LLC