Skip to main navigation
Skip to search
Skip to main content
Penn State Home
Help & FAQ
Link opens in a new tab
Search content at Penn State
Home
Researchers
Research output
Research units
Equipment
Grants & Projects
Prizes
Activities
HVAC Power Conservation through Reverse Auctions and Machine Learning
Enrico Casella
, Atieh R. Khamesi
, Simone Silvestri
, D. A. Baker
, Sajal K. Das
Animal Science
Institute for Computational and Data Sciences (ICDS)
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
12
Link opens in a new tab
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'HVAC Power Conservation through Reverse Auctions and Machine Learning'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Machine Learning
100%
Reverse Auction
100%
Power Conservation
100%
Power Saving
50%
User Behavior
50%
Greedy
33%
Texas
16%
Online Survey
16%
Machine Learning Techniques
16%
NP-hard Problem
16%
Air Conditioning
16%
Near-optimal Performance
16%
Comprehensive Approach
16%
Highly Heterogeneous
16%
Peak Load
16%
Survey Results
16%
Highly Linear
16%
Outage
16%
High-fidelity Simulator
16%
Efficient Heuristics
16%
EnergyPlus
16%
Smart Meter
16%
Computing Technology
16%
Electric Power Systems
16%
Margin of Error
16%
Willingness to Adopt
16%
Auction-based
16%
Auction Mechanism
16%
Outside Temperature
16%
Pervasive Computing
16%
Formal Properties
16%
Energy Bill
16%
Financial Rewards
16%
Catastrophic Events
16%
Polynomial Complexity
16%
Smart Thermostat
16%
Novel Machine
16%
Thermostat
16%
Residential Heating
16%
Thermostat Settings
16%
Individual Rationality
16%
Computer Science
User Behavior
100%
Learning System
100%
Machine Learning
100%
Online Survey
33%
Optimal Performance
33%
Computing Technology
33%
Smart Meters
33%
Pervasive Computing
33%
Polynomial Complexity
33%
Individual Home
33%
Engineering
Air Conditioning
100%
Learning System
100%
Limitations
20%
Optimal Performance
20%
Outages
20%
Air Conditioning System
20%
Rationality
20%
Peak Load
20%
Simulator Fidelity
20%
EnergyPlus
20%
Electric Power Systems
20%
Smart Meter
20%
Catastrophic Event
20%