The University of North Carolina at Charlotte received a $100,000 Project Grant award from the National Science Foundation under the NSF Technology, Innovation, and Partnerships program (CFDA 47.084) to develop an energy conservation network software that simultaneously audits, monitors, and manages energy use in buildings in real-time. The software aims to improve energy management of commercial buildings through three main functions: an auditing functionality using pattern recognition to...
The National Science Foundation awarded a $100,003 project grant under the Engineering (47.041) federal grant program to Rensselaer Polytechnic Institute for research developing advanced artificial intelligence and machine learning techniques to intelligently control passive and hybrid conditioning systems in buildings. Specifically, the grantee will create climate- and occupant-responsive control strategies leveraging natural resources like sunlight and outdoor air to condition indoor spaces....
This Project Grant award, valued at $147,947, was provided by the National Science Foundation (NSF) under the Engineering program (CFDA 47.041) to Loyola University of Chicago. The award period runs from August 1, 2024 to July 31, 2026. The objective of this project is to develop techniques to improve the energy efficiency of software for data centers, which currently consume approximately 2% of the U.S. energy use. The key products and services to be delivered include: A framework for automated...
Under a $650,000 Project Grant from the U.S. Department of Agriculture (USDA) National Institute of Food and Agriculture through the Small Business Innovation Research (SBIR) program (CFDA 10.212), Community Energy Labs Inc. is developing and testing an innovative model architecture to enable affordable grid connectivity and energy management for small and mid-sized commercial buildings in rural communities. The project aims to shape energy use, reduce costs, and improve renewable integration...
The National Science Foundation (NSF) awarded a $999,841 Cooperative Agreement under its Technology, Innovation, and Partnerships (CFDA 47.084) program to Rivieh Inc. for the development of advanced sensor technologies and machine learning algorithms to enable an inexpensive hardware infrastructure for autonomous indoor space control. The project aims to significantly reduce energy waste in multi-dwelling and residential buildings while improving occupant living experiences. Specifically, the...
The University of Oregon was awarded a $549,999 Project Grant from the National Science Foundation under the NSF Technology, Innovation, and Partnerships federal grant program (CFDA 47.084) to develop new tools for decarbonizing space cooling and heating in buildings. The university will create marketable design software, design services, and system control hardware for dynamic passive building systems that utilize climatic resources like solar heat, cool air, and cold night skies to reduce...
This $600,000 federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) aims to integrate federated learning with power systems to better predict electricity consumption and lower the cost of electricity generation. The project will develop machine learning methods, specifically recurrent neural networks, to forecast day-ahead electricity consumption using distributed data from smart meters while preserving consumer privacy. Key scientific...
This National Science Foundation (NSF) Engineering program (CFDA 47.041) Project Grant award of $294,457 to The Leland Stanford Junior University (Stanford University) explores the feasibility of using generative artificial intelligence (AI) language models to automate the creation of building energy models. The key objectives are to: 1) test the feasibility of applying generative AI to various steps of the building energy modeling process, and 2) quantify the performance and time trade-offs...
Cornell University received a $100,000 Project Grant award from the National Science Foundation under the NSF Technology, Innovation, and Partnerships federal grant program (CFDA 47.084) to develop an optimization algorithm and machine learning clustering technique for analyzing customer energy usage patterns. The goal is to identify opportunities for moderating electricity consumption to help utilities better plan infrastructure, enhance customer relations, and avoid power outages. Key products...
This $330,000 National Science Foundation project grant supports research at Purdue University from November 2022 through July 2025 to develop analytics and a prototype system for adaptive, human-centric coordination of demand-side flexibility at scale in electric power distribution networks. The goal is to enable actionable demand-side flexibility through adequate representation of consumer constraints and interactions with the energy system and provider. Researchers will develop learning...