Smart homes and virtual power plant (VPP) controls are growing fields of research with potential for improved electric power grid operation. A novel testbed for the co-simulation of electric power distribution systems and distributed energy resources (DERs) is employed to evaluate VPP scenarios and propose an optimization procedure. DERs of specific interest include behind-the-meter (BTM) solar photovoltaic (PV) systems as well as heating, ventilation, and air-conditioning (HVAC) systems. The simulation of HVAC systems is enabled by a machine learning procedure that produces ultra-fast models for electric power and indoor temperature of associated buildings that are up to 133 times faster than typical white-box implementations. Hundreds of these models, each with different properties, are randomly populated into a modified IEEE 123-bus test system to represent a typical U.S. community. Advanced VPP controls are developed based on the Consumer Technology Association (CTA) 2045 standard to leverage HVAC systems as generalized energy storage (GES) such that BTM solar PV is better utilized locally and occurrences of distribution system power peaks are reduced, while also maintaining occupant thermal comfort. An optimization is performed to determine the best control settings for targeted peak power and total daily energy increase minimization with example peak load reductions of 25+%.
|State||Published - Jun 2023|
Bibliographical noteFunding Information:
The support of the Department of Energy (DOE) through the project DEEE0009021 led by the Electric Power Research Institute (EPRI) is gratefully acknowledged. The support received by Evan S. Jones through a Department of Education (DoEd) GAANN Fellowship and by Rosemary E. Alden through an NSF Graduate Research Fellowship (NSF) under Grant No. 1839289 is also gratefully acknowledged. Any opinions, findings, and conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of DOE, DoEd, and NSF.
© 2023 by the authors.
- building energy model (BEM)
- distributed energy resources (DERs)
- generalized energy storage (GES)
- HVAC systems
- machine learning (ML)
- power distribution system
- smart grid
- smart home
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Geography, Planning and Development
- Renewable Energy, Sustainability and the Environment
- Environmental Science (miscellaneous)
- Energy Engineering and Power Technology
- Hardware and Architecture
- Computer Networks and Communications
- Management, Monitoring, Policy and Law