A DDS-Based Energy Management Framework for Small Microgrid Operation and Control
- Florida International Univ., Miami, FL (United States); University of Arkansas
- Florida International Univ., Miami, FL (United States)
The smart grid is seen as a power system with realtime communication and control capabilities between the consumer and the utility. This modern platform facilitates the optimization in energy usage based on several factors including environmental, price preferences, and system technical issues. In this paper a real-time energy management system (EMS) for microgrids or nanogrids was developed. The developed system involves an online optimization scheme to adapt its parameters based on previous, current, and forecasted future system states. The communication requirements for all EMS modules were analyzed and are all integrated over a data distribution service (DDS) Ethernet network with appropriate quality of service (QoS) profiles. In conclusion, the developed EMS was emulated with actual residential energy consumption and irradiance data from Miami, Florida and proved its effectiveness in reducing consumers’ bills and achieving flat peak load profiles.
- Research Organization:
- Florida International Univ., Miami, FL (United States)
- Sponsoring Organization:
- USDOE Office of Electricity Delivery and Energy Reliability (OE)
- Grant/Contract Number:
- OE0000779
- OSTI ID:
- 1406112
- Journal Information:
- IEEE Transactions on Industrial Informatics, Journal Name: IEEE Transactions on Industrial Informatics Journal Issue: 3 Vol. 14; ISSN 1551-3203
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
Hardware-in-the-Loop Validation of Energy Management Systems for Microgrids: A Short Overview and a Case Study
|
journal | November 2018 |
Energy Management Systems for Microgrids: Main Existing Trends in Centralized Control Architectures
|
journal | January 2020 |
Pre-Processing of Energy Demand Disaggregation Based Data Mining Techniques for Household Load Demand Forecasting
|
journal | July 2018 |
Similar Records
Validation of Microgrid Algorithms using At-Scale Simulation and Emulation Real-Time (ASSERT) Framework
Data-Centric Communication Framework for Multicast IEC 61850 Routable GOOSE Messages over the WAN in Modern Power Systems