Mahmoud Elkazaz
A hierarchical two-stage energy management for a home microgrid using model predictive and real-time controllers
Elkazaz, Mahmoud; Sumner, Mark; Naghiyev, Eldar; Pholboon, Seksak; Davies, Richard; Thomas, David
Authors
MARK SUMNER MARK.SUMNER@NOTTINGHAM.AC.UK
Professor of Electrical Energy Systems
Eldar Naghiyev
Seksak Pholboon
RICHARD DAVIES RICHARD.DAVIES@NOTTINGHAM.AC.UK
Teaching Assistant
David Thomas
Abstract
This paper presents a hierarchical two-layer home energy management system to reduce daily household energy costs and maximize photovoltaic self-consumption. The upper layer comprises a model predictive controller which optimizes household energy usage using a mixed-integer linear programming optimization; the lower layer comprises a rule-based real-time controller, to determine the optimal power settings of the home battery storage system. The optimization process also includes load shifting and battery degradation costs. The upper layer determines the operating schedule for shiftable domestic appliances and the profile for energy storage for the next 24 h. This profile is then passed to the lower energy management layer, which compensates for the effects of forecast uncertainties and sample time resolution. The effectiveness of the proposed home energy management system is demonstrated by comparing its performance with a single-layer management system. For the same battery size, using the hierarchical two-layer home energy management system can achieve annual household energy payment reduction of 27.8% and photovoltaic self-consumption of 91.1% compared to using a single layer home energy management system. The results show the capability of the hierarchical home energy management system to reduce household utility bills and maximize photovoltaic self-consumption. Experimental studies on a laboratory-based house emulation rig demonstrate the feasibility of the proposed home energy management system.
Citation
Elkazaz, M., Sumner, M., Naghiyev, E., Pholboon, S., Davies, R., & Thomas, D. (2020). A hierarchical two-stage energy management for a home microgrid using model predictive and real-time controllers. Applied Energy, 269, https://doi.org/10.1016/j.apenergy.2020.115118
Journal Article Type | Article |
---|---|
Acceptance Date | Apr 22, 2020 |
Online Publication Date | May 16, 2020 |
Publication Date | Jul 1, 2020 |
Deposit Date | May 22, 2020 |
Publicly Available Date | Mar 28, 2024 |
Journal | Applied Energy |
Print ISSN | 0306-2619 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 269 |
Article Number | 115118 |
DOI | https://doi.org/10.1016/j.apenergy.2020.115118 |
Keywords | General Energy; Mechanical Engineering; Civil and Structural Engineering; Management, Monitoring, Policy and Law; Building and Construction |
Public URL | https://nottingham-repository.worktribe.com/output/4481580 |
Publisher URL | https://www.sciencedirect.com/science/article/pii/S0306261920306309 |
Additional Information | This article is maintained by: Elsevier; Article Title: A hierarchical two-stage energy management for a home microgrid using model predictive and real-time controllers; Journal Title: Applied Energy; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.apenergy.2020.115118; Content Type: article; Copyright: © 2020 Elsevier Ltd. All rights reserved. |
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