An enhanced predictive hierarchical power management framework for islanded microgrids
Abstract This paper proposes an enhanced three‐layer predictive hierarchical power management framework for secure and economic operation of islanded microgrids. The tertiary control, guaranteeing the microgrid economic operation, is built upon the semi‐definite programming‐based AC optimal power fl...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-02-01
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| Series: | IET Generation, Transmission & Distribution |
| Online Access: | https://doi.org/10.1049/gtd2.12297 |
| _version_ | 1818311039924568064 |
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| author | Jimiao Zhang Jie Li Ning Wang Ben Wu |
| author_facet | Jimiao Zhang Jie Li Ning Wang Ben Wu |
| author_sort | Jimiao Zhang |
| collection | DOAJ |
| description | Abstract This paper proposes an enhanced three‐layer predictive hierarchical power management framework for secure and economic operation of islanded microgrids. The tertiary control, guaranteeing the microgrid economic operation, is built upon the semi‐definite programming‐based AC optimal power flow model, which periodically sends power references to secondary control. To mitigate uncertainties arising from renewable generations and loads, a centralized linear model predictive control (MPC) controller is proposed and implemented for secondary control. The MPC controller can effectively regulate the microgrid system frequency by closely tracking reference signals from the tertiary controller with low computational complexity. Droop‐based primary controllers are implemented to coordinate with the secondary MPC controller to balance the system in real time. Both synchronous generators (SGs) and solar photovoltaics (PVs) are simulated in the microgrid power management framework. A unified linear input‐state estimator (ULISE) is proposed for SG state variable estimation and control anomaly detection due to compromised cyber‐physical system components, etc. Simulation results demonstrated that SG states can be accurately estimated, while inconsistency in control signals can be effectively detected for an enhanced MPC. Furthermore, comparing with conventional proportional‐integral (PI) control, the proposed hierarchical power management scheme exhibits superior frequency regulation capability whilst maintaining lower system operating costs. |
| first_indexed | 2024-12-13T07:55:37Z |
| format | Article |
| id | doaj.art-68e32b7b3e5b4d5e8d14e04507cdd38b |
| institution | Directory Open Access Journal |
| issn | 1751-8687 1751-8695 |
| language | English |
| last_indexed | 2024-12-13T07:55:37Z |
| publishDate | 2022-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Generation, Transmission & Distribution |
| spelling | doaj.art-68e32b7b3e5b4d5e8d14e04507cdd38b2022-12-21T23:54:33ZengWileyIET Generation, Transmission & Distribution1751-86871751-86952022-02-0116350351610.1049/gtd2.12297An enhanced predictive hierarchical power management framework for islanded microgridsJimiao Zhang0Jie Li1Ning Wang2Ben Wu3Department of Electrical and Computer Engineering Rowan University Glassboro New Jersey USADepartment of Electrical and Computer Engineering Rowan University Glassboro New Jersey USADepartment of Computer Science Rowan University Glassboro New Jersey USADepartment of Electrical and Computer Engineering Rowan University Glassboro New Jersey USAAbstract This paper proposes an enhanced three‐layer predictive hierarchical power management framework for secure and economic operation of islanded microgrids. The tertiary control, guaranteeing the microgrid economic operation, is built upon the semi‐definite programming‐based AC optimal power flow model, which periodically sends power references to secondary control. To mitigate uncertainties arising from renewable generations and loads, a centralized linear model predictive control (MPC) controller is proposed and implemented for secondary control. The MPC controller can effectively regulate the microgrid system frequency by closely tracking reference signals from the tertiary controller with low computational complexity. Droop‐based primary controllers are implemented to coordinate with the secondary MPC controller to balance the system in real time. Both synchronous generators (SGs) and solar photovoltaics (PVs) are simulated in the microgrid power management framework. A unified linear input‐state estimator (ULISE) is proposed for SG state variable estimation and control anomaly detection due to compromised cyber‐physical system components, etc. Simulation results demonstrated that SG states can be accurately estimated, while inconsistency in control signals can be effectively detected for an enhanced MPC. Furthermore, comparing with conventional proportional‐integral (PI) control, the proposed hierarchical power management scheme exhibits superior frequency regulation capability whilst maintaining lower system operating costs.https://doi.org/10.1049/gtd2.12297 |
| spellingShingle | Jimiao Zhang Jie Li Ning Wang Ben Wu An enhanced predictive hierarchical power management framework for islanded microgrids IET Generation, Transmission & Distribution |
| title | An enhanced predictive hierarchical power management framework for islanded microgrids |
| title_full | An enhanced predictive hierarchical power management framework for islanded microgrids |
| title_fullStr | An enhanced predictive hierarchical power management framework for islanded microgrids |
| title_full_unstemmed | An enhanced predictive hierarchical power management framework for islanded microgrids |
| title_short | An enhanced predictive hierarchical power management framework for islanded microgrids |
| title_sort | enhanced predictive hierarchical power management framework for islanded microgrids |
| url | https://doi.org/10.1049/gtd2.12297 |
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