Enhanced battery controller for inertia support in residential microgrid based on active disturbance rejection control

•Inverter-interfaced generation results in lack of genuine inertia in power systems.•Grid-forming inverters respond aturallyto grid disturbances.•Residential PV-battery systems can be used to provide inertia.•Novel grid-forming control method using active disturbance rejection control.•Comparison wi...

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Bibliographic Details
Published in:Electric power systems research 2020-12, Vol.189, p.106646, Article 106646
Main Authors: Wang, Bowen, Verbič, Gregor, Xiao, Weidong, Chapman, Archie C.
Format: Article
Language:English
Subjects:
Active control
Active disturbance rejection control
Adaptive algorithms
Adaptive systems
Controllers
Converters
Distributed generation
Electricity distribution
Feedback control systems
Grid-forming control
Inertia
Optimal control
Parameters
Performance enhancement
Photovoltaic cells
Prosumers
PV-battery systems
Rejection
Residential microgrid
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Summary:•Inverter-interfaced generation results in lack of genuine inertia in power systems.•Grid-forming inverters respond aturallyto grid disturbances.•Residential PV-battery systems can be used to provide inertia.•Novel grid-forming control method using active disturbance rejection control.•Comparison with conventional PI control demonstrates superior performance. Lack of system inertia is becoming a big concern in modern power systems with a high penetration of inverter-interfaced generation. In this paper, we argue that PV-battery systems owned by end-users can be used as a source of inertia to improve the frequency performance of future grids. To that end, we implement grid-forming control on battery converters in a residential microgrid powered by prosumer-owned PV-battery systems and a back-up generator. To improve performance, we propose a novel controller based on active disturbance rejection control (ADRC). This controller observes and rejects the “total disturbance” of the system, thereby increasing the response speed and enhancing the stability of the system. In addition, we incorporate an adaptive parameter tuning algorithm into the ADRC controller, which automatically calculates and updates the optimal control parameters in every sampling period. Simulation results are provided to verify the effectiveness and feasibility of the proposed approach.
ISSN:0378-7796
1873-2046
DOI:10.1016/j.epsr.2020.106646