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Microgrid Controller Testing Using Power Hardware-in-the-Loop

doi: 10.3390/en13082044
Required functions of a microgrid become divers because there are many possible configurations that depend on the location. In order to effectively implement the microgrid system, which consists of a microgrid controller and components with distributed energy resources (DERs), thorough tests should be run to validate controller operation for possible operating conditions. Power-hardware-in-the-loop (PHIL) simulation is a validation method that allows different configurations and yields reliable results. However, PHIL configuration for testing the microgrid controller that can evaluate the communication between a microgrid controller and components as well as the power interaction among microgrid components has not been discussed. Additionally, the difference of the power rating of microgrid components between the deployment site and the test lab needs to be adjusted. In this paper, we configured the PHIL environment, which integrates various equipment in the laboratory with a digital real-time simulation (DRTS), to address these two issues of microgrid controller testing. The test in the configured PHIL environment validated two main functions of the microgrid controller, which supports the diesel generator set operations by controlling the DER, regarding single function and simultaneously activated multiple functions.
distributed energy resource; frequency control; laboratory testing; microgrid; off-grid; power hardware-in-the-loop, distributed energy resource, Technology, off-grid, T, microgrid, frequency control, laboratory testing, power hardware-in-the-loop
distributed energy resource; frequency control; laboratory testing; microgrid; off-grid; power hardware-in-the-loop, distributed energy resource, Technology, off-grid, T, microgrid, frequency control, laboratory testing, power hardware-in-the-loop
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).22 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
