Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

Voltage unbalance compensation with smart three-phase loads

Authors: Philip J. Douglass; Ionut Trintis; Stig Munk-Nielsen;

Voltage unbalance compensation with smart three-phase loads

Abstract

This paper describes the design, proof-of-concept simulations and laboratory test of an algorithm for controlling active front-end rectifiers to reduce voltage unbalance. Using inputs of RMS voltage, the rectifier controller allocates load unevenly on its 3 phases to compensate for voltage unbalance originating in the power supply network. Two variants of the algorithm are tested: first, using phase-neutral (P-N) voltage as input, second, using phase-phase (P-P) voltage. The control algorithm is described, and evaluated in simulations and laboratory tests. Two metrics for quantifying voltage unbalance are evaluated: one metric based on the maximum deviation of RMS P-N voltage from the average voltage and one metric based on negative sequence voltage. The tests show that controlling P-N voltage can in most cases eliminate the deviations of P-N voltage from the average voltage, but it does not reduce the negative sequence voltage. The controller that uses the P-P voltage as input eliminates the negative sequence voltage, and reduces P-N voltage deviations from the average to approximately half of their initial value. Current unbalance is reduced when the voltage unbalance is caused by asymmetrical loads, but it is increased in a scenario with unbalanced voltage sources. These results suggest that the optimal algorithm to reduce system unbalance depends on which system parameter is most important: RMS P-N voltage unbalance, negative sequence voltage, or current unbalance.

Related Organizations
  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    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).
    10
    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.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Top 10%
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!