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https://doi.org/10.1109/pesgm....
Conference object . 2016 . Peer-reviewed
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Validating unit commitment models: A case for benchmark test systems

Authors: Mingsong Li; Alexander C. Melhorn; Damian Flynn; Paula Carroll;

Validating unit commitment models: A case for benchmark test systems

Abstract

Due to increasing penetration of non-traditional power system resources; e.g. renewable generation, electric vehicles, demand response, etc. and computational power there has been an increased interest in research on unit commitment. It therefore may be important to take another look at how unit commitment models and algorithms are validated especially as improvements in solutions and algorithmic performance are desired to combat the added complexity of additional constraints. This paper explores an overview of the current state of unit commitment models and algorithms, and finds improvements for both comparing and validating models with benchmark test systems. Examples are provided discussing the importance for a standard benchmark test system(s) and why it is needed to compare and validate the real world performance of unit commitment models.

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    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).
    6
    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).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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).
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!
6
Top 10%
Average
Average