2013 IEEE Computational Intelligence Applications in Smart Grid (CIASG) 2013
DOI: 10.1109/ciasg.2013.6611504
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Effects of data cleansing on load prediction algorithms

Abstract: Abstract-The rollout of advanced metering infrastructure that is planned in many countries worldwide will lead to a massive inflow of data from moderately reliable sensory equipment. In principle, this will make intelligent and automated planning and operation possible at an increasingly finer scale in the electric grid. However, errors can creep into the meter data, either from faulty sensors or during transmission from the meters to the database. This work studies the role of data cleansing as a preprocessin… Show more

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Cited by 14 publications
(6 citation statements)
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“…Currently, after benefit of histograms, conversation tables and rules with algorithms individual interference is nevertheless compulsory to recognize and repair the data [30], [39].…”
Section: Manuallymentioning
confidence: 99%
“…Currently, after benefit of histograms, conversation tables and rules with algorithms individual interference is nevertheless compulsory to recognize and repair the data [30], [39].…”
Section: Manuallymentioning
confidence: 99%
“…The SINTEF data was recorded from 2004 through 2006, the BC Hydro dataset covers the period 2004 through 2010. More details on this data set can be found in [4]. The SINTEF data allows us to investigate how models perform on the single-meter level, as well as distribution substation (~150 meters).…”
Section: Methodsmentioning
confidence: 99%
“…In Høverstad et al [6], ARIMA methods achieve better results than artificial neural networks. On the other side, Veit et al [10] claim that a neural network performs slightly better than the ARIMA methods.…”
Section: Related Workmentioning
confidence: 98%