intelligent database systems lab advisor : dr.hsu graduate : keng-wei chang author :...
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Intelligent Database Systems Lab
Advisor : Dr.Hsu
Graduate : Keng-Wei Chang
Author : Gianfranco Chicco, Roberto Napoli
Federico Piglione, Petru Postolache Mircea Scutariu, Cornel Toader
國立雲林科技大學National Yunlin University of Science and Technology
Load Pattern-Based Classification of
Electricity Customers
IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 19, NO.2 ,MAY 2004
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Outline
Motivation Objective Introduction Classification Tools and Models Classification Adequacy Assessment Application of The Classification Techniques Performance Comparisons Concluding Remarks
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Motivation consumption patterns for electricity providers
in competitive electricity markets setting up new tariff structures more closely to
the actual cost in different time periods
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Objective accurate knowledge of the customer’s
consumption patterns represents
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Introduction face new challenges in providing satisfactory
service to customers set up new tariff structures survey two classes of tools
Modified Follow-The –Leader Algorithm Self-organizing maps (SOM)
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Classification Tools and Models rescale or resort related definition
Two clustering tools Modified Follow-The-Leader Algorithm SOM Approach
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KkrRtiverepresentaclass
ncomputerpatternloadtiverepresenta
ncontaineachclusterKkLL
MmlLcustomersofsetthe
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Modified Follow-The-Leader Algorithm
unsupervised clustering algorithm, not require initialization of the number of clusters and computes the cluster centers automatically
is the variance of the hth feature of all the load patterns in the population
is the average value of the variance for h=1,…,H
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SOM Approach unsupervised neural network, projects a H-
dimensional data set into a reduced dimension space
related definition N1 x N2 H-dimensional units ck, a competitive layer ||xi – ck||, activation function not only the winning unit, but also its neighbor
units
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SOM Approach Update the generic unit ck
is the learning rate
is the value of the neighborhood function referred to the generic unit k
w, the identifier of the winning unit
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Classification Adequacy Assessment
General Outline and Definition of the Distances
Adequacy Measures
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1) the distance between two load patterns
2) the distance between a representative load curve and subset , as the geometric mean
General Outline and Definition of the Distances
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Separated and compact1) the mean index adequacy (MIA)
2) the clustering dispersion indicator (CDI)
Adequacy MeasuresN.Y.U.S.T.
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Application of The Classification Techniques
Customers of the Romanian national electricity distribution company 234 customers Over three-week time intervals Contain industrial, services, and small-business
two application Application of the Modified Follow-The-Leader
Algorithm Application of the SOM
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Application of the Modified Follow-The-Leader Algorithm
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p = 2.266, k = 16
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Application of the Modified Follow-The-Leader Algorithm
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Application of the Modified Follow-The-Leader Algorithm
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Application of the SOM Average distance from each example of the data set to its
winning units
Distortion of the map as the percentage of samples for which the winning unit and the second winning unit are not neighboring map units
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Application of the SOMN.Y.U.S.T.
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Application of the SOMN.Y.U.S.T.
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MnRM / resolution property
NnRN / degree of utilization of the map
M : population
N : N1 X N2
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Application of the SOMN.Y.U.S.T.
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Application of the SOMN.Y.U.S.T.
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Performance ComparisonsN.Y.U.S.T.
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Performance ComparisonsN.Y.U.S.T.
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Concluding Remarks both can effectively assist the customer
classification Suggest using them in a way depending on the
objectives
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Review Two clustering tools
Modified Follow-The-Leader Algorithm SOM Approach
Classification Adequacy Assessment Application of The Classification Techniques Performance Comparisons
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Personal opinion …
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