DOI:10.1007/s40565-016-0258-8 |
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Residential end-uses disaggregation and demand responseevaluation using integral transforms |
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Page view: 0
Net amount: 1551 |
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Author:
Antonio GABALDO´ N1, Roque MOLINA1, Alejandro MARI´N-PARRA1,
Sergio VALERO-VERDU´ 2, Carlos A ´ LVAREZ3
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Author Affiliation:
1. ETS de Ingenierı´a Industrial, Universidad Polite´cnica de
Cartagena, Dr. Fleming s/n, 30202 Cartagena, Spain;
2. EPS de Elche, Universidad Miguel Herna´ndez, Elche, Spain;
3. Institute for Energy Engineering, Universidad Polite´cnica de
Valencia, Valencia, Spain
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Foundation: |
Spanish
Government (Ministerio de Econom?′a, Industria y Competitividad)
and EU FEDER fund (No. ENE2013-48574-C2-2-P&1-P, No.
ENE2015-70032-REDT). |
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Abstract: |
Demand response is a basic tool used to develop
modern power systems and electricity markets. Residential
and commercial segments account for 40%–50% of the
overall electricity demand. These segments need to overcome
major obstacles before they can be included in a
demand response portfolio. The objective of this paper is to
tackle some of the technical barriers and explain how the
potential of enabling technology (smart meters) can be
harnessed, to evaluate the potential of customers for
demand response (end-uses and their behaviors) and,
moreover, to validate customers’ effective response to
market prices or system events by means of non-intrusive
methods. A tool based on the Hilbert transform is improved
herein to identify and characterize the most suitable loads
for the aforesaid purpose, whereby important characteristics
such as cycling frequency, power level and pulse width
are identified. The proposed methodology allows the filtering
of aggregated load according to the amplitudes of
elemental loads, independently of the frequency of their
behaviors that could be altered by internal or external
inputs such as weather or demand response. In this way, the
assessment and verification of customer response can be
improved by solving the problem of load aggregation with
the help of integral transforms. |
Keywords: |
Demand response, Hilbert transform, Load
monitoring, Instantaneous frequency, Aggregation, Smart
meters |
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Online Time:2017/01/09 |
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