Non-Intrusive Similar Loads Identification

Non-Intrusive Similar Loads Identification

Citation Author(s):
Aloisio
Paixao
IFES
Wanderley
Celeste
DCEL/UFES
Luis
Rigo Jr.
DCEL/UFES
Daniel
Coura
DCEL/UFES
Helder
Rocha
DEL/UFES
Leonardo
Silvestre
DCEL/UFES
Silvia
Rissino
DCEL/UFES
Submitted by:
Luis Rigo Jr
Last updated:
Wed, 06/19/2019 - 15:21
DOI:
10.21227/mynq-a588
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Dataset Views:
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Abstract: 

This data set is composed by samples of load signature of electric devices acquired on a non-intrusively form. The test-bench was performed using four identical fluorescent lamps, four identical slots and four identical switches. Identical term means the same technical specifications (nominal voltage, power, isolation voltage, among others). The sensors are connected to the power supply in order to measure the electrical variations when appliances are turned on/off. We have 16 possible network configurations with 4 appliances, in which one, two, three or four appliances can be turned on. For each configuration, the acquisition of 150 samples was performed in four ways, i. e., 5, 10, 15 and 20 minutes after setting a new configuration, in order to increase the probability of obtaining a more heterogeneous set of samples.

Instructions: 

This database has 2400 samples. Each line is a feature vector represent a sample, composed by:- Active power (P);- Reactive power (Q);- Apparent power (S);- Power factor (FP);- Effective current (Irms);- 1st harmonic component;- 3rd harmonics component;- 5th harmonics component;- 7th harmonics component;- 9th harmonics component;- 11th harmonics component;- 13th harmonics component;- 15th harmonics component;- 17th harmonics component;- Class;- Sample weight.

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[1] Aloisio Paixao, Wanderley Celeste, Luis Rigo Jr., Daniel Coura, Helder Rocha, Leonardo Silvestre, Silvia Rissino, "Non-Intrusive Similar Loads Identification", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/mynq-a588. Accessed: Oct. 16, 2019.
@data{mynq-a588-19,
doi = {10.21227/mynq-a588},
url = {http://dx.doi.org/10.21227/mynq-a588},
author = {Aloisio Paixao; Wanderley Celeste; Luis Rigo Jr.; Daniel Coura; Helder Rocha; Leonardo Silvestre; Silvia Rissino },
publisher = {IEEE Dataport},
title = {Non-Intrusive Similar Loads Identification},
year = {2019} }
TY - DATA
T1 - Non-Intrusive Similar Loads Identification
AU - Aloisio Paixao; Wanderley Celeste; Luis Rigo Jr.; Daniel Coura; Helder Rocha; Leonardo Silvestre; Silvia Rissino
PY - 2019
PB - IEEE Dataport
UR - 10.21227/mynq-a588
ER -
Aloisio Paixao, Wanderley Celeste, Luis Rigo Jr., Daniel Coura, Helder Rocha, Leonardo Silvestre, Silvia Rissino. (2019). Non-Intrusive Similar Loads Identification. IEEE Dataport. http://dx.doi.org/10.21227/mynq-a588
Aloisio Paixao, Wanderley Celeste, Luis Rigo Jr., Daniel Coura, Helder Rocha, Leonardo Silvestre, Silvia Rissino, 2019. Non-Intrusive Similar Loads Identification. Available at: http://dx.doi.org/10.21227/mynq-a588.
Aloisio Paixao, Wanderley Celeste, Luis Rigo Jr., Daniel Coura, Helder Rocha, Leonardo Silvestre, Silvia Rissino. (2019). "Non-Intrusive Similar Loads Identification." Web.
1. Aloisio Paixao, Wanderley Celeste, Luis Rigo Jr., Daniel Coura, Helder Rocha, Leonardo Silvestre, Silvia Rissino. Non-Intrusive Similar Loads Identification [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/mynq-a588
Aloisio Paixao, Wanderley Celeste, Luis Rigo Jr., Daniel Coura, Helder Rocha, Leonardo Silvestre, Silvia Rissino. "Non-Intrusive Similar Loads Identification." doi: 10.21227/mynq-a588