Abstract
© 2017 IEEE. This work presents techniques for obtaining a reliable electrical load-curve based on comparative analysis between the different compressed sensing algorithms. Therefore, the goal is implementing compressed sensing (CS) when a wireless heterogeneous network, that exchanges information between electrical enterprise and smart meters, has a fault. Then, the data cannot be sent totally, and we would have the data only of some smart meters; thus, using the adequate technique of compressed sensing is possible to the reconstruction of load-curve required for generating demand response (DR) with the minimum error. In the advanced metering infrastructure (AMI) there may be communication faults; then, it is necessary to have other forms for estimating the demand response using few measurements. In addition, using a dictionary based on the DCT transform does not mean that the sea is the best option for the representation of a signal. For example, among other results, in this work we obtain an average of percent root mean square difference nearest to the 5% in relation with a Gaussian function or Wavelet basis with values between 1.4 and 1.7% average PRD.
Translated title of the contribution | Reconstrucción de la curva de carga eléctrica requerida para la respuesta a la demanda utilizando técnicas de detección comprimidas |
---|---|
Original language | English (US) |
Pages | 1-6 |
Number of pages | 6 |
DOIs | |
State | Published - 1 Dec 2017 |
Event | 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017 - Quito, Ecuador Duration: 20 Sep 2017 → 22 Sep 2017 |
Conference
Conference | 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, ISGT Latin America 2017 |
---|---|
Abbreviated title | ISGT Latin America 2017 |
Country/Territory | Ecuador |
City | Quito |
Period | 20/09/17 → 22/09/17 |