The distributed generation, along with the deregulation of the Smart Grid, have created a great concern on Power Quality (PQ), as it has a direct impact on utilities and customers, as well as effects on the sinusoidal signal of the power line. The a priori unknown features of the distributed energy resources (DER) introduce non-linear behaviours in loads associated to a variety of PQ disturbances. The aim of the database consists of providing the researchers with a collection of the most common power quality disturbance, real-life sag events, to test experiments and measurement instruments (according the UNE-IEC 61000-4-11: 2005). The dataset provides signals recordings from the power network of the University of Cádiz during the last five years (electrical network according to the UNE-EN-50160: 2011).

One of the main advantages of the dataset it is offer a diversity of real sag events (with a duration off less than 3 seconds) in order to test the performance of the instruments. The signals has been designed from the basis of representative single-isolated events for a network of 50Hz with a sampling frequency of 20 kHz (400 samples per cycle).

The dataset is used as the experimental analysis subject of the interdisciplinary project TEC2016− 77632 − C3 − 3 – R 358 - COntrol and Management of Isolable NanoGrids: Smart Instruments for Solar forecasting and Energy Monitoring (COMING-SISEM), supported by the Spanish Ministry of Economy, Industry and Competitiveness in the work flow of the State Plan of Excellency and Challenges for Research (https://www.researchgate.net/project/COntrol-and-Management-of-Isolable-NanoGrids-Smart-Instruments-for-Solar-Forecasting-and-Energy-Monitoring-COMING-SISEM-TEC2016-77632-C3-3-R). The project involve the development of new measurement techniques applied to monitor the Power Quality in micro-grids.


References power quality

[1]  Agustín Agüera-Pérez a, José Carlos Palomares-Salas, Juan-José González-de-la-Rosa José María Sierra-Fernández, Daniel Ayora-Sedeño, Antonio Moreno-Muñoz. Characterization of electrical sags and swells using higher-order statistical estimators. Measurement (Ed. Elsevier) 44 (2011) 1453–1460. ISSN 02632241. https://doi.org/10.1016/j.measurement.2011.05.014

[2]  Juan-José González de la Rosa, A. Agüera-Pérez, J. C. P. Salas, J. M. Sierra-Fernández, A. Moreno-Muñoz, A novel virtual instrument for power quality surveillance based in higher-order statistics and case-based reasoning, Measurement (Ed. Elsevier) 45 (Issue 7) (2012) 18241835. https://doi.org/10.1016/j.measurement.2012.03.036

[3] Olivia Florencias-Oliveros, Agustín Agüera-Pérez, Juan-José González de la Rosa, José-Carlos Palomares-Salas, José-María Sierra-Fernández. A novel instrument for power quality monitoring based in higher-order statistics: a dynamic triggering index for the smart grid. RE&PQJ-15, ISSN 2172-038 X, No.15 April 2017. https://doi.org/10.24084/repqj15.212

 [4] J.M. Sierra-Fernández, Juan-José González de la Rosa, A. Agüera-Pérez, J.C. Palomares Salas, O. Florencias- Oliveros. Evaluation of a new Power Quality index, based in Higher Order Statistics. RE&PQJ-15, ISSN 2172-038 X, No.15 April 2017. https://doi.org/10.24084/repqj15.210


In order to facilitate download the registers, we group the signals in a ZIP file:


·         Sag events.zip [5.25 MB]


The registers are identified according their characteristics: type of event, date and time. Each folder related to voltage characteristics has a file identifier as META.txt, which contains the sampling frequency. For each recording a txt file and a jpg image have been added, for an easier 


Dear Author,


i want to download, your data to test my Algorithm. Could you supply it for me? 



Best Regards


Submitted by yuan wang on Mon, 06/15/2020 - 22:45








Submitted by kai wei on Mon, 06/22/2020 - 22:42