1016 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 14, NO. 3, MARCH 2018 Hybrid Approach Based on GA and PSO for Parameter Estimation of a Full Power Quality Disturbance Parameterized Model Marco Antonio Rodriguez-Guerrero, Arturo Y. Jaen-Cuellar, Rene D. Carranza-Lopez-Padilla, Member, IEEE, Roque A. Osornio-Rios, Member, IEEE, Gilberto Herrera-Ruiz , and Rene de J. Romero-Troncoso , Senior Member, IEEE Abstract—Power quality (PQ) and PQ disturbances (PQD) are relevant for the industry due to the implied costs in most industrial processes. Besides, it is necessary to maintain the quality standards of the electrical grid to avoid damages in the equipment that is connected to the grid. Due to the nature and characteristics of the PQD present in the volt- age and current signals, several studies have focused on detecting and classifying particular disturbances, or sim- ple combinations between two or three of them, without presenting a methodology that describes all of them au- tomatically. Hence, this paper proposes a hybrid approach integrating genetic algorithms (GA) and particle swarm opti- mization (PSO) with other techniques that make use of their individual capabilities to automatically find a wide range of PQD present in a voltage or current signal, regardless of their nature. To achieve this hybrid approach parameteriza- tion, a full PQD model is adopted to automate the search of every one of their parameters. The proposed approach is validated through synthetic signals, real data from the IEEE data base, and through data readings from a real process. A comparison using other recent heuristic techniques is made to show the robustness of the proposed hybrid approach. Index Terms—Genetic algorithms (GA), heuristic algo- rithms, parameter estimation, particle swarm optimization (PSO), power quality (PQ). Manuscript received March 6, 2017; revised June 11, 2017 and July 31, 2017; accepted August 15, 2017. Date of publication August 24, 2017; date of current version March 1, 2018. This work was sup- ported in part by FOMIX QUERETARO-2014-C03-250269, in part by SEP-CONACyT 222453-2013, and in part by DAIP grant 733/2016, Uni- versidad de Guanajuato. Paper no. TII-17-0319. (Corresponding author: Rene de J. Romero-Troncoso.) M. A. Rodriguez-Guerrero and R. D. Carranza-Lopez-Padilla are with the Centro Nacional de Metrolog´ ıa, El Marqu´ es 76246, Mexico (e-mail: mrodrigu@cenam.mx; rcarranz@cenam.mx). A. Y. Jaen-Cuellar, R. A. Osornio-Rios, and G. Herrera-Ruiz are with the HSPdigital–CA Mecatr ´ onica, Facultad de Ingenier´ ıa, Universidad Aut ´ onoma de Quer ´ etaro, San Juan del R´ ıo 76807, Mexico (e-mail: ayjaen@hspdigital.org; Member raosornio@hspdigital.org; gherrera@ uaq.mx). R. de J. Romero-Troncoso is with the HSPdigital–CA Telem´ atica, DI- CIS, Universidad de Guanajuato, Salamanca 36700, Mexico (e-mail: troncoso@hspdigital.org). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TII.2017.2743762 I. INTRODUCTION P OWER quality (PQ) has been a major topic for research due to the relevance in energy generation and distribution [1], [2]. The capabilities in detecting and measuring the power abnormalities are useful to determine how electric equipment is affected by the electric grid contents and by the actions that can be taken to keep the source as pure as possible [3]–[5]. The PQ analysis is recently a major research topic due to the integration of renewable energy sources as well as the increasing adoption of distributed generation in power systems, especially in distri- bution networks [6], [7]. This scenario represents new technical problems for the utilities and researchers worldwide. There are challenges in PQ issues such as modeling, detecting, classifying, monitoring, or measuring disturbances in power systems. The technical issues are typically separated by the nature of the PQ event, i.e., sags and swells [8], [9], harmonics [10]–[12], tran- sients [13], [14], small angle phase measurements [15], flicker [16], etc. Studies in PQ still represent an area of opportunity since PQ detection and classification is performed through a wide variety of methodologies; as a result, several models have been proposed [17], [18]. Besides, the abnormalities present in the electric grid, known as PQ disturbances (PQD), are treated as separated phenomena or mostly as a combination of some of them [19]. Even when considering a generalized paramet- ric model that represents most of the PQD, which is so far the most complete that has been reported, this model contains very complex analytical expressions [20]. In the last years, several relevant works dealing with the PQ analysis have been presented using different approaches. A power disturbance is considered as any behavior that differs from a specified signal, typically a pure sine waveform [21]; consequently, a number of works are focused on the detection and classification of PQD. For instance, in [22], a pattern recog- nition scheme is used as an intelligent method to provide feature information of the input signal; however, only combinations of voltage sag/swell with harmonic content are considered. In the meantime, in [23], heuristic algorithms and space transform methods are used in the classification of single and combined PQD, but mostly only combinations of two electric events are considered. The proposed approach was validated by simulation, but no modeling of the disturbances is presented. Regarding the 1551-3203 © 2017 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications standards/publications/rights/index.html for more information.