The dataset contains fundamental approaches regarding modeling individual photovoltaic (PV) solar cells, panels and combines into array and how to use experimental test data as typical curves to generate a mathematical model for a PV solar panel or array.

The work starts with a short overview of grid requirements for photovoltaic (PV) systems and control structures of grid-connected PV power systems. Advanced control strategies for PV power systems are presented next, to enhance the integration of this technology. The aim of this work is to investigate the response of the three-phase PV systems during symmetrical and asymmetrical grid faults.

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.

This dataset was used to quantify the effects of environmental change on SSTDR measurements from solar panels. We collect illuminance (Lux), temperature (deg F), and humidity (%) alongside SSTDR waveforms on a fault free string. Data is collected once per minute in January 2020, and twice per minute in August-September 2020. 

This Dataset, as a Matlab script, shows input voltages vectors and output voltage reference vector for improved control of input power factor in Multiphase Conventional Matrix Converters (MCMC) using the transfer function of the load angle. Compared to the direct space--vector modulation techniques, the proposed solution can rely on the load parameters and obtain the greater value of an input displacement angle in a certain range of voltage transfer ratio and the load power factor.

The heating and electricity consumption data are the results of an energy audit program aggregated for multiple load profiles of a residential customer. These profiles include HVAC systems loads, convenience power, elevator, etc. The datasets are gathered between December 2010 and November 2018 with a one-hour timestep resolution, thereby containing 140,160 measurements, half of which is for heat or electricity. In addition to the historical energy consumption values, a concatenation of weather variables is also available.

MATLAB scripts to generate the Markov models of three-level and four-level ANPC legs and compute their mean time to failure from these models.

An efficient artificial scenerio generator for EV load simulation modeling has been developed acquiring probabilistic method for characterizing the stochastic nature of EVs and generate the schedule of EVs charging to ultimately achieve the EV load profile for impact study of EVs on distribution network. Model has been tested under different settings and by generating different scenarios to make it  viable, realistic and adaptable to any defined characteristics.

This dataset includes the monitoring of energy consumption of a Data Server that is working in the facilities of the Information Technology Center (CTI) of the Escuela Superior Politecnica del Litoral (ESPOL). The data acquisition equipment was implemented in the Electronic Prototype Development Matter of the Faculty of Electrical Engineering and Computing (FIEC), based on the ESP32 hardware.