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.


This is a publicly available dataset of heating and electricity consumption profiles, aggregated from multiple load profiles of a residential customer. The dataset is gathered between December 2010 and November 2018 with a one-hour time step resolution, thereby containing 70,080 measurements. In addition to the historical energy consumption values, a concatenation of meteorological variables is also included. The weather variables are air pressure, temperature, and humidity plus wind speed and solar irradiation at the predetermined location. 


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.



2021-10-15 Outlier in October data

We have been pointed by a participant (btw, thank you all for your great feedback and input so far) to a large outlier in the recently released October data ( This is likely the explanation why the forecasts seemed not to influence the optimisation much in Phase 1 of the competition. We can confirm that no such outlier is there in the November data, which is the evaluation dataset for Phase 2. So we expect the quality of the forecasts to be more influential in Phase 2.


Last Updated On: 
Thu, 10/14/2021 - 21:00
Citation Author(s): 
Christoph Bergmeir

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.


The data set includes 12 days of power consumption log at a sampling rate of 4 data per second (4Hz). The columns represent the following variables:

  • Voltaje (V)
  • Cirrent (A)
  • Power (W)
  • Frecuency (Hz)
  • Energy (KWh)
  • Power Factor
  • Temperature ESP32 (°C)
  • CPU usage (%)
  • RAM usage (%)

Source code:



A 24-hour of 60 seconds solar PV and load data. 


This dataset contains solar radiation data from Coto Laurel Puerto From May 20,2019 to May 19, 2020. Additional power ramp rate data is provided for seven different methods: Ramp saturation, first order low-pass filter, second order low-pass filter, moving average, exponential moving average, enhanced linear exponential smoothing, and predictive dynamics smoothing.


The data is in .mat format. Please use MATLAB to access to it. Ramp rate data results are in the out.mat file. Daily data is available under the name of each PRRC method.


These datasets collect sensorial information about collaborative robot functioning. We recorded information from two different kinds of robots UR3e and UR10e. This dataset is used for data-driving modeling of the power consumption of cobots. The datasets have the following information: recording time, trajectory ID, joints' positions, joints' velocities, motor currents, motor torques, motor voltages, end effector position, force and momentum exerted to the end effector, current and voltage of the robot.


Supplementary Material


Interleaving three-phase voltage source converters (VSCs) is a popular solution for medium- and high-power applications. In addition to the circulating current, the impact of PWM strategies on the DC-link current ripple is an important issue for practical DC-link capacitor designs, which could affect system reliability and lifetime. Existing studies have been reported to evaluate the impact of conventional pulse width modulation (PWM) strategies such as space vector modulation (SVM), sinusoidal PWM (SPWM), and discontinuous PWM (DPWM).