Power and Energy

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.

 

5442 views
  • Energy
  • Last Updated On: 
    Tue, 01/29/2019 - 00:55

    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.

    2850 views
  • Energy
  • Last Updated On: 
    Thu, 04/11/2019 - 10:58

    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.

    1905 views
  • Power and Energy
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34

    Description of the proposed method is presented with the support of experimental videos.

    34 views
  • Reliability
  • Last Updated On: 
    Sat, 05/30/2020 - 23:39

    Power transmission system losses can typically represent from five to ten percent of the total generation, a quantity worth millions of dollars per year. The purpose of loss allocation in the context of pool dispatch is to assign to each individual generation and load the responsibility of paying for part of the system transmission losses. Since the system losses are non-separable, non-linear functions of the real power generation and loads, the allocation of transmission loss is a challenging and contentious issue in a fully deregulated system.

    76 views
  • Machine Learning
  • Last Updated On: 
    Sat, 05/30/2020 - 09:16

     

     

    In the dataset, there is the electrical transmission system modeled in Simulink. It also contains the codes to generate the data from the model, extract images from data processing (in this case, a continuous wavelet transform), and image processing. Finally, the program to train the network is also provided. All codes are in M-FILE format.

    71 views
  • Artificial Intelligence
  • Last Updated On: 
    Thu, 05/28/2020 - 14:16

    An emission rate-based carbon tax is applied to fossil-fueled generators along with a Smart Grid resource allocation (SGRA) approach. The former reduces the capacity factors (CFs) of base load serving fossil-fueled units, while the latter reduces the CFs of peak load serving units.  The objective is to quantify the integration of the carbon tax and the SGRA approach on CO2 emissions and electricity prices in a multi-area power grid.

    26 views
  • Power and Energy
  • Last Updated On: 
    Fri, 05/22/2020 - 02:29

    Data for 24-node and 54-node test networks for reliability-oriented distribution expansion planning applications.

    33 views
  • Reliability
  • Last Updated On: 
    Thu, 05/21/2020 - 10:47

    This data is related to the paper: "Energy hardware and workload aware job scheduling towards interconnected HPC environments". In includes two energy models for nodes equipped with Intel Gold and Platinum CPUs, and eight application's data, to be used to estimate runtime, energy, and power at different frequencies. For detailed information on the energy model and how to use it, please read the paper.

    First model: 2x Platinum 8168 CPU [2.70GHz-1.20GHz]24C, TDP 205W, 12 x 16GB DDR4 SDRAM

    Second model: 2x Gold 6254 CPU [3.10GHz-1.20GHz] 18C,TDP 200W, 12 x 32GB DDR4 SDRAM

    24 views
  • Power and Energy
  • Last Updated On: 
    Wed, 05/20/2020 - 10:27

    The large variability of system and types of heating load is a feature of the commercial metering of thermal energy. Heating consumption depends on many factors, for example, wall and roof material, floors number, system (opened and closed) etc. The daily data from heating meters in the residential buildings are presented in this dataset for comparing the thermal characteristics. These data are supplemented by floors number, wall material and year of construction, as well as data on average daily outdoor temperatures.

    170 views
  • Energy
  • Last Updated On: 
    Sun, 05/10/2020 - 02:19

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