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Solar panels simulation data generated using LTSpice under different operating conditions.

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  • 1Department of Computer Science, California State University, Fullerton, CA 92831, United States.

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|September 27, 2022
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This study details solar panel circuit simulation data generated using LTspice and Python. The data, organized in CSV files, aids in evaluating photovoltaic module performance.

Keywords:
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Area of Science:

  • Electrical Engineering
  • Renewable Energy Systems
  • Materials Science

Background:

  • Accurate simulation of photovoltaic (PV) systems is crucial for efficient solar energy integration.
  • Standardized data representation facilitates the analysis and comparison of different PV module configurations.
  • LTspice and Python offer powerful tools for circuit simulation and data generation.

Purpose of the Study:

  • To present a comprehensive dataset of solar panel circuit simulations.
  • To detail the methodology for automated data generation and organization.
  • To provide a resource for evaluating photovoltaic module performance.

Main Methods:

  • Utilizing LTspice for high-performance SPICE simulations of PV circuits.
  • Employing automated Python scripts for generating and simulating PV cell configurations.
  • Organizing simulation data, including cell voltage and current, into CSV files.

Main Results:

  • Generated detailed circuit simulation data for various photovoltaic module configurations.
  • Successfully automated the creation and simulation process of PV cells.
  • Collected and organized data in a structured CSV format for accessibility.

Conclusions:

  • The presented dataset and methodology streamline the evaluation of photovoltaic modules.
  • This work provides a valuable resource for researchers and engineers in solar energy.
  • The automated approach enhances the efficiency of PV system analysis.