EFFICIENT MAXIMUM POWER POINT ESTIMATION MONITORING OF PHOTOVOLTAIC USING FEED FORWARD NEURAL NETWORK

  • Hasnira Hasnira Politeknik Negeri Batam
  • Novie Ayub Windarko Politeknik Elektronika Negeri Surabaya
  • Anang Tjahjono Politeknik Elektronika Negeri Surabaya
  • Mochammad Ari Bagus Nugroho Politeknik Elektronika Negeri Surabaya
  • Mentari Putri Jati Politeknik Elektronika Negeri Surabaya

Abstract

The development of the utilization of solar panels in the future will continue to increase. One characteristic form of solar panels is the I-V curve which can be used to analyze the amount of solar panel output power. By knowing the I-V curve, we can get Maximum Power Point Estimation (MPPE) value that can be supported by solar panels. Information about the estimated value of the maximum solar panel power is an important part in determining the loading capacity, while maintaining the life of the equipment used. Feed Forward Neural Network with Back Propagation Algorithm (FFBP) has proven to be able to provide MPPE value information on solar panel output. The input values ​​in ANN are the voltage and current of the solar panel, while the output of ANN is in the form of an estimated power value. MPPE simulation results obtained an average error of 0.04 points between actual power (MPP) and estimated power (MPPE).

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Published
2020-10-31