Abstract
The research paper presents a single-stage solar photovoltaic battery grid-tied system with a simple phase-locked loop which needs less control to operate. The system losses are decreased because of the exclusion of boost converter and addition of a storage battery. Earlier, many other techniques were implemented to extract maximum power from the solar panels such as incremental conductance (InCond) and perturb and observe (P and O). Now, the maximum power is being tried to be extracted by using the artificial intelligence’s artificial neural network (ANN) technique. Tests results for the system operations are studied from doing the simulations of the proposed model. The operation conducts on two modes, i.e., fixed power and variable power in compliance with IEEE-519 standards. The power given as input to the grid is fixed during mode 1 and varies during mode 2. It is very essential to extract maximum power from the solar panels by increasing the efficiency, reducing the losses, and evading any possible faults. Hence, Simulink model of solar PV system using the artificial neural network is being built and simulated. The obtained results are observed and analyzed in the research paper.
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Singh, M., Singh, O., M.A.Ansari, Singh, V. (2022). Simulation and Analysis of Single-Stage Grid-Connected Solar PV System Using ANN. In: Tripathi, A., Soni, A., Shrivastava, A., Swarnkar, A., Sahariya, J. (eds) Intelligent Computing Techniques for Smart Energy Systems. Lecture Notes in Electrical Engineering, vol 862. Springer, Singapore. https://doi.org/10.1007/978-981-19-0252-9_34
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