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Renewable Hybrid Battery Energy Management System Using ANN Controller

EasyChair Preprint no. 4546

7 pagesDate: November 11, 2020


Renewable energy sources are major focus in power system areas for new researchers.  Recently many power plants are being established based on these sources.  Integration of solar and wind energy-based power plants are common. In this paper variable DC motor load connected with wind and solar power-based hybrid power system is described. To enhance the utilization of these energy sources as per demand load, battery bank-based energy storage system is used to handle the excess power generation. The switching control is required to route the power through battery bank in the condition of excess power generation. Many researchers have proposed the control strategy based on PI control, fuzzy control etc. for switching control in this case. Adaptive Control system with added intelligence is proposed in this paper for controlling the excessive power control.  With the time, multiple battery bank and more sources can be connected to the power system. The adaptability in control system helps to reconfiguration itself based on the training from the desired signals. Artificial Neural Network based controller has been proposed here. The training results and results of the handling the excessive power during simulation are described in the result section of the paper

Keyphrases: ANN controller, power system, renewable energy, Solar system, wind power

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Animesh Masih and H K Verma},
  title = {Renewable Hybrid Battery Energy Management System Using ANN Controller},
  howpublished = {EasyChair Preprint no. 4546},

  year = {EasyChair, 2020}}
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