ANN for Optimal Operation of BESS in a Grid Integrated Wind Farm

Diotama, Evando and Irnawan, Roni and Putranto, Lesnanto Multa and Sarjiya, Sarjiya (2020) ANN for Optimal Operation of BESS in a Grid Integrated Wind Farm. In: 1st FORTEI-International Conference on Electrical Engineering, FORTEI-ICEE 2020 Virtual, Bandung 23 September 2020.

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Abstract

The combination of windfarm and battery energy storage system (BESS) can be developed massively by the fact that many countries are planning to add more penetrations to the grid system in large scale. In large scale capacity, fluctuation of renewable energy resource might increase the loss of a system. That problem is also affected by the state of charge (SOC) of battery. The objective of this paper is to simulate the load flow and optimize the BESS operation using python integrated with DIgSILENT PowerFactory. Further, we compare the system power losses of three cases, i.e.: the system that is only supported by windfarm, adding BESS to the system and optimizing BESS operation. The optimization of BESS operation is done by using ANN (Artificial Neural Network). The optimized BESS operation reduced the average system power losses by 13 from the system that only utilizes windfarm. © 2020 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Cited by: 0; Conference name: 1st FORTEI-International Conference on Electrical Engineering, FORTEI-ICEE 2020; Conference date: 23 September 2020 through 24 September 2020; Conference code: 165502
Uncontrolled Keywords: wind farm, battery energy storage system, digsilent powerfactory, optimization, state of charge, artificial neural network, losses
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering > Electrical and Information Technology Department
Depositing User: Sri JUNANDI
Date Deposited: 06 May 2025 07:36
Last Modified: 06 May 2025 07:36
URI: https://ir.lib.ugm.ac.id/id/eprint/16727

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