Abstract

Electricity is a very important need for daily life. It began to be developed and researched additional energy in the form of renewable energy sources, such as the utilization of solar energy using photovoltaic (PV). The utilization of solar energy in PV can be connected to the grid. For that, we need a stable performance that grid usage can be reduced. So we use Battery Energy Storage (BES). The role of the Energy Management System (EMS) is needed to determine the charge/discharge of battery and strategies to minimize grid power. The proposed research carried out an EMS on a system consisting of PV, BES, and load. First is predicting PV output power using Artificial Neural Network (ANN) by considering the parameters of irradiance, temperature, and time. Second, it is considering battery State-Of-Charge (SOC). The battery is kept at the minimum and maximum SOC limits to maintain the battery. These two parameters become the input of EMS. EMS using ANN to determine charge/discharge of the battery and minimize grid power usage by determining load usage. This research was simulated using MATLAB Simulink. EMS uses ANN then compared with results of EMS with the rule-base algorithm.

Original languageEnglish
Title of host publicationProceedings - 2020 International Seminar on Intelligent Technology and Its Application
Subtitle of host publicationHumanification of Reliable Intelligent Systems, ISITIA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages357-362
Number of pages6
ISBN (Electronic)9781728174136
DOIs
Publication statusPublished - Jul 2020
Event2020 International Seminar on Intelligent Technology and Its Application, ISITIA 2020 - Virtual, Online, Indonesia
Duration: 22 Jul 202023 Jul 2020

Publication series

NameProceedings - 2020 International Seminar on Intelligent Technology and Its Application: Humanification of Reliable Intelligent Systems, ISITIA 2020

Conference

Conference2020 International Seminar on Intelligent Technology and Its Application, ISITIA 2020
Country/TerritoryIndonesia
CityVirtual, Online
Period22/07/2023/07/20

Keywords

  • ANN
  • ANN prediction
  • BES
  • Battery SOC
  • EMS

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