Title

Pico-Micro Grid Power Management Energy Systems

Location

Presentation- Allen E. Paulson College of Engineering and Computing

Document Type and Release Option

Thesis Presentation (Restricted to Georgia Southern)

Faculty Mentor

Rami Haddad

Faculty Mentor Email

rhaddad@georgiasouthern.edu

Presentation Year

2021

Start Date

26-4-2021 12:00 AM

End Date

30-4-2021 12:00 AM

Keywords

Pico-micro grid, electronics, energy consumption, device identification

Description

Technology continues to improve, and people buy more electronics day by day. Therefore, something very important is to be smart about how much energy one uses. Being smart about how one uses electricity can decrease their environmental footprint and decrease their electric bill. Therefore, the Pico-Micro Grid Power Energy Management System (PEMS) is an important tool that will help one to monitor how much energy they are using as well as how they are using it. In order to monitor how much energy each device is consuming, identifying the device is vital. This project focuses on finding the best method to use in order to identify a device. Some methods explored are a single large ANN, applying principal component analysis (PCA) with different methods, and a Bi-directional Long Short-Term Memory (Bi-LSTM) network. The best method is found to be the Bi-LSTM network, once this was discovered, tests were ran for five different devices and the resulting data for each device was collected and verified the findings that the best method of classification is through the use of a Bi-LSTM network.

Academic Unit

Allen E. Paulson College of Engineering and Computing

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Apr 26th, 12:00 AM Apr 30th, 12:00 AM

Pico-Micro Grid Power Management Energy Systems

Presentation- Allen E. Paulson College of Engineering and Computing

Technology continues to improve, and people buy more electronics day by day. Therefore, something very important is to be smart about how much energy one uses. Being smart about how one uses electricity can decrease their environmental footprint and decrease their electric bill. Therefore, the Pico-Micro Grid Power Energy Management System (PEMS) is an important tool that will help one to monitor how much energy they are using as well as how they are using it. In order to monitor how much energy each device is consuming, identifying the device is vital. This project focuses on finding the best method to use in order to identify a device. Some methods explored are a single large ANN, applying principal component analysis (PCA) with different methods, and a Bi-directional Long Short-Term Memory (Bi-LSTM) network. The best method is found to be the Bi-LSTM network, once this was discovered, tests were ran for five different devices and the resulting data for each device was collected and verified the findings that the best method of classification is through the use of a Bi-LSTM network.