NILM- based system for energy monitoring of compound houses in Ghana
Date
2020-05
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Abstract
Compound housing is a housing arrangement that stemmed from cultural family
living settings. Over the years, it has evolved to denote a group of different households that
share a number of utilities including electricity. Electricity bills and payments are a concern
in such living units due to the inability to split bills fairly. Previous work done to solve this
are either expensive, or do not take into consideration the complexity of electricity
connections in such houses. This thesis aims at verifying if the Feedforward Artificial
Neural Network (ANN) can be used to split bills by implementing a Non-Intrusive Load
Monitoring System for Compound Houses in Ghana. The proposed algorithm’s
performance is compared to Hidden Markov Model (HMM) and its variants. It was
discovered that the Feedforward ANN had higher overall performance than the HMM and
its variants, and is efficient for splitting electricity bills in compound houses.
Description
Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Electrical and Electronic Engineering, May 2020
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Senior project
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Keywords
compound houses, Non-Intrusive Load Monitoring (NILM), electricity consumption