SPLTRAK Abstract Submission
ANN-based Internet of Home Energy Management System Integrated with Solar PV System
Md. Rokonuzzaman1, Mahmuda K. Mishu1, Kazi S Rahman2, Wen-Shan Tan3, Jagadeesh Pasupuleti1, Nowshad Amin1
1Universiti Tenaga Nasional (@The National Energy University), Kajang, Malaysia
/2Universiti Kebangsaan Malaysia, Bangi, Malaysia
/3Monash University Malaysia, Kuala Lumpur, Malaysia

In this paper, an artificial neural network (ANN) based Internet of home energy management system (IoHEMS) is developed and integrated with the grid-connected solar photovoltaic (PV) system. The proposed IoHEMS can take responsibility for the transition by supervisory control and data acquisition with the smart grid concept. The developed system incorporates conventional power frameworks with data, sensors, advanced metering infrastructure (AMI) and empowers bi-directional correspondence among utility and consumers. The Levenberg-Marquardt (LM) algorithm is implemented with 1000 real-time PV plant data and shows the error of -0.0000027 with the regression value of 1. Seventy percent of data is used to train the IoHEMS, 15% data to test, and 15% to validate the model.