A Smart Home Energy Management System Using Two-Stage Non-Intrusive Appliance Load Monitoring over Fog-Cloud...

Area of Science:

• Electrical Engineering
• Computer Science
• Energy Systems

Background:

• Electricity is crucial for modern society, necessitating effective demand-side management (DSM) in smart grids.
• Non-intrusive appliance load monitoring (NIALM) offers a way to monitor energy consumption without individual appliance meters.
• Fog (edge) computing enhances IoT data processing by distributing computation closer to data sources.

Purpose of the Study:

• To develop and evaluate a Smart Home Energy Management System (SHEMS) prototype integrated with fog-cloud computing.
• To investigate the application of Non-Intrusive Appliance Load Monitoring (NIALM) within this fog-cloud enabled SHEMS.
• To demonstrate a feasible and usable NIALM approach for residential demand-side management.

Main Methods:

• Established a Smart HEMS prototype using Tridium's Niagara Framework over fog-cloud architecture.
• Implemented a two-stage, artificial neural network-based NIALM approach for appliance monitoring.
• Utilized a compact, embedded IoT controller as the core gateway for device connectivity and data management.

Main Results:

• The developed SHEMS prototype successfully integrated NIALM within a fog-cloud computing environment.
• The two-stage NIALM approach enabled non-intrusive monitoring of electrical appliances without requiring smart plugs.
• The system demonstrated feasibility and usability for residential demand-side management applications.

Conclusions:

• The proposed Smart HEMS prototype, leveraging fog-cloud computing and NIALM, is a viable solution for modern energy management.
• This approach provides an effective method for appliance monitoring and supports residential DSM strategies.
• The integration of NIALM as an IoT application within the SHEMS framework enhances smart grid capabilities.