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Smart Home Energy Management Based on Renewable Energy Resources
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The energy management system (EMS) can be used to optimize renewable energy resources and to monitor and schedule household appliances to reduce energy cost and Peak-to-Average-Ratio (PAR). This paper presents a smart home EMS with renewable energy sources and energy storage systems and shows how to use/ sell electrical power from/to the main grid (MG). Detailed information about the electricity selling/buying operation and appliances schedule at each hour during the day are shown. The main objective of the system is to reduce the daily cost and PAR and maximize the user’s comfort. The system achieved a reduction in cost by scheduling the appliances and optimizing the renewable and stored energy. Based on the day ahead pricing of electricity and available renewable and stored energy, the appliances are scheduled. The mathematical models of each component in the system and the daily cost, PAR, and user’s comfort functions are built in MATLAB. All constraints of the system are considered. Multi-objective optimization with a genetic algorithm (GA) is used to solve this problem. The EMS with PV renewable energy source and battery energy storage is applied on smart home appliances (shiftable and non-shiftable). The efficiency of the scheduled appliances is measured by the electricity cost. The results show that the system helps to reduce the electricity cost and PAR.
Title: Smart Home Energy Management Based on Renewable Energy Resources
Description:
The energy management system (EMS) can be used to optimize renewable energy resources and to monitor and schedule household appliances to reduce energy cost and Peak-to-Average-Ratio (PAR).
This paper presents a smart home EMS with renewable energy sources and energy storage systems and shows how to use/ sell electrical power from/to the main grid (MG).
Detailed information about the electricity selling/buying operation and appliances schedule at each hour during the day are shown.
The main objective of the system is to reduce the daily cost and PAR and maximize the user’s comfort.
The system achieved a reduction in cost by scheduling the appliances and optimizing the renewable and stored energy.
Based on the day ahead pricing of electricity and available renewable and stored energy, the appliances are scheduled.
The mathematical models of each component in the system and the daily cost, PAR, and user’s comfort functions are built in MATLAB.
All constraints of the system are considered.
Multi-objective optimization with a genetic algorithm (GA) is used to solve this problem.
The EMS with PV renewable energy source and battery energy storage is applied on smart home appliances (shiftable and non-shiftable).
The efficiency of the scheduled appliances is measured by the electricity cost.
The results show that the system helps to reduce the electricity cost and PAR.
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