Synchronizing of Smart Homes in Microgrids using Whale Optimization Algorithm
محورهای موضوعی : مهندسی هوشمند برق
Farhad Nourozi
1
(
Department of Electrical Engineering, Ahrar Institute of Technology and Higher Education, Rasht, Iran
)
Navid Ghardash khani
2
(
Department of Electrical Engineering, Bandar Anzali Branch, Islamic Azad University, Bandar Anzali, Iran
)
کلید واژه: Chaos Whale optimization (CWOA), Distributed Energy Resources (DER), Household Energy Management System (HEMS), Particle Swarm Optimization (PSO), Renewable Energy Systems (RES), Smart time Scheduling (SS),
چکیده مقاله :
The household energy management system (HEMS) can optimally schedule home appliances for transferring loads from peak to off-peak times. Consumers of smart houses have HEM, renewable energy sources and storage systems to reduce the bill. In this article, a new HEM model based on the time of usage pricing planning with renewable energy systems is proposed to use the energy more efficiently. The new meta-heuristic whale optimization algorithm (WOA) and the common meta-heuristic of particle swarm optimization (PSO) are used to achieve that. To improve the performance, a mapping chaos theory (CWOA) is proposed. Also, an independent solar energy source is used as a support of the microgrid to achieve a better performance. It is concluded that the energy saving achieved by the proposed algorithm is able to decrease the electricity bill by about 40-50% rather than the WOA and PSO methods. The proposed system is simulated in MATLAB environment.
The household energy management system (HEMS) can optimally schedule home appliances for transferring loads from peak to off-peak times. Consumers of smart houses have HEM, renewable energy sources and storage systems to reduce the bill. In this article, a new HEM model based on the time of usage pricing planning with renewable energy systems is proposed to use the energy more efficiently. The new meta-heuristic whale optimization algorithm (WOA) and the common meta-heuristic of particle swarm optimization (PSO) are used to achieve that. To improve the performance, a mapping chaos theory (CWOA) is proposed. Also, an independent solar energy source is used as a support of the microgrid to achieve a better performance. It is concluded that the energy saving achieved by the proposed algorithm is able to decrease the electricity bill by about 40-50% rather than the WOA and PSO methods. The proposed system is simulated in MATLAB environment.
