A Home Energy Management System with Renewable Energy and Energy Storage Utilizing Main Grid and Electricity Selling

• Published in: IEEE access Vol. 8; p. 1
• Main Authors: Dinh, Huy Truong, Yun, Jaeseok, Kim, Dong Min, Lee, Kyu-Haeng, Kim, Daehee
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Alternative energy sources; Convergence; day-ahead price; Electricity; electricity selling; Energy costs; Energy management; Energy management systems; Energy storage; energy storage systems; Home energy management systems; Houses; meta-heuristic algorithms; Meteorology; Multiple objective analysis; New technology; Optimization; Particle swarm optimization; Peak to average power ratio; Renewable energy sources; Renewable resources; Residential energy; Schedules; Storage systems
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.2979189

With the development of new technologies in the field of renewable energy and batteries, increasing number of houses have been equipped with renewable energy sources (RES) and energy storage systems (ESS) to reduce home energy cost. These houses usually have home energy management systems (HEMS) to control and schedule every electrical device. Various studies have been conducted on HEMS and optimization algorithms for energy cost and peak-to-average ratio (PAR) reduction. However, none of papers give a sufficient study on the utilization of main grid's electricity and selling electricity. In this paper, firstly, we propose a new HEMS architecture with RES and ESS where we take utilization of the electricity of the main grid and electricity selling into account. With the proposed HEMS, we build general mathematical formulas for energy cost and PAR during a day. We then optimize these formulas using both the particle swarm optimization (PSO) and the binary particle swarm optimization (BPSO). Results clearly show that, with our HEMS system, RES and ESS can help to drop home energy cost significantly to 19.7%, compared with the results of previous works. By increasing charge/discharge rate of ESS, energy cost can be decreased by 4.3% for 0.6 kW and 8.5% for 0.9 kW. Moreover, by using multi-objective optimization, our system can achieve better PAR with an acceptable energy cost.