Abstract
In this study, we investigate the operation of an optimal home energy management system (HEMS) with integrated renewable energy system (RES) and energy storage system (ESS) supporting electricity selling functions. A multi-objective mixed integer nonlinear programming model, including RES, ESS, home appliances and the main grid, is proposed to optimize different and conflicting objectives which are energy cost, user comfort and PAR. The effect of different selling prices on the objectives is also considered in detail. We further develop a formula for the lower bound of energy cost to help residents or engineers quickly choose best parameters of RES and ESS for their homes during the installation process. The performance of our system is verified through extensive simulations under three different scenarios of normal, economic, and smart with different selling prices using real data, and simulation results are compared in terms of daily energy cost, PAR, user's convenience and consecutive waiting time to use appliances. Numerical results clearly show that the economic scenario achieves 51.6% reduction of daily energy cost compared to the normal scenario while sacrificing the user's convenience, PAR, and consecutive waiting time by 49%, 132%, and 1 hour, respectively. On the other hand, the smart scenario shows only slight degradation of user's convenience and PAR by 2% and 18%, respectively while achieving 46.4% reduction of daily energy cost and the same level of consecutive waiting time. Furthermore, our simulation results show that a decrease of selling prices has tiny impacts on PAR and user comfort even though the daily energy cost increases.
Highlights
I N the future, the smart grid (SG) will be a main component of electricity delivery between suppliers, prosumers and consumers and play a key role in reducing energy consumption [1]
The simulation results show that our home energy management system (HEMS) accomplishes a balance among daily energy cost, user’s convenience, peak-to-average ratio (PAR), and consecutive waiting time
Our simulation results show that a decrease of selling prices has very slight impacts on PAR and user comfort even though the daily energy cost increases
Summary
I N the future, the smart grid (SG) will be a main component of electricity delivery between suppliers, prosumers and consumers and play a key role in reducing energy consumption [1]. In our previous work [15], we presented a HEMS to optimize energy cost and PAR To achieve these objectives, optimization formulas were built and solved using a PSO algorithm. Motivated by the above literature works, we propose a novel HEMS with integration of RES and ESS supporting user comfort and electricity selling. In this HEMS which is an extension of our previous work [15], the effects of different selling prices on energy cost, user comfort and PAR are fully considered. To the best of our knowledge, none of the previous studies considered an optimization model which takes daily energy cost, user comfort, and PAR into account and supports electricity selling.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
