Abstract
In the last decades, the growth of electric energy demand made the study and application of peak shaving systems grown rapidly. One of the most crucial parts of these systems is the Energy Storage System (ESS) sizing. Numerous methods have already been proposed for sizing, forecasting and ESS charge/discharge planning. However, optimization sizing techniques aiming economic benefits have not been explored yet for Battery Energy Storage Systems (BESS) associated with Supercapacitors. This paper proposes a sizing methodology to determine the quantity of BESS and Supercapacitor from a load profile to obtain maximum financial savings. The code uses genetic algorithm to find the best ESS combination and calculates its respective operating points to determine which has the greatest economic potential. The outputs are the BESS and Supercapacitor values (in kWh) that the consumer should acquire in order to obtain the highest rate of return. Showing that, depending on the analyzed load profile, the association of different ESS technologies can lead to a higher economic benefit than using only one.
Sign-in/Register to access full text options 
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.
