Capacity configuration method for new energy storage system based on segmented peak shaving

Zesen Li, Bingjie Li and Guojing Liu

International Journal of Global Energy Issues, 2025, vol. 47, issue 4/5, 418-435

Abstract: To overcome the problems of low accuracy in capacity estimation, low balancing degree and low utilisation rate in traditional methods, a capacity configuration method for new energy storage system based on segmented peak shaving is proposed. The battery's internal resistance and terminal voltage signals of the new energy storage system are taken as inputs, and the capacity estimation is the output. A capacity estimation model based on an improved fuzzy neural network is established. The capacity configuration objective function is constructed by combining segmented peak shaving and economic cost. Hybrid frog-leaping algorithm is used to obtain the optimal parameters for segmented peak shaving and economic cost through population initialisation, position updates and frog swarm sorting to determine the optimal configuration scheme. Experimental results show that the average accuracy of capacity estimation using this method is 97.31%, the maximum balancing degree is 0.98 and the minimum utilisation rate is only 90.9%.

Keywords: segmented peak shaving; new energy storage system; capacity configuration; improved fuzzy neural network; hybrid frog-leaping algorithm. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=147240 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijgeni:v:47:y:2025:i:4/5:p:418-435

Access Statistics for this article

More articles in International Journal of Global Energy Issues from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().