Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/100638
PIRA download icon_1.1View/Download Full Text
Title: Optimal scheduling of virtual power plant with battery degradation cost
Authors: Zhou, B
Liu, X
Cao, Y
Li, C
Chung, CY
Chan, KW 
Issue Date: Feb-2016
Source: IET generation, transmission & distribution, Feb. 2016, v. 10, no. 3, p. 712-725
Abstract: This study proposes a novel optimal generation scheduling model for virtual power plant (VPP) considering the degradation cost of energy storage system (ESS). The VPP is generally formed by a mix of distributed energy resources, and the ESS is an important installation for flexible VPP dispatch due to its controllable and schedulable behaviours. For the operations of battery storage systems, the ambient temperature and depth of discharge have significant impacts on the wear and tear of the ESS as well as battery degradation cost. Furthermore, the battery degradation cost is modelled and approximated by a piecewise linear function, and then incorporated into the proposed optimal VPP scheduling model. Consequently, the optimal VPP scheduling problem is formulated as a two-stage stochastic mixed-integer linear programming in order to maximise the expected profits of the VPP. The proposed model has been successfully implemented and tested through a representative case study, and the influence of battery degradation cost on optimal VPP scheduling has also been thoroughly analysed and demonstrated.
Publisher: Institution of Engineering and Technology
Journal: IET generation, transmission & distribution 
ISSN: 1751-8687
EISSN: 1751-8695
DOI: 10.1049/iet-gtd.2015.0103
Rights: © The Institution of Engineering and Technology 2016
This paper is a postprint of a paper submitted to and accepted for publication in IET Generation, Transmission & Distribution and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Chan_Optimal_Scheduling_Virtual.pdfPre-Published version1.17 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

68
Citations as of Apr 14, 2025

Downloads

93
Citations as of Apr 14, 2025

SCOPUSTM   
Citations

105
Citations as of Sep 12, 2025

WEB OF SCIENCETM
Citations

78
Citations as of Oct 10, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.