Optimal scheduling of virtual power plant with battery degradation cost. Issue 3 (1st February 2016)

• Record Type: Journal Article
• Authors: Zhou, Bin; Liu, Xi; Cao, Yijia; Li, Canbing; Chung, Chi Yung; Chan, Ka Wing
• Is Part Of: IET generation, transmission & distribution. Volume 10:Issue 3(2016)
• Page Start: 712
• Page End: 725
• Publication Date: 2016-02-01
• Subjects: power generation scheduling -- battery storage plants -- costing -- energy storage -- distributed power generation -- power generation dispatch -- approximation theory -- stochastic programming -- integer programming -- linear programming -- profitability -- power generation economics -- power distribution economics; virtual power plant -- battery degradation costing -- optimal generation scheduling model -- energy storage system -- ESS -- distributed energy resource -- flexible VPP dispatching -- battery storage system -- piecewise linear function -- optimal VPP scheduling problem -- two‐stage stochastic mixed‐integer linear programming; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2015.0103
• Languages: English
• ISSNs: 1751-8687

Abstract

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.