Optimal scheduling of a microgrid with demand response resources. Issue 12 (1st December 2014)

• Record Type: Journal Article
• Authors: Carpinelli, Guido; Mottola, Fabio; Proto, Daniela
• Is Part Of: IET generation, transmission & distribution. Volume 8:Issue 12(2014)
• Page Start: 1891
• Page End: 1899
• Publication Date: 2014-12-01
• Subjects: demand side management -- electric vehicles -- distributed power generation -- power grids -- cost reduction; optimal scheduling -- microgrid -- demand response resources -- plug‐in electric vehicle fleets -- microgrids -- distributed generation units -- DG units -- distributed resources -- power grid -- load profile -- high‐cost periods -- μG -- EV fleets -- data centre storage systems -- optimisation model -- cost minimisation; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2013.0758
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : A larger penetration of plug‐in electric vehicle (EV) fleets and of data centres in the microgrids (µGs) is foreseeable in the near future. Their presence and the presence of distributed generation (DG) units represent a challenge for system operators in that they must identify approaches for using these distributed resources that allow them to operate the grid in a more efficient and economical way. With particular reference to EVs and data centres, it must be noted that they are equipped with storage devices that potentially could result in the modification of the daily load profile of µGs by shifting peak demand away from the high‐cost periods. This study is focused on the use of data centres and EV aggregators as demand‐response resources, and a new model for the operation of a µG that includes DG units, EV fleets and the data centre's storage systems has been proposed. The procedure is based on a non‐linear, constrained, optimisation model with the aim of minimising the total cost of energy and simultaneously shaving peak power. The effectiveness of the proposed strategy was demonstrated by means of numerical applications to a low‐voltage, test µG.