Open AccessOptimised TSO–DSO interaction in unbalanced networks through frequency‐responsive EV clusters in virtual power plants
Author(s) -
Sanchez Gorostiza Francisco,
GonzalezLongatt Francisco
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2019.1947
Subject(s) - distributed generation , harmony search , frequency deviation , electric power system , engineering , grid , converters , power (physics) , ac power , automatic frequency control , computer science , simulation , renewable energy , electrical engineering , voltage , physics , quantum mechanics , geometry , mathematics , artificial intelligence
The increased penetration of distributed energy resources (DERs) installed in distribution networks via power electronic converters reduces the overall rotating inertia of the power system, causing faster frequency dynamics after a large disturbance. However, these DERs coupled with energy storage systems (ESSs) can be managed to provide valuable grid support functions such as fast frequency response (FFR) and assist the transmission system operator (TSO) in frequency control. In this study, single‐ and three‐phase clusters of electric vehicles (EVs), acting as mobile‐ESSs, are grouped together as virtual power plants (VPPs) to centralise the provision of FFR for the distribution system operator (DSO) whilst considering network unbalance. Furthermore, the parameters of the EV clusters within each VPP are optimised to minimise the inertia‐weighed maximum frequency deviation following a disturbance whilst adhering to network security and power quality constraints. To this aim, a variant of the metaheuristic optimisation algorithm called improved harmony search is used for the optimisation process. Finally, the merits of the proposed methodology are shown with an illustrative example of an unbalanced three‐phase transmission and distribution network modelled in DIgSILENT PowerFactory. The results show that clusters of EVs grouped as VPPs effectively improve frequency support via the TSO–DSO interaction.