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The University of Southampton
UK/China Project on Battery Characterisation and Management

WP3 - V2G control

V2G Power System Control and Operation

V2G implementation will be on a geographically distributed basis, using EVs when grid connected, i.e. parked for recharging. The number of batteries grid connected reflects driving patterns and the charging strategies adopted to deliver the different power system support functions of interest. Modelling these complex tasks and developing effective control algorithms will be addressed in the following two sub‐tasks:


Task 3.1 ‐ V2G Power System Modelling 

Technical Challenge – Battery systems for vehicles are designed to fulfil the requirements for the driving cycles, range and lifetime expectations for which they are installed. They are not presently designed to deliver any additional V2G functionality. To determine realistic V2G battery usage cycles an accurate understanding of vehicle use and charge requirements, alongside power system operation and constraints and how this can be improved by V2G based energy storage, is essential. This is best approached by static and dynamic power system analysis based on comprehensive Monte Carlo simulation of the charging loads.
As the EVs will almost always physically connect to the grid only at low voltage (LV) levels detailed power system models must be extended to include these levels (typically LV networks use ‘lumped’ models) and cater for modelling the geographical element of V2G operation.


Task 3.2 ‐ V2G Control Algorithms

Technical Challenge – The use of aggregated EV batteries offering grid support services is inherently technically feasible, however there are considerable technical, regulatory and commercial challenges remaining that require further study, prior to implementing such a system. At a core level, the instantaneous energy capacity, availability and power capability of grid connected EVs must be calculated (parts of WPs 1 & 2), and the power system status and required control function reference defined e.g. system frequency signal or renewable energy forecast (from Task 3.1). The challenge for this task is to develop robust V2G control algorithms that can deliver the required total electrical energy storage functionality in a responsive manner.

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