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Balancing the load. A look at the prospects of UK V2G

The UK represents one of the most open energy marketplaces in the world and therefore offers an opportunity for reliable financial modelling.

In a recent report by the National Grid and Ricardo, the future of plug in hybrid and electric vehicles is considered as a long term solution to the problems of the high cost of energy storage and decarbonising grid power supplies, by connecting variable sources of power such as wind and wave to the grid.

 

 

The problem

The Report sets out in a simple and understandable manner how grid supply and demand is balanced in the UK. Balancing services are procured by the National Grid on a commercial basis from both power station operators and large scale energy consumers. Power station operators hold spare capacity at varying levels of readiness, and on the demand side, customers can reduce their consumption within a defined response period.

Balancing services are either ‘response’ services, ie those that can be applied quickly and automatically, or those which are ‘reserve’ services, ie dispatched for longer periods. With the exception of some renewable generators, all power station turbines are synchronised giving the same frequency of output at 50HZ. Any mismatch in energy imput to drive the turbine must be matched with the output of the generator, or damage can be done to the network,

 

The solution

The report looks at ‘Demand Side Management’ by the use of plug in vehicles. One method is to power a battery below its capacity to allow headroom for increases or reductions in demand. The other method is known as V2G ie reverse charging, where the battery is made available for balancing services, where the grid’s authority is limited to permit the driver to use his vehicle when required.

The Ricardo Model

Ricardo has developed a comprehensive model that simulates interaction between PIVs and the electricity grid to evaluate the potential for a future ‘parc’ [or population of users] of plug in vehicles to enter the balancing services market. Two distinct models were considered, the ‘grid- level model’ where one operator is responsible for a large number of ‘fleet vehicles’ and ‘the individual user model’.

Within the two distinct models, Ricardo looked at various pricing models, such as delayed charging to encourage night time charging and smart charging.  For the individual user model, certain assumptions were made that vehicles would be charged during office hours and overnight as the majority of users would be commuters.

Spectacular results

The report concluded that the use of V2G could produce a considerable financial advantage over earlier Demand Side Management models. A parc wide implementation of V2G by 2020 could produce 100% of the UK’s balancing service requirements between 19.00 and 06.55 producing considerable payments to the user from £600 per annum to a possible £8,000 per annum for a more sophisticated installation.

The commercial potential for the individual market is however limited as increasing users bring down the income generated as a return on investment.  The advantages would seem to be more apparent for fleet users such as commercial logistics firms, vehicle rental firms, ports and airports or battery swap station networks such as Better Place.

Conclusion.

The report concludes that the research has found that there is a clear potential for the commercial exploitation of a future ‘parc’ of electric plug in vehicles in the provision of grid balancing services while they are connected for the purposes of daily recharging. By 2020 the ‘parc’ could provide an average of 6% of the country’s predicted grid balancing requirement at a zero investment cost with a limited financial return, with a more dramatic potential for fleets and other vehicle aggregators.√جª¬ø

The report is an excellent read as it has some helpful graphics to explain ‘load balancing’ as well as more details of the financial modelling that was undertaken. Click here to read the full report.

 

 

 

 

Originally posted 2011-08-23 00:00:00.

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