Recordando el texto leído

In Case A1 we investigated the impact that shifting demand at the national level has on the load on the distribution network. The question here is:

When does shifting demand at the national level create a new level of demand on the distribution network that is higher than would have been the case if the distribution network had only been reinforced to meet a fixed demand profile?

Our main conclusion from this scenario is that shifting demand at the national level to meet a network constraint does create the need for additional investment in the distribution network and more specifically the rural area of the distribution network. We compared two scenarios for this analysis. The first was when there was no DSR deployed and therefore the assumption was that networks were sized to meet peak demand. In the second scenario, DSR is allowed to be used to minimise the cost of meeting demand as long as it does not exceed the total national network constraint. Table 1 shows the level of capped demand on the national network.

Table 1 – National network constraint in runs for Case A1

Action Max. national demand, GW

Without DSR 89.3

With DSR 86.8

In order to identify the level of the distribution network on which the problem takes place, we produced distribution network profiles by disaggregating national demand to specified levels on the distribution network:

Urban: low voltage (LV), high voltage (HV) and extra high voltage (EHV); Suburban: LV, HV and EHV; and

As a result, we derived 9 separate demand profiles, each corresponding to the different voltage level (LV, HV and EHV) and area (urban, suburban and rural) for each set of constraints i.e. the no DSR case and the DSR case with a national network constraint. Examples of the demand profiles we used are shown in Annex A.

By comparing each of the 9 distribution network profiles with the corresponding profile from the second run we established the magnitude and frequency of the network breach. Table 2 gives the magnitude of demand that exceeds the level set in the baseline case while Figure 18 shows the frequency and maximum of instances in which demand on the distribution network under DSR and a national network constraint is greater than demand on the distribution network in the baseline.

Table 2 – Total magnitude of demand shifted on distribution network to meet national transmission constraint (MWh)

Urban Suburban Rural

LV 1661 MWh 125 7072

HV 1144 0 5860

EHV 419 0 3627

Figure 18 – Magnitude by which demand is reduced on the distribution network using DSR

There are two trends visible from Table 2 and Figure 18. Firstly, there are a relatively small number of periods in which demand is greater on the distribution network than the maximum level set in the baseline and secondly there are more instances of demand

breaching the baseline on the rural network. Following on from this second point, there is a greater volume of demand that exceeds the capacity limit set in the baseline scenario on the rural network while the absolute magnitude of these breaches is most on the rural and urban network.

The reason for the relatively small number of breaches compared to the baseline is due to the fixed profile of electric vehicles. In the baseline electric vehicles are deployed but the profile is fixed and is quite peaky. This means that in the baseline scenario, the fixed EV demand profile sets the peak network demand rather high in areas where EV

concentration is high. These areas include urban and suburban but not rural areas. As a result, when demand is flexible, the baseline is set quite high in the urban and suburban networks. This means that even when demand moves around it does not necessarily breach the network limit. However, this is not the case on the rural network where there are far fewer electric vehicles. As a result, EVs contribute less to the non DSR baseline capacity which means the network constraint will be relatively tight and more susceptible to breaches when DSR moves demand around.

In order to derive a price signal for each use of DSR, we need two pieces of information: the cost of investment and the magnitude of energy (MWh) that is moved by the TSO when it wants to avoid investment and the result the volume by which demand is increased on the DNO network.

The cost of avoiding network investment at the national level is taken from our previous work for DECC and as a rule of thumb is about £0,5bn/GW. Distribution network investment costs differ by voltage level and network area and are specified in Table 3.

Table 3 – Investment costs required for each MW upgrade to the distribution network

£k/MW Urban Suburban Rural

LV 337.8 120.1 40.6

HV 164.4 178.4 170.0

EHV 242.6 175.1 111.0

Source: University of Bath

If we assume that the distribution network is reinforced to meet the maximum demand then the costs specified in Table 4 are incurred.

Table 4 – Additional investment costs required on the distribution network

£m Urban Suburban Rural

LV 94.8 7.9 9.9

HV 35.8 0 33.7

In order to convert total investment costs into an average price signal, we divide the levelised investment cost by the MWh of demand that has been moved (Table 2). The results are shown in Table 5.

Table 5 – Price signals required for DNO to invest when demand is capped at the national level (levelised distribution network investment costs)

£/MWh Urban Suburban Rural

LV 2882 3165 71

HV 1582 - 292

EHV 3031 - 326

Table 5 shows the price signals required to incentivise additional investment on the distribution network. There are two trends to comment on. The first is the magnitude of the price signal and the second is the difference between price signals on different parts of the distribution network.

The price signals that are derived in Table 5 are large. The main reason for this is the relatively small volume of demand that is moved compared to the baseline (Table 2). As a result, we are effectively dividing a fairly large investment cost by a relatively small volume of demand. The result is a high price signal to justify investment.

There is a clear difference between the price signals on different parts of the distribution network due to the volume of additional demand that is above the limit set in the baseline case. As a result, in the cases where there is more demand shifted above the network constraint set in the baseline the corresponding price signal from the distribution network gets weaker.

This difference is most marked between the price signals shown in the urban demand column and those shown in the rural demand column. This means that compared to the baseline, the urban network, if sized according to the magnitude and profile of demand in this study, is better placed to facilitate DSR than the rural network.

In reality the breaches on the network are not distributed evenly. The data table in the Appendix shows the distribution of instances where the peak set in the baseline is breached sorted into bins of magnitude. This uneven distribution suggests that at some point it will be economically optimum limit capacity on the distribution network by sending a strong price signal to the market.

Figure 19 below illustrates the point by showing the levelised investment cost for different voltage levels of the rural network divided by the MWh of demand that is shifted to meet national network constraints.

Figure 19 – Effect of incremental investment on price signals

Clearly the above figure suggests that there is an increased cost when the distribution network is reinforced beyond 150MW on each of the rural voltage levels. The maximum benefit (in terms of lowest price signal per MWh) is achieved when the distribution network is reinforced by between 50MW and 150MW.