Cost reflectivity of investment proxies CAP131 Working Group (4) 17 November 2006 Slides updated to reflect: feedback and comments from WG2 include available data from Scotland alternative proxies raised effect of different substation costs (the collar) comparison to current FSL and entry CAPEX “s-curve” comparison – 25/50/75/100

Action Action To explore the cost reflectivity of various proxies for infrastructure investments, which need to be supported by a user commitment Aim To establish whether there are more cost-reflective investment proxies than TNUoS tariffs and consider whether these are “better” when assessed against the Applicable CUSC Objectives

Content Analysis framework and methodology Locational investment proxies zonal proxies nodal proxies sensitivity analysis Non-locational investment proxies Wider assessment of proxies Conclusions

Cost reflectivity of investment proxies Analysis framework and methodology

Process Map Identify groups of projects that require similar system reinforcements Establish unit capital investment costs (£/kW) for groups Compare annual investment proxy to capital investment costs Calculate average & spread between project groups as measure of cost reflectivity Express as a number of years of the investment proxy

Investment costs for groups Several groups of projects considered, where each group requires similar transmission investments represents a sample of ~31GW of generation (between 2007-2012) Investments consider a range of scenarios within group One investment group is illustrated below Gradient gives average capital investment cost in £/kW [Note, all investment costs expressed in unit terms, where kW refers to generation capacity] P1+P2+P3 P3 P2 P1

Number of project scenarios Project group data Project Group Gen Capacity (MW) Number of project scenarios Group A (EW) 2400 12 Group B (EW) 4300 10 Group C (EW) 5100 Group D (EW) Group E (EW) 3100 6 Group F (EW) 2200 3 Group G (EW) 2500 24 Group H (Scotland) 3400 1 (contracted) Group I (Scotland) 23 E&W projects considered 67 Scotland projects considered

Establishing number of years of proxy For each group, actual investment costs (£/kW) are compared with applicable investment proxy (£/kW): where a zonal proxy has been used, the zone that best represents projects within a group has been used Range of annual proxies For each Group Actual Capital Cost (£/kW) Number of years of proxy Annual Proxy Cost (£/kW) = × across all investment Groups Average and St. Dev.

Cost reflectivity of investment proxies Locational Investment Proxies Zonal proxies Nodal proxies Sensitivity analysis

Investment proxies considered Locational proxies All proxies been derived from the TNUoS model Retained £3/kW p.a. de-minimis for local substation works Nodal investment proxies full tariffs locational tariffs Zonal investment proxies full TNUoS tariffs locational TNUoS tariffs re-zeroed TNUoS differential tariffs (no residual) Removes the revenue recovery adjustments i.e. the residual To remove effects of an arbitrary slack node (see sensitivity analysis)

Zonal investment proxies Slide illustrates shape of the proxies compared against TNUoS. [Easiest to explain shapes starting with TNUoS, then add the collar, then remove residual, then re-zero. In practise, the order does not matter] £3 /kW p.a. collar

Analysis results Zonal investment proxies Zonal Investment Proxy Years of Proxy Average SD Zonal TNUoS tariff 12.8 3.7 (29%) Zonal TNUoS, locational only 16.4 5.8 (35%) Zonal TNUoS, re-zeroed at London 8.0 1.8 (27%)

Nodal investment proxies Where possible, the nodal marginal km at the node where generation is expected to connect has been converted to a tariff by considering: re-referencing quantity security factor expansion constant Has not been applied to all projects, as nodes do not presently exist within transport model analysis covers ~19GW of sample pool (~31GW) England & Wales only same parameters used to calculate zonal tariffs

Analysis results Nodal investment proxies (c.f. Zonal) Nodal Investment Proxy Years of Proxy Average SD Nodal “TNUoS tariff” 15.1 5.3 (35%) Nodal “TNUoS”, locational only 17.7 6.0 (34%) Zonal Investment Proxy Years of Proxy Average SD Zonal TNUoS tariff 12.3 3.6 (29%) Zonal TNUoS, locational only 15.8 6.6 (36%) Zonal TNUoS, re-zeroed at London 7.6 1.9 (24%)

Observations Locational proxies Nodal approach does not add extra cost-reflectivity no smoothing for lumpiness of a nodal cost adds complexity to the methodology for little return Trade-off between number of years of the investment proxy and the magnitude of that proxy low number of years, high proxy cost high number of years, low proxy cost

Sensitivity analysis Two key sensitivities tested: effect of different zero points effect of different substation costs

Why consider re-zeroing? Additional generation triggers reinforcement to load centres DCLF model establishes a system centre (the “slack node”) The “slack node” is the most interconnected node and is arbitrarily assigned an incremental cost of zero (£0MWkm) The ‘real’ incremental cost at the “slack node” is not zero investment required to transfer the marginal MW to the load

Is Thorpe Marsh an appropriate centre? Costs incurred “south” of the system centre to transport energy to location of load CAP131 is about the commitment made prior to costs being incurred Thorpe Marsh is the slack node (SN) “B7” SN “B8”

Effect of different zero points Alternative zero-points considered Investigated the effect of considering different zero points Have considered: Peninsula (Zone 21) Central London (Zone 16) S.Wales & Gloucester (Zone 19) South Yorkshire & North Wales (Zone 14) Peterhead (Zone 1) The aim is to identify which zero-point provides the best fit to actual investment costs incurred Contains the slack node, Thorpe Marsh [Zone 14 was used effectively as the “baseline” against which the other options were considered. Zone 16, Central London, is an obvious choice given the flows typically observed on the system. Zone 21, Peninsula is a bounding extreme.] [The residual has been removed to exclude revenue collection effects] [There might be other alternative ways by which an alternative zero-point could be established, e.g. some sort of sensitivity analysis, but don’t expect this to add much.]

Effect of different zero points Investment proxies with different zero points

Effect of different centres of load Identifying the most appropriate zero point Note, a lower number represents a better fit Best Fit

Local substation costs Used to determine de-minimis level of investment proxy Calculated the cost of a generic substation for a 1GW plant designs will clearly vary, some more expensive others less but this is a generic methodology Expected capital cost ~£30m For interim arrangements, a 10 year commitment was sought and therefore an annual £3/kW commitment needed Needed to check whether still appropriate Assessed sensitivity of different local costs

Local substation costs Sensitivity results Note, a lower number represents a better fit Best Fit

Cost reflectivity of investment proxies Non-Locational Investment Proxies

Investment proxies considered Non-Locational, nodal proxy An alternative investment cost proxy suggested within Working Group is based on: capacity requested, TEC (MW) length of local line required to connect, L (km) minimum of 15km for substation assets TO and voltage / circuit specific expansion factor, EF expansion constant, EC (£/MWkm) Generic cost proxy = TEC × L × EF × EC … shouldn’t the security factor be in here too?

Illustration Investment Proxy = TEC (MW) × L (km) × EF × EC (£/MWkm) Assumes 400kV OHL EF = 1 EC ≈ 10 £/MWkm 500MW, 15km Liability = £75k 650 marginal km Proxy does not consider the costs associated with wider reinforcements shown by the red arrows SN 500MW, 15km Liability = £75k -500 marginal km

Observations Non-Locational, nodal proxy Does not consider any wider reinforcement costs associated with a given project at a given location Very difficult for users to apply prior to application length of connection unknown circuit type unknown (OHL / cable, voltage) Potentially subjective use of expansion factors what is a representative value for project / system / TO region

Cost reflectivity of investment proxies Wider assessment & Conclusions

Wider assessment of investment proxies Cost reflectivity is not an applicable CUSC objective, it is part of facilitating competition Important, therefore, to consider other criteria against which the investment proxies should be assessed transparency of methodology to derive proxy ease for both Users and National Grid to determine commitment ease of application to new entry points i.e. nodes that don’t exist others?

Wider assessment of options Investment Proxy Transparency of proxy Ease of use by Users Copes with change Cost Reflectivity Locational proxies Zonal TNUoS tariff      Zonal TNUoS, locational only  Zonal TNUoS, re-centred Nodal “TNUoS tariff”       Nodal “TNUoS”, locational only Non-locational proxies Expanded connecting line length

Cost Reflectivity Comparison

Timing of spend – actual v generic (Sample size 24 projects)

Shape Comparison - 25/50/75/100 v 40/75/85/100

Cost Reflectivity Conclusions A pure non-locational approach is a poor investment proxy TNUoS tariffs provide a reasonable investment proxy Locational TNUoS tariffs re-centred on Central London provide a more cost reflective locational investment proxy But, this would require arrangements to overcome transparency issues and could confuse new entrants A de-minimis level of £3 /kW reasonably reflects local costs X=12.8 is a good approximation of total TO planned entry CAPEX 25/50/75/100 provides a better overall fit