environment and innovation commentary v5 · 2019-10-24 · two other substations were fitted with...

RIIO-ED1 RIGs Environment and Innovation Commentary

2018/19

UK Power Networks

Contents

Summary – Information Required 1

Worksheet by worksheet commentary 1

E1 – Visual Amenity 2

E2 – Environmental Reporting 2

E3 – BCF 3

E4 – Losses Snapshot 5

E5 – Smart Metering 6

E6 – Innovative Solutions 7

E7 – LCTs 8

Summary – Information Required

One Commentary document is required per DNO Group. Respondents should ensure that comments are clearly marked to show whether they relate to all the DNOs in the group or to which DNO they relate.

Commentary is required in response to specific questions included in this document. DNO’s may include supporting documentation where they consider it necessary to support their comments or where it may aid Ofgem’s understanding.Please highlight in this document if additional information is provided.

The purpose of this commentary is to provide the opportunity for DNOs to set outfurther supporting information related to the data provided in the Environment and Innovation Reporting Pack. It also sets out supporting data submissions that DNOs must provide to us.

Worksheet by worksheet commentary

At a worksheet by worksheet level there is one standard question to address, where appropriate, as follows:

Allocation and estimation methodologies: DNOs should detail estimates, allocations or apportionments used in reaching the numbers submitted in the worksheets.

This is required for all individual worksheets (ie not an aggregate level), where relevant. Not all tables will have used allocation or estimation methods to reach the numbers. Where this is the case simply note “NA”.

Note: this concerns the methodology and assumptions and not about the systems in place to check their accuracy (that is for the NetDAR). This need to be completed for all worksheets, where an allocation or estimationtechnique was used.

In addition to the standard commentary questions, some questions specific to each worksheet are asked.

Environment and Innovation Commentary 1

E1 – Visual AmenityAllocation and estimation methodologies: detail any estimations, allocations or apportionments to calculate the numbers submitted.Our direct cost allocations described in the Strategic Commentary apply to this table.

Explanation of the increase or decrease in the total length of OHL inside designated areas for reasons other than those recorded in worksheet E1. For example, due to the expansion of an existing, or creation of a new, Designated Area. AONB project work is heavily front end loaded on, and includes: scheme identification; planning; costing; and securing scheme approval through the agreed constitutional process with the Area of Outstanding Natural Boards/National Park Authorities. UK PowerNetworks is now working to an agreed list of projects, to be delivered throughout the remainder of RIIO-ED1. Where it is necessary, due to engineering complexities or inability to secure landowner consents, schemes will be swapped out from a reserve pool of schemes. In EPN, progress has been steady with further schemes delivered and in construction phases since end of the 2018/19 regulatory year. Recent work has refocused attention on the delivery of schemes in the SPN region, which has fallen behind the curve on the progression on consents and delivery of schemes.

E2 – Environmental ReportingAllocation and estimation methodologies: detail any estimations, allocations or apportionments to calculate the numbers submitted.Our direct cost allocations described in the Strategic Commentary apply to this table.

DNOs must provide some analysis of any emerging trends in the environmentaldata and any areas of trade-off in performance. During the regulatory period 2018/19 UK Power Networks received 26 enquiries and complaints about noise from substations and transformers, 9 fewer than the previous year. This number fluctuates from year to year but without any identifiable cause.

All cases were investigated and, where appropriate, sound measurements were taken in the customers’ home, either by trained members of staff who hold the Institute of Acoustics Certificate of Competence Environmental Noise Measurement, or by a specialist Acoustic Consultants. When those measurements exceeded the reference curves in the ‘Procedure for the assessment of low frequency noise complaints’ (NANR 45) mitigation measures were instigated. NANR 45 was developed to assist local authority environmental health officers dealing with low frequency noise complaints.

Four substations had mitigation measures applied during the regulatory period; two secondary substations had replacement transformers installed and the transformers at two other substations were fitted with anti-vibration pads.

We proactively engage with local authority environmental health and planning departments and offer to deliver presentations at their professional forums about the assessment of low frequency noise from substations and the importance of considering it in the planning process. We also give ad hoc support and guidance in individual casesbecause many environmental health teams have limited experience of low frequency noise assessment.

Where reported in the Regulatory Year under report, DNOs must provide discussion of the nature of any complaints relating to Noise Pollution and the nature of associated measures undertaken to resolve them.


One abatement notice was received from a local authority for noise from a temporary generator.

Six notices were received relating to litter, third-party fly-tipped waste, or pests; three of which were rejected because the land was not owned or controlled by UK Power Networks.

A warning letter was received from the Environment Agency relating to pollution of surface water via a surface water outfall. EHV cable fluid from a very low volume (<40L/month) leak entered a sewer pipe damaged by a third party and co-mingled with pollution from other sources linked to drain misconnections.

Twelve reportable incidents were logged with the Environment Agency where oil was lostto the local environment. We reported one case of minor tree damage to the local authority.

There were no prosecutions.

Where reported in the Regulatory Year under report, DNOs must provide detailsof any Non-Undergrounding Visual Amenity Schemes undertaken. None to report.

Any Undergrounding for Visual Amenity should be identified including details of the activity location, including whether it falls within a Designated Area.None to report.

Where reported in the Regulatory Year under report, DNOs must provide discussion of details of any reportable incidents or prosecutions associated withany of the activities reported in the worksheet. None to report.

Where reported in the Regulatory Year under report, DNOs must provide discussion of details of any Environmental Management System (EMS) certified under ISO or other recognised accreditation scheme.External Audits of our Environment Management System were conducted in May and October/November 2018. ISO 14001:2015 certification to the new standard was achieved in August 2018. There were no major non-conformities and in the most recentreport the auditors commented that there was ‘Increasing visibility of environment at a high level within UKPN and a positive approach to further delivering environmental performance improvement and compliance.’

DNOs must provide a brief description of any permitting, licencing, registrationsand permissions, etc related to the activities reported in this worksheet that you have purchased or obtained during the Regulatory Year.No new permits, or variations to existing permits, were applied for in the regulatory year.

DNOs must include a description of any SF6 and Oil Pollution Mitigation Schemes undertaken in the Regulatory Year including the cost and benefit implications and how these were assessed. SF6 Mitigation – Replacements

Histon Grid – This involved the replacement of a defective and leaking 33kV SF6 circuit breaker. The Aldreth Number 1 circuit at Histon Grid is a 33kV South Wales Switchgear HG36 circuit breaker, situated outdoors. It is a feeder breaker that feeds the Aldreth Primary Substation and Sutton Power Station.

This circuit breaker was a priority, because it leaked significantly.

The most cost-effective solution was deemed to be replacement of the circuit breakers


following assessment of the condition of the breakers which confirmed that it could not be repaired. This intervention was completed on the 12th of July and resolved the issue with SF6 leakage on this breaker as we have had no reported leaks since the intervention.

Tillingham Primary 33kV - This involved the replacement of a defective and leaking 33kVSF6 circuit breaker. The Bradwell Farm circuit at Tillingham Primary is a 33kV OrmazabalCGMPV circuit breaker, situated indoors. It is a feeder breaker that supplies the BradwellWind Farm. The circuit breaker was leaking at a rate of 0.65kg a month. Following an assessment of the circuit breaker by the manufacturer, it was deemed irreparable and therefore replacement was the only viable solution. The intervention was completed in November, 2018.

SF6 Mitigation – Refurbishments City Road – A 132kV circuit breaker at City Road was leaking significantly. Following an assessment by the manufacturer, it was deemed amenable to repair. It was refurbished in December 2018 with a replacement of all worn or defective parts and there have beenno more reported leaks since.

Wimbledon Grid – This was a refurbishment (replacement of worn seals and other relevant parts) of a 132kV circuit breaker. This circuit breaker is a 132kV GEC FG1 which was leaking at a rate of 0.8kg per month. Following detection and assessment of the leak source, refurbishment was selected as the most cost-effective solution. The refurbishment was completed on the 15th of June 2018 and the asset has been leak free since.

Three Bridges Main - This was a refurbishment (replacement of worn seals and other relevant parts). This circuit breaker is a 132kV Siemens 3AP1DT which was leaking significantly and following condition assessment was refurbished on the 6th of September2018. It has not leaked since.

Brimsdown 132kV – This was a refurbishment (replacement of worn seals and other relevant parts) of two 132kV circuit breakers and was completed on the 18th of November 2018.

CB105 and CB305 are 132kV ABB HPL145A SF6 circuit breakers which were leaking at acombined rate of 1.4kg per month. Following an assessment of the circuit breakers, a refurbishment was determined as the most cost-effective form of intervention. The workwas completed on the 18th of November 2018 and both breakers have been leak free since then.

E3 –BCFAllocation and estimation methodologies: detail any estimations, allocations or apportionments to calculate the numbers submitted.

The following commentary details the processes used to calculate the BCF for UK Power Networks specific to our three licensed distribution networks; EasternPower Networks plc (EPN), London Power Networks plc (LPN) and South Eastern Power Networks plc (SPN).

All data in this commentary that is indicated with a yellow box as shown in the example below corresponds with the completed E3 summary tables returned toOfgem.

Example:

Where data is only collected centrally this is apportioned between UK Power Networks three DNOs based on headcount as of March 2019. These


apportionments are covered in the detailed commentary for the individual areas.

BCF reporting boundary and apportionment factorDNOs that are part of a larger corporate group must provide a brief introduction outlining the structure of the group, detailing which organisations are considered within the reporting boundary for the purpose of BCF reporting.

Any apportionment of emissions across a corporate group to the DNO business units must be explained and, where the method for apportionment differs from the method proposed in the worksheet guidance, justified.All data provided is for the Regulatory reporting year (April 2018 to March 2019). In all calculations the Defra conversion factors in place on March 31st 2019 - as recommended in the reporting guidelines from Ofgem - have been used unless stated otherwise.

The Greenhouse Gas (GHG) Protocol categorises direct and indirect emissions into three broad scopes:

Scope 1: Direct GHG emissions from sources owned or controlled by UK Power Networks.

Scope 2: Indirect GHG emissions from consumption of purchased electricity, heat or steam.

Scope 3: Other indirect emissions, such as the extraction and production of purchased materials and fuels, transport-related activities in vehicles not owned or controlled by UK Power Networks, electricity-related activities (e.g. T&D losses) not covered in Scope 2, outsourced activities, waste disposal, etc.

UK Power Networks is a parent company Z that has full ownership and financialcontrol of operations A, B, C and D Unregulated. Data indicated with an X in our submission is inclusive of data from subsidiaries; A, B, and C unless stated otherwise.

Data defined as D refers to our unregulated business and is excluded from the tables.

Data indicated with a Y is from our main contractors and their sub-contractors for the regulated activities.


BCF processThe reporting methodology for BCF must be compliant with the principles of theGreenhouse Gas Protocol.1 Accounting approaches, inventory boundary and calculation methodology must be applied consistently over time. Where any processes are improved with time, DNOs should provide an explanation and assessment of the potential impact of the changes.

Monthly reports are received from various sources within UK Power Networks covering electricity and gas meter readings; Fleet fuel usage; business mileageand transport expense claims; generator fuel usage; SF6 top ups and head count.

Externally contractors provide monthly reports of fuel usage for fleet and plant and equipment and provide business mileage on UKPN contracts. Booking reports are received from our external travel provider, all on a monthly basis.

Annually a report on network losses is received.

The conversion factors were sourced from Defra on 31st March 2019 and the latest Regulatory Information Guidelines are reviewed for any changes to the reporting process.

Data for the regulatory year is apportioned between UK Power Networks three DNOs, directly where possible and based on headcount where unique data is not available.

A monthly carbon footprint is produced from all the monthly reports to check on progress. Any anomalies in the data are highlighted in this monthly report and carefully examined to understand the reasons behind them. Corrective actions are put in place if necessary.

1 Greenhouse gas protocol


http://www.ghgprotocol.org/

The entire Business Carbon footprint process was examined for three consecutive years by UK Power Networks own internal audit team. They have moved this to every second year as they have sufficient confidence in the process.

Elements of the reporting process have also been examined on an annual basisby external auditors DNV, as part of our ISO 14001 accreditation.


Commentary required for each category of BCFFor each category of BCF in the worksheet (ie Business Energy Usage, Operation Transport etc) DNOs must, where applicable, provide a description ofthe following information, ideally at the same level of granularity as the Defra conversion factors:

the methodology used to calculate the values, outlining and explaining any specific assumptions or deviations from the Greenhouse Gas Protocol

the data source and collection process the source of the emission conversion factor (this shall be Defra unless

there is a compelling case for using another conversion factor. Justification should be included for any deviation from Defra factors. )

the Scope of the emissions ie, Scope 1, 2 or 3 whether the emissions have been measured or estimated and, if

estimated the assumptions used and a description of the degree of estimation

any decisions to exclude any sources of emissions, including any fugitiveemissions which have not been calculated or estimated

any tools used in the calculation where multiple conversion factors are required to calculate BCF (eg, due

to use of both diesel and petrol vehicles), DNOs should describe their methodology in commentary

where multiple units are required for calculation of volumes in a given BCF category (eg, a mixture of mileage and fuel volume for transport), DNOs should describe their methodology in commentary, including the relevant physical units, eg miles.

DNOs may provide any other relevant information here on BCF, such as commentary on the change in BCF, and should ensure the baseline year for reference in any description of targets or changes in BCF is the Regulatory Year2014-15. DNOs should make clear any differences in the commentary that relate to DNO and contractor emissions.

Operational Transport

Fuel purchased for UKPN fleet vehicles is captured via fuel cards. Contractor transport data is included from contractor fuel cards submitted via manual reporting. The diesel factor has been used for conversion in the E3 template as 99.23% of fuel purchased in 2018/19 was diesel.

A small amount of diesel for temporary generation is purchased on the fuel cards but recorded separately. This is reported as part of our temporary generation carbon footprint.

Table 1a shows tCO2e emitted from the UK Power Networks fleet (X)

Key

Data Type/Description

DataSource

ConversionFactor

ConversionFactor

explained

Total Apr 18to Mar 19

(tC02e)

Details of dataprovided e.g. Direct

Measurement,Estimated or

Excluded Data

Scope(GHG

Protocol)

X Diesel FuelCard

2.627 (litres tokgC02e)

17,087.35 Measurement 1

The methodology used for calculating operational transport is consistent each year to obtain comparable data. Fuel usage is not recorded separately for each licence area. The total has been apportioned based on the number of direct operational staff per area. This year’s operational staff split was 44.1% in EPN, 29.1% in LPN and 26.8% in SPN. This compares with 43.6% in EPN, 29.8% in LPN and 26.5% in SPN last year. This method was favoured over geographic


area as a split based on km2 shows that our London network accounts for only 2% of the total km2 across our three areas and this would be a disproportionate split of CO2e from our transport fleet.

Tree trimming and streetworks services have been brought in house since 2014/15 to enable us to have greater control over the customer service offered. This inevitably increases our Scope 1 emissions in this category. However, this has to be seen in conjunction with the related decrease in Scope 3 contractor fleet fuel emissions. These combined Operational Transport emissions have reduced from 30,948.23 tCO2e in 2014/15 to 27,299.74 tCO2ein 2018/19. This represents an 11.8% decrease, mainly due to modernisation of our operational fleet and the introduction of tough pads to enable detailed job information to be transmitted on the go.

Table 1b shows the breakdown and the final submitted figures to Ofgem per licence area.

Key Area Direct op. staff Percentage of staff tC02eA LPN 809 29.1% 4,965.40B SPN 747 26.8% 4,584.86C EPN 1,228 44.1% 7,537.09

Business Transport

This section refers primarily to employee’s mileage and public transport (attending meetings etc.) which constitutes our indirect operational emissions. Some of the emissions included will be directly related to our operational work (such as visits to projects) due to the data being combined. Any source data available as costs only, has been converted into kms or litres using best available methodologies before applying the Defra conversion factors.

Transport records for shared services such as IT, HR, etc. relating to the unregulated business (D) as well is not recorded separately and all data is included within the calculations. This is consistent with previous submissions.

The data is captured from four different sources:

1) SAP (financial management system): mileage and travel claimed through expenses 2) Clarity Travel: our approved travel provider 3) Corporate credit card (CCC): travel purchased through company credit cards4) Fuel cards: fuel purchased through company fuel cards (Private mileage by those using fuel cards is declared in miles so this is deducted from the mileage expense claims in SAP)

Table 2a shows a breakdown of the amount of tCO2e emitted by our employees (X)

Business Transport - Passenger ROADKey


DataSource

ConversionFactor

ConversionFactor

explained

Total Apr18 to Mar19 (tC02e)

Details of dataprovided - Direct

MeasurementEstimated or

Excluded Data

Scope(GHG

Protocol)

X Business Kms(UKPN

companycars)

SAP(Businessmileageclaims)

0.114 (Kms tokgCO2e) (uses

car’sindividual

taxation CO2factor)

577.05 Measurement 3

X Business Kms(Non UKPN

owned

SAP(Businessmileage

0.181 (Kms tokgCO2e)(average

372.52 Measurement andestimation of taxi

journey length

3


cars/taxis) claims) unknown carfactor)

from price

X Diesel Fuel Cardand fuelexpenseclaims


2,875.16 Measurement andestimation

3

Total 3824.73

Business Transport - Passenger RAILKey Data Type/

DescriptionData

SourceConversion

FactorConversion

Factorexplained

TotalApr 18to Mar

19(tC02e)



Excluded Data

Scope(GHG

Protocol)

X Rail Travel SAP;corporatecard andClarity

0.04424 (£ to kms tokgC02e)

(Clarity datais already in

kms)

187.68 Estimate andmeasurement

3

Business Transport - Passenger AIRKey


DataSource

ConversionFactor

ConversionFactor

explained

TotalApr 18 toMar 19(tC02e)

Details of dataprovided e.g.

DirectMeasurement,Estimated or

Excluded Data

Scope(GHG

Protocol)

X Air Travel CorporateCredit

Card andClarity

0.2151 (£ to kms) tokgC02e

(weighted factor- proportional to% of long haul,

short haul ordomestic travel)

162.35 Estimate andMeasurement

3

Total 4,174.76

The data is recorded by type of travel e.g. air, rail and road.

Business travel data is not recorded by each licence area; therefore the total business mileage has been apportioned based on the number of indirect staff employed per area. In 2018/19 this was LPN 31%, EPN 38% and SPN 31%. Vehicles owned by UK Power Networks or bought through the business needs self-purchase scheme use the actual CO2 rating to improve the quality and accuracy of data while for privately owned vehicles the DEFRA unknown vehicleaverage conversion factor has been used.

Business kilometres are based on actual kilometres claimed. Fuel card usage is based on actual litres used. Private mileage by fuel card users is reported and paid back. These kilometres are deducted from the overall business mileage figures. Fuel expense claims are a monetary value converted into litres based on the average price of a litre of fuel over the reporting period. Taxi data is in monetary value only. A cost per mile calculation is ascertained using best available methodologies and applied to the SAP and credit card data. There hasbeen a push towards those with company cards using fuel cards. This provides a more accurate measure from a carbon footprinting perspective as it provides a figure in litres of fuel which eliminates the wide variations between cars and drivers in actual carbon used per km.

Air and rail travel data is provided by our external travel provider Clarity as actual kilometres; however the air and rail travel data from SAP and corporate credit cards is in monetary value only. A cost per kilometre calculation is ascertained using the Clarity data and applied to the SAP and credit card data.

Environment and Innovation Commentary10

This includes an assumption that the cost of air and rail transport from SAP data will be the similar to the cost of air and rail transport from Clarity data.

The provision and encouragement of teleconferencing facilities and a business wide attempt to reduce travel generally are measures introduced to reduce business mileage.

Table 2b shows the breakdown and the final figures per licence area submitted to Ofgem.

Business Transport - Passenger ROADKey Area Headcount Percentage of staff tC02eA LPN 774 31% 993.45B EPN 948 38% 1628.42C SPN 773 31% 1202.86

Business Transport - Passenger RAILKey Area Headcount Percentage of staff tC02eA LPN 774 31% 58.23B EPN 948 38% 71.31C SPN 773 31% 58.15

Business Transport - Passenger AIRKey Area Headcount Percentage of staff tC02e

A LPN 774 31% 50.36B EPN 948 38% 61.68C SPN 773 31% 50.30

Fugitive Emissions

SF6 is an electrical insulating gas that is commonly found in modern electrical switchgear. This gas can leak following faults or from old equipment. We continue to actively monitor our assets and have a number of procedures to minimise the escape of SF6 to the environment. We measure the SF6 that is lostin terms of top ups required. Emissions from air conditioning has not been included, consistent with our return in previous years. LPN’s figure, usually very low, increased as a result of leaks at City Road 132kV and Brunswick Wharf 132kV Substations. Projects to replace them are taking place. The circuitbreakers were replaced at 3 of EPN’s sites which suffer from the most gradual leakage and EPN recorded it’s lowest leakage level so far.

Table 3a shows the data by licence area submitted to Ofgem.

Key Data Type/Description

DataSource

ConversionFactor

ConversionFactor

explained




Excluded Data

Scope(GHG

Protocol)

A LPN SF6

LossesEllipse 22800 (kg to

kgC02e)607.62 Measurement 1

B SPN SF6



C EPN SF6




Fuel Combustion

This section refers to the emissions from plant and equipment such as temporary generators used during fault repairs and planned work on the network.

The data is captured through three different sources:

1) Contractors provide standby diesel generators and report the monthly fuel usage of these generators. Though provided by external contractors on an as needed basis, as they are in direct use on our networks, we class these as Scope 1 rather than Scope 3 emissions

2) Data from fuel cards capture the fuel used by company owned plant and equipment.

3) Invoices from the tanker company which fills the bowsers at several of our sites used to fuel our own generators.

The source data is separated by area so no headcount conversion needs to be applied. This is consistent with previous years.

Use of temporary generators is highly weather dependent in both SPN and EPN and 2018/19 featured a range of weather extremes.

Table 4a details our generator and bowser usage.


DataSource

ConversionFactor

ConversionFactor

explained




Excluded Data

Scope(GHG

Protocol)

X Stand-by Dieselgenerators; Plantand Equipment

Invoices;Deliveriesto bowsers;fuel cards

2.97 (red diesellitres tokgC02e)


Table 4b shows the final figures per licence area submitted to Ofgem.

Key Area tC02eA LPN 796.11B SPN 6,033.07C EPN 4,315.39

LossesThese calculations measure units exiting our distribution network compared to units entering from Grid Supply Points and any other sources.Please note the final data for 2018/19 is expected to deteriorate as future reconciliations are received. The current position should therefore not be taken as a forecast of future performance.

Table 5a shows the data by licence area submitted to Ofgem.


DataSource

Conversion Factor

ConversionFactor

explained


(tC02e)


Directmeasurement,Estimated or

Excluded Data

Scope(GHG

Protocol)

A LPN Losses Billing foreach site

0.283 (kWh totC02e)

503,864.60 Measurement


B SPN Losses Billing foreach site

0.283 (kWh totC02e)


C EPN Losses Billing foreach site

0.283 (kWh totC02e)


ContractorsWhen reporting BCF emissions due to contractors in the second half of the worksheet please:

Explain, and justify, the exclusion of any contractors and any thresholdsused for exclusion.

Provide an indication of what proportion of contractors have been excluded. This figure could be calculated based on contract value.

Please provide a description of contractors’ certified schemes for BCF where a breakdown of the calculation for their submitted values is not provided in the worksheet.

If a DNO’s accredited contractor is unable to provide a breakdown of the calculation and has entered a dummy volume unit of ‘1’ in the worksheet please provide details of the applicable accredited certification scheme which applies to the reported values.

Contractor DefinitionContractors were originally selected for inclusion by the size of the financial contract (above a £250k spend) and the scope of work i.e. activities involved indeveloping and operating the electricity network. Where there have been contractual changes, data from the new contractors has been included maintaining a level of consistency within the scope of work.Contractors are reviewed regularly to maintain a consistent approach.As part of our agreement with our contractors they are required to include any data from work that they sub-contract, and to report data that is accumulated as a direct result of works undertaken for UK Power Networks.The data is not gathered by individual DNO so contractor emissions are based on direct operational staff headcount. This year’s operational staff split was 44.1% in EPN, 29.1% in LPN and 26.8% in SPN. The proportion attributed to EPN has increased by 7.1% since 2014/15, due to bringing streetworks and tree trimming functions in-house with some contracting staff being transferred over. This makes an increase in share in contractor emissions for EPN counter intuitive but it maintains consistency with other areas of the Business Carbon Footprint and is the methodology that works best for UK Power Networks and the atypical nature of the London Network.

Table 6a shows a breakdown of tCO2e emitted from our contractors (Y) operational transport.

Key


DataSource

ConversionFactor

ConversionFactor

explained


(tC02e)



Excluded Data

Scope(GHG

Protocol)

Y Diesel Contractorfuel card




Key Area Direct op. staff Percentage of staff tC02eA LPN 809 29.1% 2,967.61B SPN 747 26.8% 2,740.18C EPN 1,228 44.1% 4,504.60


Table 7a shows a breakdown of the amount of tCO2e emitted by our contractors (Y) Business mileage.

Key


DataSource

ConversionFactor

ConversionFactor

explained




Excluded Data

Scope(GHG

Protocol)

Y ContractorBusiness

kms

Contractorrecords

0.181 (Kms tokgCO2e)

(average carfactor)



Business Transport - Passenger ROADKey Area Headcount Percentage of staff tC02eA LPN 809 29.1% 38.92

B SPN 747 26.8% 35.94

C EPN 1,228 44.1% 59.08

Table 8a shows a breakdown of the amount of tCO2e emitted by our contractors (Y) for Plant and Equipment


DataSource

ConversionFactor

ConversionFactor

explained

TotalApr 18to Mar

19(tC02e)



Excluded Data

Scope(GHG

Protocol)

Y Contractor Plantand equipment

Contractorrecords

2.97 (red diesellitres tokgC02e)



Key Area Direct op. staff Percentage of staff tC02eA LPN 809 29.1% 137.26B SPN 747 26.8% 126.74C EPN 1,228 44.1% 208.35


Building energy usageNatural gas, Diesel and other fuels are all categorised as fuel combustion and must be converted to tCO2e on either a Gross Calorific Value (Gross CV) or NetCalorific Value (Net CV) basis. The chosen approach should be explained, including whether it has been adapted over time.

Substation Electricity must be captured under Buildings Energy Usage. Please explain the basis on which energy supplied has been assessed.

Building Energy Usage data is collated from electricity and gas bills received for each location. Staff for the unregulated business are predominantly concentrated on two sites, Chatham depot and Newington House. Half of the electricity consumption at each of these sites is deducted to allow for the unregulated business (D). Offices at the airports for example, where all staff are part of the unregulated business are excluded entirely.

Data is measured in kWh then converted into tCO2e. Large offices, containing many staff with centralised functions are designated as shared offices as opposed to belonging to the DNO in which they are geographically located and their energy usage divided between all 3 DNOs. In shared buildings overall UK Power Networks headcount is used as a factor to determine energy used per DNO. The split used this year is EPN 41%, LPN 30%, SPN 29%. This headcountsplit is only a slight variation on that used for the 2014/15 baseline carbon footprint of EPN 41%, LPN 29%, SPN 30%.

We use the Gross CV conversion factor for gas as recommended by Defra, as it represents the CO2 content of gas as it is delivered to buildings. Gas is a very minor element of our overall footprint.

Savings have been introduced through consolidation of staff into fewer buildingand energy saving initiatives such as the introduction of LED lighting in many offices.

In the absence of current Ofgem guidance on location based vs market based reporting methodologies we have followed a location based system of reporting, using the UK’s annual electricity conversion factor regardless of the type of tariff purchased. Since January 1st 2018 all UKPN’s electricity purchasedhas been on a 100% renewable tariff. Under market-based reporting methodology all of our electricity could therefore be discounted from our business carbon footprint.

Table 9a shows a breakdown by energy type and licence area submitted to Ofgem.


DataSource

ConversionFactor

ConversionFactor

explained

Total Apr18 to Mar19 (tC02e)



Excluded Data

Scope(GHG

Protocol)

A LPNElectricity

Usage

Energy Bills

0.283 (kWh tokgC02e)


B SPNElectricity

Usage

Energy Bills



C EPNElectricity

Usage

Energy Bills



Total 2,819.45


A LPN GasUsage

Energy Bills

0.184(GrossCV)

(kWh tokgC02e)

46.18 Measurement 2

B SPN GasUsage

Energy Bills

0.184(GrossCV)

(kWh tokgC02e)

86.68 Measurement 2

C EPN GasUsage

Energy Bills

0.184(GrossCV)

(kWh tokgC02e)


Total 259.87

A detailed project to analyse electricity usage in our substations is the basis of the reporting and billing of our unmetered supply. Substations were separated into Grid, Primary and Secondary substations and comprehensive analysis of the energy usage of each type undertaken. Typical energy usage on aspects like heating, lighting and security were determined and then applied across thebusiness based on the numbers of unmetered substations of that type in operation. Annual consumption of energy used in unmetered substations has been assessed based on the number and type of plant installed in each licence area. This method has been consistent with that used in previous years.

In 2014/15 an estimated figure was used for our metered substations due to the large number with unread meters. However, after a drive to get meters read and a major push on any properties more than 90 days in arrears on a meter reading, actual data from all metered substations is included in the data for the RIIO ED1 period. This has had the biggest impact in LPN where the majority of substations are metered. On the few occasions where it has not been possible to obtain a reading for the latest month at the time of submission a reading based on the same month the previous year has been inserted to reflect the seasonal nature of electricity usage. This is an improvement on previous years when an average figure for the whole year wasused.

Table 9b shows the substation electricity usage for metered and unmetered sites by licence area.


DataSource

ConversionFactor

ConversionFactor

explained


(tC02e)



Excluded Data

Scope(GHG

Protocol)

A LPNMetered andUnmetered

EnergyBills andAssessed



B SPNMetered andUnmetered




C EPNMetered andUnmetered




Total 13,056.23


E4 – Losses SnapshotAllocation and estimation methodologies: detail any estimations, allocations or apportionments to calculate the numbers submitted.EPN

Transformer replacementsCBA analyses have demonstrated that the following secondary transformer size increments are economically justifiable from a losses perspective:

GMTs, upsize 315kVA to 500kVA, 500kVA to 800 kVA, and 800kVA to 1000kVA. PMTs, upsize 25kVA to 50kVA and 50kVA to 100kVA. Table 1 below captures the relevant numbers and associated losses benefits:

Table 1 : Energy savings attributed to secondary transformers:

Number of transformers MWh savingsPMTs 64 68.1GMTs 49 455.1Totals 113 523.2

In addition to the equipment categories above, the amorphous steel pole-mounted transformers (PMTs) that we have introduced as part of our LDR work have begun to emerge in our equipment records. In total, twelve units were installed in EPN, leading to13 MWh losses savings per annum.

HV CablesWe have developed a new CBA for HV aluminium underground cables during the past year. We shared our methodology with our peers at the ENA Technical Losses Task Group to ensure that the approach is robust and widely acceptable.

During this study, we have demonstrated that we will save 5.94 MWh per annum on average for every kilometre of aluminium cable that we upgrade from 185mm2 to 300mm2 on HV underground feeders’ main lines.

Using these new developments, we have established that we have installed 60.2km of 300mm2 aluminium conductor on HV feeders’ main lines in EPN during the past financial year, leading to an annual energy loss reduction of 357.8 MWh.

LV CablesSimilar to HV cables, we have developed a new CBA for LV underground cables this year. According to this work, we save 6.35 MWh per annum for every kilometre of 185mm2 aluminium cable that we upgrade to 300mm2 on LV main lines. We developed scripts in our GIS System to differentiate between feeders’ main lines and service cables.

Using this new approach, we determined that we have installed 39.4 km of 300mm2 aluminium underground cables on LV feeders’ main lines in EPN during the past fiscal year, leading to an annual energy loss reduction of 250.3 MWh.

Brief overview and summary

Table 2: Summarised results of CBA supported activitiesAsset Category Annual MWh losses improvementLV Cables 250.3HV Cables 357.8Ground-mounted secondary transformers 455.1Pole-mounted secondary transformers 68.1Amorphous Steel pole-mounted transformers 13Total: 1144.3

Energy Loss Reduction in Grid & Primary TransformersTo supplement the information above, we have calculated annual energy loss reductions


attributable to the adoption of newer specification transformers in EPN during the past financial year. We report these figures in the interest of completeness, even though these energy loss improvements are not supported by cost/benefit analyses (CBAs):

Five new Grid Substation Transformers and one new Primary Substation Transformer in EPN are saving 784.3 MWh per annum in terms of energy losses. In addition to these transformers, 205 new PMTs and 371 new GMTs are helping to reduce losses by 1791.3MWh per annum in EPN.

Combining all CBA supported and unsupported figures yields a total a total ongoing annual energy loss reduction of 3719.9 MWh for EPN.

Technical: Calculating Loss ReductionsFor secondary transformers, we first determine each unit’s age and capacity. Next, we reference generic transformer specifications (pre-1955, 1971, 1979, 1984 & ECO 2015),which enable us to quantify the iron and copper losses for each unit. Using assumed levels of utilisation and load loss factors, and assuming that the load on the transformer remains constant even if a larger unit is installed, the old and new annual energy losses are estimated.

Note that loss improvements in amorphous steel transformers are largely due to improvements in iron loss characteristics. Their copper loss characteristics are similar to Eco 2015 units’ specifications.

After calculating the sum of annual iron and copper losses for each new & old unit, we subtract the totals from one another to obtain the total annual energy loss improvement. UK Power Networks recognise that where a larger transformer has been installed it likely corresponds with a load-related increase. However, in the interest of comparing losses on a like-for-like basis, a constant level of utilisation has been assumed.

To identify work that delivered improvements in losses the transformer replacements that did not deliver benefits were dismissed.

Loss improvements in Grid and Primary transformers we calculated in a similar way, except that we used transformers’ test certificates to enhance accuracy. In instances where there were no transformers installed previously, we compared loss performance against a 1984 specification equivalent unit to establish an energy loss differential (given that ECO 2015 transformers are used at present).

For HV & LV cables, we studied a selection of feeders across our three licence areas. We built a tailored model for each feeder, using actual loads and cable lengths. We used a curve published in Northern Powergrid’s LDR Tranche 2 submission to obtain the Load Loss Factor at each node on each feeder. We then calculated losses across each feeder’smain line twice. In the first scenario we assumed that all main line cables are 300mm2 and then 185mm2 in the second instance. The difference between the two scenarios enabled us to determine the average loss reduction per kilometre for each feeder’s mainline.

Once the above-mentioned calculations were complete, we used statistical methods to quantify the average loss improvement across our entire population of feeders. As mentioned earlier, we presented our methodology to peers at the ENA Technical Losses Task Group for scrutiny to ensure that our approach is robust.

LPN




Table 1: Energy savings attributed to secondary transformers:

Number of transformers MWh savingsPMTs 0 0GMTs 91 1154.5Totals 91 1154.5



Using these new developments, we have established that we have installed 54.8km of 300mm2 aluminium conductor on HV feeders’ main lines in LPN during the past financial year, leading to an annual energy loss reduction of 325.5 MWh.


Using this new approach, we determined that we have installed 46.8 km of 300mm2 aluminium underground cables on LV feeders’ main lines in LPN during the past fiscal year, leading to an annual energy loss reduction of 297.5 MWh.


Table 2: Summarised results of CBA supported activities

Asset Category Annual MWh losses improvementLV Cables 297.5HV Cables 325.5Ground-mounted secondary transformers 1154.5Total: 1777.5

Energy Loss Reduction in Grid & Primary TransformersTo supplement the information above, we have calculated annual energy loss improvements attributable to the adoption of newer specification transformers in LPN during the past financial year. We report these figures in the interest of completeness, even though these energy loss improvements are not supported by cost/benefit analyses (CBAs):

Nine new Grid Substation Transformers and one new Primary Substation Transformer in LPN are saving 1019.2 MWh per annum in terms of energy losses. In addition to these transformers, 219 new GMTs are helping to reduce losses by 1483.5 MWh per annum inLPN.

Combining all CBA supported and unsupported figures yields a total ongoing annual energy loss reduction of 4280.2 MWh for LPN.

Technical: Calculating Loss ReductionsFor secondary transformers, we first determine each unit’s age and capacity. Next, we reference generic transformer specifications (pre-1955, 1971, 1979, 1984 & ECO 2015),which enable us to quantify the iron and copper losses for each unit. Using assumed levels of utilisation and load loss factors, and assuming that the load on the transformer remains constant even if a larger unit is installed, the old and new annual energy losses


are estimated.

Note that loss improvements in amorphous steel transformers are largely due to improvements in iron loss characteristics. Their copper loss characteristics are similar to ECO 2015 units’ specifications.


To identify work that delivered improvements in losses the transformer replacements that didn’t deliver benefits were dismissed.




SPN



Table 1: Energy savings attributed to secondary transformers:

Number of transformers MWh savingsPMTs 26 27.1GMTs 26 198Totals 52 225.1

In addition to the equipment categories above, the amorphous steel pole-mounted transformers (PMTs) that we have introduced as part of our LDR work have begun to emerge in our equipment records. In total, two units were installed in SPN, leading to 2.5 MWh losses savings per annum.




Using these new developments, we have established that we have installed 33.2km of 300mm2 aluminium conductor on HV feeders’ main lines in SPN during the past financial year, leading to an annual energy loss reduction of 197 MWh.


Using this new approach, we determined that we have installed 28.3 km of 300mm2 aluminium underground cables on LV feeders’ main lines in SPN during the past fiscal year, leading to an annual energy loss reduction of 179.7 MWh.


Table 2: Summarised results of CBA supported activitiesAsset Category Annual MWh losses improvementLV Cables 179.7HV Cables 197Ground-mounted secondary transformers 198Pole-mounted secondary transformers 27.1Amorphous Steel pole-mounted transformers 2.5Total: 604.3

Energy Loss Reduction in Grid & Primary TransformersTo supplement the information above, we have calculated annual energy loss improvements attributable to the adoption of newer specification transformers in SPN during the past financial year. We report these figures in the interest of completeness, even though these energy loss improvements are not supported by cost/benefit analyses (CBAs):

Three new Grid Substation Transformers and two new Primary Substation Transformers units are saving 1006.8 MWh per annum in terms of energy losses. In addition to thesetransformers, 83 new PMTs and 170 new GMTs are helping to reduce losses by 1016.3 MWh per annum in SPN.

Combining all CBA supported and unsupported figures yields a total a total ongoing annual energy loss reduction of 2627.4 MWh for SPN.

Technical: Calculating Loss ReductionsFor secondary transformers, we first determine each unit’s age and capacity. Next, we reference generic transformer specifications (pre-1955, 1971, 1979, 1984 & ECO 2015),which enable us to quantify the iron and copper losses for each unit. Using assumed levels of utilisation and load loss factors, and assuming that the load on the transformer remains constant even if a larger unit is installed, the old and new annual energy losses are estimated.

Note that loss improvements in amorphous steel transformers are largely due to improvements in iron loss characteristics. Their copper loss characteristics are similar to ECO 2015 units’ specifications.



To identify work that delivered improvements in losses the transformer replacements that didn’t deliver benefits were dismissed.




Please see below a photo of an Amorphous Steel Pole Mounted Transformer:

Programme/Project TitlePlease provide a brief summary and rationale for each of the activities in column C which you have reported against.As we work through the activities detailed within our losses strategy we currently are tackling areas where data is available. As more data becomes available the number of topics that we report will correspondingly increase. We will proactively seek to obtain the relevant data to enable us to report further areas in future RIGs submissions.

Currently we are able to report loss improvements associated with cables and transformers. These activities are split between Asset Replacement, Reinforcement and ‘Other’. Distribution transformers are split further between PMT and GMT categories.


Primary driver of activityIf, in column E, you have selected ‘Other’ as the primary driver of the activity, please provide further explanation.The “Other” category mentioned above captures volumes associated with: Diversions, Quality of Supply, OHL Clearance, Faults, Legal + Safety, Environmental and Connections i.e. those associated with volumes from V3 and V5.

Baseline ScenarioPlease provide a brief description of the ‘Baseline Scenario’ inputted in column K for each activity.The baseline scenario captures the unit cost to do work in the ‘business as usual’ mode. The unit costs of work undertaken to improve network losses are detailed in the respective CBA worksheets.

Use of the RIIO-ED1 CBA ToolDNOs should use the latest version of the RIIO-ED1 CBA Tool for each of the activities reported in column C. Where the RIIO-ED1 CBA Tool cannot be used to justify an activity, DNOs should explain why and provide evidence for how they have derived the equivalent figures for the worksheet. The most up-to-date CBA for each activity reported in the Regulatory Year under report must be submitted. The following CBAs were used and have been sent with the submission:

Generic CBA RIIO ED1_v4 PMTs (final)Generic CBA RIIO ED1_v4 GMTs (final)CBA RIIO ED1 (50kVA 1ph_2W ASPMT) (final)CBA RIIO ED1_v4 HV Cable 185to300mm (final)CBA RIIO ED1_v4 LV Cable 185to300mm (final)

Changes to CBAsIf, following an update to the CBA used to originally justify the activity in column C, the updated CBA shows:

a negative net benefit for an activity, but the DNO decides it is in the best interests of consumers to continue the activity, or

a substantively different NPV from that used to justify an activity that has already begun.

the DNO should include an explanation of what has changed and why the DNO is continuing the activity.

For example, where the carbon price used in the RIIO-ED1 CBA Tool has changed from that used to inform the decision such that the activity no longer has a positive NPV.N/A

Cost benefit analysis additional informationPlease include a reference to the file name and location of any additional relevant evidence submitted to support the costs and benefits inputted into thisworksheet. This should include the most recent CBA for each activity reported in column C in the Regulatory Year under report. The following CBAs were used and have been sent with the submission:

Generic CBA RIIO ED1_v4 PMTs (final)Generic CBA RIIO ED1_v4 GMTs (final)CBA RIIO ED1 (50kVA 1ph_2W ASPMT) (final)CBA RIIO ED1_v4 HV Cable 185to300mm (final)CBA RIIO ED1_v4 LV Cable 185to300mm (final)


E5 – Smart MeteringAllocation and estimation methodologies: detail any estimations, allocations or apportionments to calculate the numbers submitted.N/A

Actions to deliver benefitsDetail what activities have been undertaken in the relevant regulatory year to produce benefits of smart metering where efficient and maximise benefits overall to consumers. At a minimum this should include:

A description of what the expenditure reported under Smart Meter Information Technology Costs is being used to procure and how it expects this to deliver benefits for consumers.

A description of the benefits expected from the non-elective data procured as part of the Smart Meter Communication Licensee Costs. TheDNO should set out how it has used this data.

A description of the Elective Communication Services being procured, how it has used these services, and a description of the benefits the DNO expects to achieve.

N/A

Calculation of benefitsExplain how the benefits have been calculated, including all assumptions used and details of the counterfactual scenario against which the benefits are calculated.N/A

Use of the RIIO-ED1 CBA ToolDNOs should use the latest version of the RIIO-ED1 CBA Tool for each solution reported in the worksheet in the Regulatory Year under report. Where the RIIO-ED1 CBA Tool cannot be used to justify a solution, DNOs should explain why and provide evidence for how they have derived the equivalent figures for the worksheet. The most up-to-date CBA for each activity reported in the Regulatory Year under report which are used to complete the worksheet must be submitted. N/A

Cost benefit analysis additional informationPlease include a reference to the file name and location of any additional relevant evidence submitted to support the costs and benefits inputted into thisworksheet. This should include the most recent CBA for each solution reported in the Regulatory Year under report.N/A

E6 – Innovative SolutionsAllocation and estimation methodologies: detail any estimations, allocations or apportionments to calculate the numbers submitted.UK Power Networks now has 30 Innovative Solutions in the E6 table. We have put all the commentary requirements into an appendix to this commentary entitled “UKPN E6 commentaries merged”.


GeneralFor each of the solutions please explain:

In detail what the solution is, linking to external documents where necessary.

How this is being used, and how it is delivering benefits. What the volume unit is and what you have counted as a single unit. How each of the impacts have been calculated, including what

assumptions have been relied upon.See “UKPN E6 commentaries merged”.

Use of the RIIO-ED1 CBA ToolDNOs should use the latest version of the RIIO-ED1 CBA Tool for each solution reported in the Regulatory Year under report. Where the RIIO-ED1 CBA Tool cannot be used to justify a solution, DNOs should explain why and provide evidence for how they have derived the equivalent figures for the worksheet. The most up-to-date CBA for each solution reported in the Regulatory Year under report which are used to complete the worksheet must be submitted. See “UKPN E6 commentaries merged”.

Changes to CBAsIf, following an update to the CBA used to originally justify the activity in column C, the updated CBA shows a negative net benefit for an activity, but the DNO decides it is in the best interests of consumers to continue the activity,the DNO should include an explanation of what has changed and why the DNO is continuing the activity.See “UKPN E6 commentaries merged”.

Calculation of benefitsExplain how the benefits have been calculated, including all assumptions used and details of the counterfactual scenario against which the benefits are calculated.See “UKPN E6 commentaries merged”.

Cost benefit analysis additional informationPlease include a reference to the file name and location of any additional relevant evidence submitted to support the costs and benefits inputted into thisworksheet. This should include the most recent CBA for each solution reported in the Regulatory Year under report.See “UKPN E6 commentaries merged”.

E7 – LCTsAllocation and estimation methodologies: detail any estimations, allocations or apportionments to calculate the numbers submitted.Heat Pump Data

Where the MPAN is omitted, records have been allocated to a DNO in accordance with the postcode. Where postcode is also unavailable records have been spread across the three DNOs in accordance with the proportions observed among records successfully mapped to a DNO. There were only 0.5% of records for which neither the MPAN nor postcode was specified.

Where system capacity is omitted for a record, it has been estimated by the average size of known heat pumps connected to the given DNO. Where the DNO is unknown, the capacity is estimated by the average size of all known heat pumps connected to our networks.

Capacity of NDRHI originally given in kWth, is converted to kW by using Coefficient ofPerformance for each technology (water, air, and ground source heat pump).


Electric Vehicle Charge Point Data

In the event of the system size being indeterminable or unclear for a given record, it was either estimated on the basis of other available information or assumed to be the most common system size (32A).

Where the installation date is unavailable, in the absence of evidence to the contrary the installation date is assumed to fall in the regulatory year in which the application was received.

Charge points of 16A or less have been reported as slow charge. Charge points of greater than 16A have been reported as fast charge.

For the EV HomeCharge Scheme, as the capacity of each charge point was not provided,it was necessary to infer the capacity from the information provided. The primary basis for inferring the capacity was the charge point model. In some cases the model could not be determined with certainty.

Where model information is available but does not enable unambiguous mappingto a particular model, the model has been assumed to be the model with the most similar name to the given information.

Where no model information is available, but manufacturer information is available, the model has been assumed to be the most common model for the given manufacturer.

Where no model or manufacturer information is available, the model has been assumed to be the most common model under the schemes (the Rolec EVWP2026).

Where possible, the capacity of each approved charge point model was obtained from the manufacturer. Where the model capacity could not be obtained from the manufacturer or inferred from the model name, it was assumed to be 7kW as this is by far the capacity most commonly occurring in the data provided.

For the Workplace Charging Scheme, where the capacity of a charge point was not provided, it was estimated to be the average of known capacities in the data provided.

For both the EV Home Charge and Workplace Charging Schemes, no estimation of installation date or DNO was necessary.

Zap-Map Public Charge Point Data

As the capacity information for public charge points was limited to the range of slow (3kW), fast (7-22kW) and rapid (≥43kW) charge points, the aggregate capacity connected to each DNO was estimated using the following assumptions:

1. All slow chargers were assumed to be 3.7kW and ≤16A.2. On the basis of data from the Workplace Charging Scheme, all fast charge points

were assumed to be 10kW and >16A. 3. All rapid chargers were assumed to be 43kW and >16A. This represents the

minimum capacity of a rapid charge point as defined by Zap-Map.

As the Zap-Map public charge point information provided only the total change points connected by DNO as at March 2019 and previously at March 2018, the split across RIIO-ED1 up to 2018 was assumed to be in line with that observed in the EV Home Charge Scheme. This split was performed separately for the count and capacity data, as the split may be different for different quantities.

Distributed Generation

Sites less than or equal to 11.04kW have been treated as G83 and sites greater than 11.04kW have been treated as non-G83.

In the absence of information indicating whether a site is connected to the primary orsecondary network it has been assumed that sites less than or equal to 1MW are connected to the secondary network and sites greater than 1MW are connected to


the primary network. As some of the data sources are overlapping and it is expected that the data relating

to some sites may not be precisely accurate, if two records are sufficiently similar they have been considered to relate to the same site and the data believed to be most reliable has been used in all calculations. It was necessary to apply an element of judgment in this review process.

In the case of an unpopulated or incomplete data field for records believed to represent true sites not represented elsewhere, the missing field has been estimated based on the best available information. The most common missing fields were postcode and generation type. Such estimation was not frequently necessary.

LCT – Processes used to report data(i) Please explain processes used to calculate or estimate the number and size of each type of LCT. (ii) If any assumptions have been made in calculating or estimating either of these values, these must be noted and explained. (i)The below processes are performed for each DNO.

Heat Pump Data

1. Obtain Renewable Heat Incentive data for UKPN’s licence areas from Ofgem in accordance with the Data Sharing Agreement signed on 30th May 2017.

2. Use MPAN and/or postcode to map each record to the corresponding DNO.3. Determine regulatory year of installation based on the commissioning date.4. Calculate the quantity and aggregate capacity of installed systems by DNO and

regulatory year.

Electric Vehicle Charge Point Data

1. Obtain EV Home Charge and Workplace Charging Scheme databases from the Office of Low Emission Vehicles as per the established data sharing agreement.

2. For the EV Home Charge Scheme, use the best available information to map each record to a charge point model eligible for the given scheme.

3. Use the UK Power Networks Model Capacity Database to determine the capacity and current of each charge point.

4. For the Workplace Charging Scheme, where the charge point capacity is not provided, estimate it by the average of known capacities in the data provided.

5. Categorise each charge point model as Slow Charge (≤16A) or Fast Charge (>16A).

6. Determine the regulatory year of installation from the installation date.7. Determine the DNO from the postcode.8. Calculate the required summary of number and aggregate capacity of slow and

fast charge points by DNO and regulatory year.9. Obtain number of slow, rapid and fast public charge points by DNO from Zap-

Map.10. Estimate the aggregate capacity by DNO based on conservative assumptions

and average capacity data from Workplace Charging Scheme.11. Estimate the number and capacity of slow and fast public charge points

connected in each DNO by regulatory year on the basis the annual connections observed in the EV Home Charge Scheme data.

12. Sum the summaries of the three input datasets to obtain the total number and capacity of slow and fast charge points connected in each DNO by regulatory year.

Distributed Generation

1. Obtain from Ofgem the FiT Database with MPAN in accordance with the data sharing agreement finalised in 2016 and the Renewables Obligation Accredited Stations Public Report.

2. For the FiT database, map each record to the appropriate DNO on the basis of


the MPAN.3. For the Renewables Obligation database, map each record to the appropriate

DNO on the basis of the postcode provided or other available information, such as the site description.

4. For each dataset, append any records identified from UK Power Networks’ Connections data that do not appear to be included in the FiT and ROC databases.

5. Map the appended records to the appropriate DNO on the basis of the postcode or other available information.

6. For each dataset, determine the regulatory year from the commissioning date orinstallation date. Where such a date is unavailable, estimate it on the basis of the best available data.

7. Determine whether each site was connected under G83, and whether to the primary or secondary network in accordance with the assumptions outlined under Extent of manual intervention in the method statement.

8. Populate E7 as required.

(ii)

All assumptions are outlined, together with the estimation methodologies, under Allocations and estimation methodologies, above.

LCT - UptakePlease explain how the level of LCT uptake experienced compares to the forecast in your RIIO-ED1 Business Plan and the DECC low carbon scenarios. This must also include any expectation of changes in the trajectory for each LCT over the next Regulatory Year in comparison to actuals to date.In the BPDT we expected over 33,000 PV units to connect to the secondary network in 2018/19 whereas 4,936 units actually connected. We highlighted in previous years that the changes in both the Feed-in Tariff and Renewables Obligation schemes would resultin lower volumes. We have seen a significant reduction since 2015/16 reflecting those changes, although the number of installations is notably higher than last year, likely due to consumers attempting to utilise the Feed-in Tariff before it was discontinued in March 2019. The fall in distributed generation is particularly true in the small-scale generation market where volumes have decreased by 88% since 2015/16. We expect no significant increase in volumes in the next regulatory year, as the tariff rates associated with the Smart Export Guarantee for all suppliers may not be known until 1 January 2020.

In our original business plan, we expected over 35,000 heat pumps to connect in 2018/19 whereas 1,156 actually connected, 17% less than in 2017/18. As we highlighted in previous years, the BPDT assumption was that in 2016 the Zero Carbon Homes policy would have been implemented which would have kick started the heap pump deployment. The Committee on Climate Change has highlighted that the UK heat decarbonisation policy needs to be rethought if the 2050 heat decarbonisation targets are to be achieved. There are proposals to take homes off the gas grid during the 2020’sas outlined in the Clean Growth Strategy, however until these become policy we do not expect to see significant growth in heat pump installations.

In the BPDT we predicted over 34,000 charge points connecting in 2018/19 whereas ourrecords show that 7,967 actually connected, 17% more than in 2017/18. However, the volume of electric vehicles registered in 2018/19 is thought to be approximately 18,000,an increase of approximately 87% on the 2015/16 value of 9500. This growth is being driven by a focus on air quality in urban areas, as demonstrated by the introduction of London’s ULEZ, as well as increasing popularity of electric vehicles. Furthermore, the standardisation of installing and connecting charge points is expected to streamline to process, allowing charge points to be installed at a greater rate than seen historically. Consequently, we expect the number of electric vehicle charge points to increase in the next regulatory year.


We currently have 237MW of grid scale storage connected to our network; 131MW in EPN, 3MW in LPN, and 103MW in SPN. We believe that this capacity should be reflected in the E7 submission tables, as there is currently no visibility for storage assets.


environment and innovation commentary v5 · 2019-10-24 · two other substations were fitted with...

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