DNSP Outputs for Use in Economic Benchmarking

1. DNSP Outputs for Use in Economic Benchmarking AER Economic Benchmarking Workshop #1 13 March 2013 Denis Lawrence and John Kain

2. Economic benchmarking • Compares the overall quantity of outputs produced to the overall quantity of inputs used and costs incurred across DNSPsand/orover time • Holistic, tops-down measure • Range of techniques used: total factor productivity (TFP), multilateral TFP, econometric cost functions, data envelopment analysis, stochastic frontier analysis • Use in building blocks regulation: • Initial screening – accept revealed cost vs detailed analysis • Is base year expenditure efficient? • Efficiency improvement to be included in rates of change • Benchmarking reports

3. Data requirements • Require data on the price and quantity (and hence value) of all outputs and inputs and on the quantities of operating environment variables (noting that output prices may be shadow prices where the output is not explicitly charged for). • This then allows any of the key economic benchmarking methods to be implemented. • Given its tops-down nature, it is important to concentrate on a relatively small number of key outputsin economic benchmarking • Desirable to have robust and consistent data • Data backcasting may be possible and facilitate early use

4. Billed vs functional outputs (1) • Billed outputs are those items an NSP actually charges customers for • NSP charging practices have typically evolved on an ease of implementation basis rather than on a network cost-reflective basis • High proportion of charges are on energy throughput • Dimensions that customers may value such as reliability, continuity or speedy restoration after any interruption are not explicitly charged for • Functional outputs are all those services NSPs provide to customers which are valued by customers (of which billed outputs are a subset)

5. Billed vs functional outputs (2) • Under building blocks the revenue requirement is set based on the DNSP being expected to meet a range of performance standards and other deliverables required to meet the expenditure objectives • Prices then have to be consistent with broad regulatory pricing principles • In the case of building blocks, it will be important to measure output (and hence efficiency) in a way that is broadly consistent with the output dimensions implicit in the setting of NSP revenue requirements • Points to functional rather than billed outputs specification but sensitivity analysis important • Need criteria to choose functional outputs to include

6. Output selection criteria • the output aligns with the NEL and NER objectives which are to: • meet or manage the expected demand for standard control services • comply with all applicable regulatory obligations or requirements associated with the provision of standard control services • maintain the quality, reliability and security of supply of standard control services, and • maintain the reliability, safety and security of the distribution system through the supply of standard control services. • the output reflects services provided to customers, and • the output is significant.

7. The short list • customer numbers (total or by broad class or by location) • measured maximum demand and contracted maximum demand for those customers charged on these bases • system capacity (taking account of both transformer and line/cable capacity) • reliability (SAIDI and/or SAIFI), and • throughput (total or by broad customer class or by location).

8. Billed outputs • Energy delivered • Bulk of charges but little impact on costs • Proxy for load? • Road analogy • Customer numbers • Proxy for fixed output components • Need to disaggregate? • Demand-based outputs • Industrial customers usually charged on basis of actual peak demand or reserved capacity • Data available but not generally reported • System proxies problematic

9. Other functional outputs (1) • System capacity • Captures capacity to deliver (road analogy) • Line capacity or line and transformer capacity? • How can DSM and embedded generation be allowed for? • Peak demand • Important cost driver but customers see reliability at peak as relevant output • SA Power Networks advocates use of spatial rather than system peak • Volatility and incentive effects • Reliability • Important to customers • Some practical issues to be resolved • Should other aspects of service quality be included?

10. Other functional outputs (2) • System security • Important cost driver and can provide an ‘insurance effect’ but is it what customers see? • Can a satisfactory objective summary measure be developed? • Electricity safety and quality • Of obvious importance but generally a prerequisite • More important to include other outputs? • Broader obligations • Can include environmental, customer satisfaction and social obligations • Hard to measure • Materiality?

11. Output weights • Need weights to aggregate outputs into an aggregate output measure or to assess shadow weights estimated by the model • Revenue weights or cost-reflective weights • Forming output weights on a cost–reflective basis is likely to provide the most practical option going forward • Cost function methods provide one way of doing this • Information DNSPs use to demonstrate compliance with regulatory pricing principles and for internal planning purposes might provide another means of forming cost-reflective output weights • Other methods may be required to allocate a value to reliability outputs

12. The short list • customer numbers (total or by broad class or by location) • measured maximum demand and contracted maximum demand for those customers charged on these bases • system capacity (taking account of both transformer and line/cable capacity) • reliability (SAIDI and/or SAIFI), and • throughput (total or by broad customer class or by location).