Electricity distribution service quality. Metrics and objectives: A literature survey

Transcription

1 Electricity distribution service quality Metrics and objectives: A literature survey August 2012

2 For further information about this response please contact: Luke Berry Principal Engineroom Infrastructure Consulting Pty Ltd ABN ACN Phone:

3 [This page left intentionally blank] 3

4 Contents Electricity distribution service quality 1 Contents 4 Glossary 6 Executive summary 8 Part 1: Introduction 10 Part 2: Service quality metrics and definitions 13 Part 3: Importance and features of electricity distribution service quality 17 Part 4: Different preferences for service quality among different customer classes 19 Part 5: Trade-offs between service quality and price 21 Part 6: Current framework for regulation of service quality 24 International Experience 28 Part 7: Ways of measuring customer preferences for service quality 30 Model-based approaches 32 Survey-based approaches 33 Australian experience 34 International experience 35 England and Wales 35 New Zealand 35 Part 8: Service quality incentive schemes 37 Part 9: Adjusting service quality over time 40 Part 10: Regulatory lessons 41 Part 11: Literature survey 42 4

5 MCE 42 National Framework 42 AER 42 NSW (IPART) 44 Victoria (ESC) 44 Queensland (QCA) 45 Western Australia (ERA) 46 South Australia (ESCOSA) 46 Tasmania (OTTER) 46 Consumer Preference studies 47 International Studies 48 Performance Monitoring Reports 51 5

6 Glossary AC AEMC AEMO AER CAIDI CBD DC GDP GSL Hz IPART kwh MAIFI MCE MVA alternating current Australian Energy Market Commission Australian Energy Market Operator Australian Energy Regulator Customer Average Interruption Duration Index (means the average length on an interruption for an average customer) central business district direct current gross domestic product guaranteed service level hertz (the number of cycles per second of an alternating current) Independent Pricing and Regulatory Tribunal kilowatt-hour Momentary Average Interruption Frequency Index (measures momentary interruptions Ministerial Council on Energy megavolt ampere (a measure of apparent power) 6

7 MWh megawatt-hour N-1 a network planning standard requiring the network to continue to function without interrupting any customers following the loss of one network component, or one credible contingency NEM NER PBR SAIDI SAIFI STPIS USE VCR VOLL WTA WTP National Electricity Market National Electricity Rules performance based rates System Average Interruption Duration Index (measures the total length of interruptions per year for an average customer) System Average Interruption Frequency Index (measures the number of interruptions per year for an average customer) service target performance incentive scheme unserved energy value of Customer Reliability value of Lost Load willingness to accept willingness to pay 7

8 Executive summary The quality of electricity distribution services is a critical aspect of the provision of electricity distribution services. This report summarises the issues involved in regulating electricity distribution service quality and the literature and studies around those issues. The quality of electricity distribution services can be difficult to define and measure. Typically service quality measures include reliability (measured in terms of both the total time off supply and the number of interruptions), 1 quality of supply (encompassing voltage fluctuations, continuous low voltage, and waveform distortion), and customer service (encompassing such matters as call centre performance, dealing with complaints, billing, and timeliness of new connections). Typically aspects of service quality, and in particular reliability measures, are set in legislation or subordinate legislation. The standards vary from jurisdiction to jurisdiction. The Australian Energy Regulator (and the Economic Regulation Authority in Western Australia) sets incentive arrangements for electricity distributors. Complicating the picture is the fact that electricity distribution services are different to most services provided in typical markets. Electricity distribution services are provided jointly to many customers and it would rarely be feasible for customers individually to negotiate with distributors over quality levels. Additionally, industrial and commercial users are likely to value reliability much more highly than residential customers because of the major impact that interruptions can have on business. 1 There are also increasing moves to measure the number of momentary interruptions to supply. 8

9 A major challenge for regulators is to determine whether to provide incentives in regulatory arrangements to improve service quality and how to set such arrangements. On one hand, where regulators set the maximum prices that electricity distributors can earn, distributors may be tempted to underspend on service quality in order to maximise profits. 2 On the other hand, if distributors are awarded revenues on a cost plus basis, then they may be tempted to over-invest in or gold-plate the network, providing higher reliability but at an unacceptable cost. The Ministerial Council on Energy recently directed the Australian Energy Market Commission to investigate the electricity distribution reliability framework because of concerns over its upward impact on prices. The Council noted that in NSW the application of reliability standards has substantially increased the expenditure of distribution network businesses on infrastructure. Ideally, in setting incentive arrangements around service quality, regulators would like to have information on customers willingness to pay for improvements and on distributors costs of making improvements. There have been a number of measures of customer willingness to pay for service quality improvements, most notably in Victoria and South Australia, as well as some other studies around the world. The choice of the method for measuring customers willingness to pay is important, as different methodologies can provide significantly different answers. One approach is to examine the actions customers take to avoid or minimise interruptions, while another approach is to survey customers on their estimates of the costs of interruptions to them or what they would pay to improve reliability. Information on distributors costs for improving reliability is relatively rare. Where such studies exist, they may not be applicable to other networks since the costs of improving service quality vary widely among networks based on factors such as the density of user demand. In setting incentive arrangements, regulators will also need to grapple with design issues such as whether to set strong or weak incentives to improve service quality, accommodating changes in user preferences over time, and deciding whether to permit some level of negotiation among users and distributors in relation to service quality and prices. 2 Revolo

10 Part 1: Introduction Electricity distribution service quality is a critical, but sometimes neglected, aspect of distribution pricing and regulation. Service quality is an integral part of the package of services and prices that electricity users consume. Electricity distribution service quality is important because: It affects the value of the price/quality proposition provided by the distributor; and It affects the viability of economic activities that depend on electricity. Reliability is one aspect of a broader range of distribution service quality measures. Other measures include quality of supply, timeliness of new connections, and call centre performance. 3 Distribution activities have a bigger impact on the customer experience with electricity compared with smaller impacts from generation, transmission, and retailing activities. 4 The challenge for markets and policy-makers is to find the optimal trade-off between service quality and tariffs. The picture is complicated by a range of factors. Firstly, there is little available information on the costs to a distributor of improving service quality. Secondly, distributors have little information on customers willingness to pay. Thirdly, customer preferences vary considerably while distribution services are traditionally 3 Holt Ajodhia and Hakvoort 2005 suggests over 90 per cent of interruptions relate to the distribution system. 10

11 supplied at a single service standard to all or most of the users within an area. The distributor s choice of service quality level is complicated by the relatively heterogeneous mix of preferences from industrial, commercial, agricultural, and residential customers. Fourthly, consumers preferences are unlikely to be stable over time. Instead they are likely to change in line with the types of electrical applications that users have connected within their houses or places of business. Fifthly, where electricity prices are regulated on a price or revenue cap basis but service quality is relatively less regulated, then there will be a temptation for distributors to save costs by reducing operating and capital expenditure on service quality (assuming that under the regulatory arrangements, underspending is retained by the distributor). 5 Alternatively, where electricity prices are regulated on a rate of return basis, distributors may seek to gold-plate assets through excessive investment. 6 Electricity distribution service quality is topical at present in terms of its capacity to influence the price of electricity. The Ministerial Council on Energy (MCE) 7 noted in a June 2011 communiqué that: Energy Ministers considered the drivers of recent electricity price increases and noted that distribution network investment is a large contributor to these rises. Energy Ministers agreed to direct the AEMC to conduct a review of the distribution reliability standards framework in the National Electricity Market, subject to the finalisation of the terms of reference. 8 The MCE also noted the recent finding of the Independent Pricing and Regulatory Tribunal (IPART) of New South Wales that the application of reliability standards in that state has substantially increased the expenditure of distribution network businesses on infrastructure. 9 5 Ter-Martirosyan 2003, Ajodhia and Hakvoort Ajodhia and Hakvoort The Ministerial Council on Energy has since been incorporated into the Standing Council on Energy and Resources. 8 See Energy and Resource Ministers Communiqué, 10 June 2011, accessed 2 August MCE letter of direction to AEMC, 30 August

12 This paper discussed the issues involved in regulation of electricity distribution service quality, and identifies source material on the issues raised. It is structured as follows: Part 2 discusses electricity distribution service quality metrics and definitions; Part 3 discusses the importance of electricity distribution service quality and some of its unusual features; Part 4 discusses the problem posed by the fact that different customers have different preferences for service quality; Part 5 discusses trade-offs between service quality and price; Part 6 discusses the current framework for regulation of service quality; Part 7 discusses ways of measuring customer preferences for service quality; Part 8 discusses service quality incentive schemes; Part 9 discusses changes in service quality over time and mechanisms to cater to these changes; Part 10 draws out some regulatory lessons from the review; and Part 11 provides a consolidated literature review. 12

13 Part 2: Service quality metrics and definitions The quality of electricity supply has a range of different dimensions. Many of the key service quality measures are primarily determined by the performance of the distribution network. For example, for customers connected to the distribution network, reliability performance is mainly determined by the performance of the distribution network. Interruptions caused by generation or transmission factors are typically very low compared to interruptions caused by distribution factors. 10 The Standing Committee on National Regulatory Reporting Requirements has devised standardised service quality reporting measures for electricity distribution networks in Australia Ajodhia and Hakvoort In an Australian context, typically interruptions caused by generation and bulk transmission factors together are less than 10 minutes per year in Australia, while the Brattle Group report for AEMC found that distribution interruptions generally lay between 150 and 350 minutes per year across different Australian jurisdictions: Brattle 2012, p Utility Regulators Forum The paper was called a discussion paper but represents the final position of the Standing Committee on National Regulatory Reporting Requirements. 13

14 Their metrics encompass three broad categories of measures: Reliability; Quality of supply; and Customer service. 12 Reliability encompasses the aspect of outages on the distribution system (excluding outages attributable to generation or transmission causes). Outages can either be planned by the network (for example, for the purpose of network construction, augmentation, or maintenance) or unplanned (e.g. due to weather, equipment faults). The focus is typically on unplanned outages. As customers focus on both the number of outages and the length of outages, outages are typically reported in terms of: Total time off supply averaged across the customer base (known as SAIDI or System Average Interruption Duration Index); The number of outages per period averaged across the customer base (known as SAIFI or System Average Interruption Frequency Index); The average length of an interruption averaged across the customer base (known as CAIDI or Customer Average Interruption Duration Index). CAIDI can be calculated by dividing SAIDI by SAIFI so it is sometimes omitted from reported numbers; and The number of momentary outages (say under one minute) (known as MAIFI or Momentary Average Interruption Frequency Index). These momentary interruptions are normally excluded from SAIDI or SAIFI figures to prevent double-counting. 13 Reliability performance typically varies across the network. The central business district and urban areas typically perform more reliably than rural or remote areas. This is because urban areas have greater interconnection among distribution lines (or feeders ), meaning customers are supplied via a number of different distribution pathways and thus are less likely to be cut off and more likely to be restored quickly. CBD and urban distribution networks can be thought of as a spider-web of interconnection of distribution feeders, where cutting off an individual line may not interrupt supply to customers. In rural and remote areas, the distribution system is more radial, with fewer interconnections and thus it is more likely that interruption to a feeder will interrupt supply to customers. The denser level of interconnection in urban areas reflects the 12 See Utility Regulators Forum 2002, pp , Appendix Compare Meyrick and Associates and Pacific Economics Group 2003, and Ter-Martirosyan

15 denser pattern of use and provides for higher levels of reliability and quicker restoration in the event of an interruption. Due to the variations in reliability performance over different types of areas or feeders, reliability is reported in Australia for CBD feeders, urban feeders, rural short feeders (under 200km), and rural long feeders (over 200km). The Australian Energy Regulator (AER) reports in its annual State of the Energy Market on reliability performance across the different distribution areas in Australia. The most recent statistics for SAIDI and SAIFI are in the 2011 edition. 14 Quality of supply encompasses the quality of the electricity supplied over a line to a customer. Though quality of supply is sometimes defined to include outages, generally quality of supply captures situations where supply continues to a customer but varies from the normal characteristics of supply. In Australia, electricity is normally supplied at 240 volts by alternating current (AC) on a smooth sine wave (sinusoidal) at 50 hertz (Hz). 15 In essence, in AC supply the electrons move back and forwards in supplying power and in doing so form a smooth sinusoidal waveform. Alternating current at 50 Hz means that the electrons move back and forwards at 50 times or cycles per second. Diagram 1 below illustrates a sinusoidal wave at 1 hertz. Diagram 1: Sinusoidal waveform at 1 Hz 14 See table 2.4, p The other main form of electrical power supply is direct current or DC. 15

16 Quality of supply is impaired when external factors affect either the voltage levels or the smooth waveform of the AC current. Variations could include: Voltage swells, surges, spikes, and dips; More continuous low voltage supply situations brown-outs ; Distortions to the sinusoidal waveform, for example, notching, which involves dropping out of the smooth signal for very short periods; Interference with TV or radio broadcasts; and Humming and noise. These variations can affect the customer s experience. They can also affect the operation of electrical equipment, potentially causing permanent damage to more sensitive electrical equipment. Customer service covers measures of how successfully distributors have dealt with customers problems, enquiries and requests for services. 16 The national service quality reporting system focuses on the following aspects of customer service: Network contact centre performance (how promptly calls are answered, the number of abandoned because there are too many prior calls in the system waiting to be answered; Appointment punctuality; Timely provision of connections; Maintaining street lights (average time to repair faulty street lights, and instances of delay in repairing street lights); Instances where the electricity distributor makes payments for not meeting guaranteed service levels; Providing adequate notice of any planned interruptions; and Complaints (reporting of the number of complaints over a range of categories, and the average time to resolve complaints for category of complaint). 16 Holt

17 Part 3: Importance and features of electricity distribution service quality Consumers are accustomed in most markets to make judgments about the relative quality of competing products as part of their purchasing decisions. The quality of a product is an integral aspect of the purchasing decision for consumers. Many markets offer differentiated quality levels over a product. For example, in the market for cars, buyers can purchase cheaper cars that are considered of lower quality (against some measure) or more expensive cars of higher quality. That market tends to fragment in to a number of submarkets where cars of a certain quality compete with each other. However, in electricity markets, consumers rarely, if ever, have an explicit choice regarding the quality of service they receive in their electricity supply. 17 Moreover, it does not tend to be feasible for electricity distributors to provide differentiated service levels to different users. Within a given area, it would normally be cost-prohibitive to provide varying service levels to different customers. It may be 17 Ignoring, for the moment, that consumers may tend to relocate at the margin to areas where service quality, for example reliability, is expected to be higher. 17

18 practical on a limited scale to provide higher or lower levels of service to all the users in a particular area, for example by investing more heavily in the network in that area. 18 This means that in broad terms it is not practical for an individual user (except perhaps a very large user in particular circumstances) to negotiate with a service provider around service standards as part of the wider negotiation around tariffs. Generally arrangements around service standards have to be jointly negotiated across the network, or across large areas of the network. Often there is no practical negotiation, with users accepting the level of service quality that is provided. The negotiation, to the extent it occurs, happens as part of the regulatory process or as a result of political pressure A distributor could offer to provide higher levels of reliability in, for example, a given areas in exchange for user agreement to pay higher tariffs. The distributor s offer would likely need to be seen as credible to attract user interest in paying higher tariffs. 19 For example, the Brattle Group report notes that several of the distributors are Stateowned and have been expected to implement the findings of enquiries into reliability without explicit direction. Brattle cites in particular the enquiries in 2004 and 2011 in Queensland in ENERGEX and Ergon: Brattle Group 2012, p

19 Part 4: Different preferences for service quality among different customer classes In examining preferences for different levels of service quality, it is noticeable that different classes of customers attach different valuations to service quality. In broad terms, customers can be divided into three classes: Industrial; Commercial; and Domestic (or residential) classes. Agricultural customers are sometimes considered as a separate class, for example in the 2002 and 2007 VENCorp studies in Victoria. Studies of the value that customers place on reliability in Australia have found that the different customer classes face significantly different values on reliability. For example, the 2007 study from VENCorp performed by CRA found that: The commercial and industrial sectors VCR dominate the composite State VCR [the value that customers place on reliability], contributing 63% and 25% per cent respectively to the final 2007 VCR estimate. These sectors also dominated the Monash and CRA 2002 studies CRA 2007, p

20 Diagram 2 shows the costs of interruptions across different customer classes based on the 2007 VENCorp study. Diagram 2: Costs of interruptions to different customer classes in Victoria (2007) Note: No data was collected for residential customers for 20 minutes and 2 hours. These data points were joined to create an indicative line. The significant differences in the valuations placed on reliability pose questions for policy-makers and regulators, such as: Should networks invest more to improve service quality (and in particular reliability) in areas of the network containing a high proportion of industrial and commercial customers? Should there be higher bonuses and penalties under incentive arrangements for improving reliability in areas with high proportions of commercial and industrial customers? Should customers that place a higher weight on reliability contribute more to improvements in reliability? 20

21 Part 5: Trade-offs between service quality and price As in all markets, higher levels of service quality are associated with higher prices. A paper by Coelli et al 2012 found that there is a significant trade-off between reliability and price, with price rising as reliability rises. 21 In the electricity market, customers are sometimes reluctant to accept that there is a trade-off between service quality and price. 22 This may be to some extent because their perceptions are affected by the idea that electricity is provided by government and that there should be some form of subsidy for service quality or that market principles do not apply in relation to provision of government services. 23 More broadly, where customers have not been able to choose level of service quality in the past it is difficult to become acquainted with the notion of choosing service qualities levels through some sort of market or regulatory mechanism Coelli et al Nonetheless such trade-offs are unavoidable for electricity distribution networks. Growitsch et al 2005 shows the interaction between electricity distributor operating and capital expenditure and service quality. 23 McKenzie and Mookherjee The idea of choice here is at the aggregate customer level rather than the individual customer level. 21

22 Customer perceptions may also be affected by the fact that service quality is not offered at an individual level and thus it is not possible for customers to obtain their individual choice around service quality levels. Customers may perceive they will be able to obtain high levels of service through a cross-subsidy from other users. These difficulties are magnified by the fact that the trade-offs between service quality and cost are not easily observable in electricity distribution services. Generally only distributors are likely to have a clear idea of the costs and possibilities for improving service quality within their area. Comparisons with other distributions can provide guidance on these costs but there will tend to be a number of specific factors operating within a distribution area that will limit confidence in comparator studies. 25 Thus, in order to properly set service quality incentive schemes regulators need to know both the cost of making improvements and the willingness of customers to pay for those improvements. In an ideal market the incentive scheme would drive performance towards the optimum point, i.e. the point at which the two curves intersect. Diagram 3 illustrates this point of intersection where the marginal benefits of spending on service quality coincide with customer willingness to pay for service quality improvements. 26 Diagram 3: Willingness to pay, marginal costs of improving reliability, and the optimal quality level Source: modelled on Jamasb et al 2010, p Brattle Group 2012, pp Jamasb et al

23 At some point, the cost of improvements to service quality will escalate rapidly: Yu et al Jamasb et al 2010 suggests that, above certain levels, there may be an exponential increase in costs to improve service quality. 27 Coelli et al 2012 found in a study of French distribution entities that there is a wide variance by region in the costs of improving reliability and that the costs of marginal improvements to reliability rise as reliability approaches 100 per cent. 27 Jamasb et al 2010, pp and in particular figure 9. 23

24 Part 6: Current framework for regulation of service quality Within Australia, there are a number of participants in regulation of electricity distribution service quality, reflecting in part the state of transition of electricity regulation from an area of State regulation to a more national approach. Service quality standards are set under jurisdictional legislation by each State and Territory. States typically set output standards for service quality, i.e. measured on the basis of outputs such as SAIDI, SAIFI, and so on. However, NSW regulates distribution networks on the basis of deterministic planning criteria. Under these criteria, distribution lines in the Sydney CBD are planned to an N-2 planning standard, distribution lines over 10 MVA (generally urban lines) are planned to an N-1 standard, and distribution lines under 10 MVA (generally rural lines) are planned to an N standard Other distributors apply these criteria internally but are not regulated on the basis of these criteria N-2 is a network planning standard requiring the network to continue to function without interrupting customers following the loss of two network components, or two "credible contingencies". N-1 and N have corresponding meanings. 29 Brattle Group 2012, p Except that to some extent ENERGEX and Ergon were possibly pressured to apply similar planning principles as a result of the 2004 enquiry into poor levels of service: Brattle Group 2012, p

25 A number of jurisdictions also have penalty payments where performance is below a certain standard (guaranteed service level or GSL payments). These are often related to the time take to restore power following an interruption. Service quality is mainly monitored and enforced by the AER, have transitioned from monitoring by State and Territory jurisdictional regulators. Service quality in Western Australia is monitored and enforced by the Economic Regulation Authority. The Brattle Group report for the AEMC noted that Australia was unusual compared to other nations in splitting the regulation of reliability between jurisdictional regulators and the AER. 31 The AER sets service quality incentive schemes for distribution networks as part of its pricing regulation arrangements. Under chapter 6 of the National Electricity Rules, the AER is required to develop and publish a Service Target Performance Incentive Scheme (STPIS) for distribution network service providers. Clause 6.6.2(a) of the National Electricity Rules provides: The AER must, in accordance with the distribution consultation procedures, develop and publish an incentive scheme or incentive schemes (service target performance incentive scheme) to provide incentives (which may include targets) for Distribution Network Service Providers to maintain and improve performance. In developing the scheme, the AER must take account of factors including: (i) the need to ensure that benefits to consumers likely to result from the scheme are sufficient to warrant any reward or penalty under the scheme for Distribution Network Service Providers;... (v) the need to ensure that the incentives are sufficient to offset any financial incentives the service provider may have to reduce costs at the expense of service levels; and (vi) the willingness of the customer or end user to pay for improved performance in the delivery of services Brattle Group 2012, p NER, clause 6.6.2(b)(3)(i),(v) and (vi). 25

26 The AER published its most current STPIS and accompanying explanatory document in November 2009 (version 1.2). 33 The scheme comprises four components: The reliability of supply component; The quality of supply component; The customer service component; and The guaranteed service level (GSL) component. 34 The scheme sets performance targets across reliability and customer service measures. The AER decided to not yet set performance targets for the quality of supply component due to difficulties in measurement. The three reliability measures in the scheme are: Unplanned SAIDI; Unplanned SAIFI; and MAIFI. The incentive payments are broken down into payments for reliability performance of in CBD feeders, urban feeders, rural short feeders (under 200km), and rural long feeders (over 200km). The incentive payment for CBD feeders is double the incentive payment for urban, rural short, and rural long feeders. The reliability measures exclude interruptions caused by generation, transmission, safety and network management directions issued by the Australian Energy Market Operator (AEMO), and certain major events such as cyclones. The reason for this is that these 33 AER 2009 and AER 2009a. 34 AER 2009a, p. 6, clause AER 2009a, p. 9, clause unless the AER determines otherwise in respect of a distributor. 26

27 events occur rarely and have major impacts that are beyond the design capability of the networks. 37 The total revenue at risk for the reliability measures is 5 per cent of the aggregate revenue allowance for the distribution network service provider. 38 The incentive is double-sided in that the distributor faces a penalty for not achieving the standard and faces a bonus for exceeding the standard. In other words, the total adjustment for the scheme may be plus or minus 5 per cent for the aggregate revenue allowance for a given year of a regulatory period. The customer service measures are: Telephone answering; Streetlight repair; New connections; and Response to written enquiries. 39 Total revenue at risk is plus or minus 1 per cent of aggregate revenue for a given year. 40 As noted in the introduction, the MCE in August 2011 directed the AEMC to undertake a review of distribution reliability outcomes and standards. The review has two separate work streams, working to separate (but overlapping) timetables: A review of the distribution reliability outcomes in NSW (and in particular the extent to which the input standards in NSW are driving higher than necessary expenditures; and A review of the frameworks across the National Electricity Market (NEM) for the delivery of distribution reliability outcomes. The AEMC released a report in January 2012 by the Brattle Group surveying current practice in Australia and a number of overseas jurisdictions around reliability, and putting forward a number of best practice recommendations. The AEMC is considering whether to recommend a move from State and Territory regulation of service standards 37 Except if very large expenditures are undertaken which are assumed to be beyond the willingness of customers to pay. 38 AER 2009a, p. 7, clause AER 2009a, p. 14, clause AER 2009a, p. 14, clause

28 to nationally consistent regulation of service standards. The AEMC is scheduled to provide a final report by June Distributors in some jurisdictions are still transitioning from State or Territory arrangements to the AER arrangements, as their current access arrangement has been set by a State or Territory regulator. The Brattle group paper summarises the current state of arrangements in the eight State and Territory jurisdictions in Australia. 41 International Experience 42 In New Zealand, the Commerce Commission regulates service quality for both privately owned and community owned distributors. The Commission sets minimum performance standards for privately owned distributors. It requires all distributors to publish asset management plans detailing how the networks will be managed. Privately owned distributors are required SAIDI and SAIFI targets two in every three years. The targets are based on average historical performance adjusted upwards by one standard deviation. Distributors are subject to penalties for not meeting their targets. However, there are no financial incentives or bonuses for improving performance. In Great Britain, standards are set in legislation. The Office of Gas and Electricity Markets also sets incentive arrangements around service quality as part of broader price regulation. The regulator sets incentive targets and rates for each distributor for each year of the next price control along with the investment allowances and customer payment levels under the guaranteed standards for the next price control period. 43 The bonuses and penalties are based on customer willingness to pay surveys. There are also arrangements for guaranteed service level payments for failure to meet minimum standards. There is a fund for payments to worst served customers. If the distributors can improve service by 25 per cent over three years, they can draw a payment from the fund. In Italy, the Italian Regulatory Authority for Electricity and Gas sets minimum standards and monitors compliance. It sets standards for reliability, response times to customer requests (including connections, activations, quotations, and technical checks), and the performance of the telephone helpline. The regulator sets SAIDI and SAIFI performance standards as well as bonuses and penalties. There are additional payments 41 Brattle Group 2012, Table 3, page The following discussion is drawn from Brattle Group 2012, pp Brattle Group 2012, p

29 for improving performance in the worst performing areas. There are caps on the total possible bonus payments that can be earned. The regulator monitors quality of service on a voluntary basis. The regulator enforces a compensation system if performance is below the minimum standard (e.g. for response times to customer requests). In the Netherlands, the Office of Energy and Transport Regulation within the Netherlands Competition Authority is in charge of monitoring the activities of energy distributors. Electricity distributors have incentives to beat the average historical performance of all the distributors in terms of SAIDI and CAIDI. The bonuses and penalties around beating or not beating this historical average are determined by user surveys of willingness to pay for improvements or willingness to accept interruptions. The Dutch Network Code set minimum standards for quality of service and customer service measures. The regulator can fine distributors that do not meet these minimum standards. The regulator has recently started publishing customer service metrics but without specific bonuses or penalties. Distributors must also publish a capital and operating expenditure plan with SAIDI and CAIDI targets for the regulator s scrutiny. In the United States, distributor service quality is regulated by the individual states. The States have enacted statutory requirements to meet specified standards. In most states, service quality has received stronger attention since the 1990s. The Brattle Group report notes that: Some (states) have set targets for desired ranges of reliability performance; others have gone further, developing systems of penalties and incentives regarding compliance with performance standards, sometimes within the context of already established performance based rate (PBR) plans. Furthermore, most regulators conduct some level of review of distributors capital plans and [operating and maintenance] spending. 44 Regulators track SAIDI and SAIFI and in addition individual circuit performance and MAIFI measures. Many regulators also track customer service measures such as call centre performance, billing and customer complaints, and meter reading accuracy. Most regulators set performance targets and some also set bonus and penalty arrangements around those targets. 44 Brattle Group 2012, p

30 Part 7: Ways of measuring customer preferences for service quality Markets and regulators have to determine how to set service quality standards for distribution networks. Effectively, this requires the regulator to estimate customer preferences. Customer preferences are difficult to observe directly in electricity markets. Historically, customers have taken what they have been given with little opportunity to provide feedback. Given the fact that preferences are amalgamated in the process of delivery of electricity services, different price/service quality trade-off decisions by customers cannot be directly noted. 45 A number of mechanisms can be used to gain insights into customer preferences. To date, most of the work in this area has been to measure customer preferences in relation to reliability, with less focus on other aspects of electricity distribution service quality. The main measure of the value that customers place on reliability of electricity supply is the Value of Customer Reliability (VCR). Another measure that is sometimes discussed in similar terms is the Value of Lost Load (VOLL). However, VOLL is used within the National Electricity Market as a cap on the price of electricity in the wholesale electricity 45 For example, in car markets, customer preferences for different quality and price combinations can be observed over multiple purchases to build up a more complete picture of the mix of preferences among customers. 30

31 market which exists in the absence of strong and effective demand-side market signals by users. 46 As such, the value of VOLL will tend to be lower than the value of VCR. The value placed on reliability will tend to vary across different customer classes. As a result, VCR is calculated as an averaged value across a number of different customer classes, typically residential customers, commercial customers, agricultural customers, and industrial customers. There are broadly two methods used to derive an estimate of VCR (and other service quality measures): Model-based approaches: by, for example, using the pre-existing generation security standard and the fixed and variable costs of a new peaking plant to put an implicit value on lost load; and Survey-based approaches: by surveying different customers on what value they would put on their electricity supply not being interrupted. 47 The types of approaches are summarised in table 1 below. Table 1: Approaches to estimating VCR Approach type Specific Approach Relevant customer sectors Model-based Income proxy Residential Case studies of blackouts Backup generator proxy GDP per KWh proxy (production function) All Commercial and industrial Commercial and industrial Survey-based Direct cost Commercial and industrial Contingent valuation (WTP/WTA) Choice modelling Conjoint analysis Economic principle of substitution Source: Oakley Greenwood 2011, p. 3, reproducing CRA Residential, small and medium commercial and industrial Residential, small and medium commercial and industrial Residential, small and medium commercial and industrial Residential 46 At any given time customers will tend to be unaware of the wholesale price of electricity in the NEM and so will not be making their consumption choices based on that cost. 47 Oakley Greenwood 2011, p

32 The specific approaches mentioned above can also be classified in terms of: Direct Costs capturing direct costs flowing from interruptions, for example lost production or lost profitability. Revealed Preferences measuring costs through proxy activities such as buying candles or torches or installing back-up generators to mitigate interruptions. Stated Preferences asking users to estimate the costs of interruptions. 48 The model-based and survey-based approaches are discussed below. Model-based approaches Model-based approaches draw from information and data available in the market. They typically use some observable response by market participants as a proxy for the value of service quality. For example, this approach could examine which parties purchase back-up generators and their associated level of reliability. The costs of the back-up generation are then equated with that level of reliability to provide a value for that level of reliability. Another example of this approach might be to assign a value to lost time due to an interruption at the rate at which interrupted user earns net income or profit. 49 Alternatively, for businesses the interruption could be assigned a value related to a loss in some proportion of gross domestic product. This assumes that each $1,000 of production is represented by a certain amount of electricity in kwh. Another approach may be to conduct a case-study of an interruption and study the actual costs imposed on various users by it. For example, a researcher might study the impact on sales and profitability from loss of electricity to a hardware store adjusted for factors such as any make-up sales after power is restored. 48 Generally direct costs are considered the most reliable guide to the value of a particular aspect of service quality, followed by revealed preferences, and then stated preferences. This is because direct costs and revealed preferences capture actual decisions made by users. However, this assumes the direct cost or revealed preference data is accurate and representative. 49 In other words, an interruption to a residence where people earn $x/hour will be treated as a cost of $x/hour. Likewise an interruption to a business can be estimated in the same way. 32

33 Model-based approaches have the advantage over survey-based approaches that they are based on actual choices and hard data, whereas survey-based approaches rely on theoretical choices put to survey respondents. Further, respondents may respond to strategically to surveys if they see an advantage in providing a certain response, for example if they perceive that compensation payable for interruptions may be greater if they overstate the cost of an interruption to them. However, the disadvantage with model-based approaches is that the proxies used in the models are inevitably an approximation of the underlying relationships between consumer behaviour and the value that customers put on service quality, and as such may be misleading or inaccurate. Survey-based approaches Survey-based approaches rely on asking representative users about the costs of interruption. There are two main survey-based approaches direct and indirect. Direct approaches focus on the direct costs of interruptions in terms of lost production, sales, spoiled perishables in refrigerators, or other measures. These costs are relatively easier to quantify, but these approaches do not work so well for residential users, who experience fewer direct costs from an interruption. Indirect approaches attempt to measure the less tangible costs arising from interruptions such as inconvenience from the inability to use appliances such as televisions, disruption to cooking times, and so forth. There are a number of indirect approaches including: Economic principle of substitution this approach asks a series of questions about options with known costs as substitutes for the good or service in question. Users might be asked what actions they might take in response to an interruption of a specified length (such as one hour). The options might be to buy a torch or candles, dine out, buy a gas camping stove, buy a generator, and so forth. Each of these options has a different and ascending value. The choices of a large number of users can be combined to arrive at a central value for the cost of an interruption of the specified length.50 Contingent valuation this approach measures what customers would be willing to pay to improve reliability or willing to accept as compensation for a reduction in the level of reliability. Users nominate what they would be prepared to pay or 50 Of course, users do not tend to know in advance the length of an interruption, which is a flaw in this approach. 33

34 accept for an interruption of a specified length, or they select a value from a menu of values presented to them. Choice modelling this approach attempts to model the choices made by users among a variety of price/service scenarios. Users are asked to choose between two scenarios, each with a given cost. For example, users may be asked to choose between electricity supply at $1,000 with 10 hours of interruptions per year and electricity supply at $1,100 with 8 hours of interruptions per year. The benefit of this approach is that it can model many different scenarios to arrive at a value on an hour of interruptions, and can also model factors such as a declining or increasing value placed on interruptions as the number of interruptions per year falls. Conjoint analysis this approach is similar to choice modelling. It involves the users selecting among bundles of price/service offerings. Products are defined in terms of a number of features (e.g. price, reliability, ease of access to the call centre, quality of supply) and customers make multiple choices among different combinations of features (for example, between moderately priced electricity with moderate reliability and moderate quality of supply and high priced electricity with moderate reliability and high quality of supply) to determine the value of each feature. Australian experience A number of Australian regulators have conducted studies on VCR and other aspects of service quality. Table 2 illustrates some of the studies, the approach used, and the findings. Table 2: Australian studies of VCR Study Approach Findings Jurisdiction 1997 Monash study VENCorp 2002 (CRA) IPART 2002 (KPMG) 1,2 ESCOSA 2003 (KPMG) 1 VENCorp 2007 (CRA) Economic principle of substitution Economic principle of substitution; Direct costs $28.89/KWh for VCR $29.60/kWh for VCR Victoria Victoria Willingness to pay --- NSW Willingness to pay, choice modelling Economic principle of substitution; Direct costs WTP between 12% and 23% across different customer classes for a range of service quality improvements $47.85/kWh (including broader social costs) SA Victoria 34

35 Study Approach Findings Jurisdiction ESCOSA 2007 (McGregorTan) Willingness to pay 13% residents and 8% businesses WTP to improve service quality. Most of those WTP indicated they would be prepared to pay $25 - $49 per year. SA AEMO AEMC 2012 Derived from Victorian 2007 studies with tolerances On-going study in NSW at request of NSW Government Between $41.53/kWh (NSW) and $57.29/kWh (Vic) On-going NSW, Vic, Qld, SA, Tas NSW Note 1: The IPART and ESCOSA studies studied other aspects of service quality. The ESCOSA study looked at matters including information provision about planned and unplanned interruptions, voltage fluctuations, and undergrounding. Note 2: The NSW study by IPART did not proceed past the initial pilot stage: Oakley Greenwood 2011, p. 16. In addition to the regulator studies, a number of studies have been conducted by regulated electricity distributors, for example, Aurora in Tasmania, Integral Energy in NSW, and Citipower and Powercor in Victoria. 52 International experience England and Wales Kariuki and Allan conducted a study in 1996 of VOLL in England and Wales, which estimated VOLL at US$18.5/kWh in 1999 prices. 53 New Zealand NEW Zealand is using choice modelling to estimate the value of unserved energy (USE). 54 USE is the amount of energy demanded but not supplied due to an 51 Used by AEMO to value the benefit of proposed transmission augmentations to reduce unserved energy. 52 IPART 2003, p Kariuki and Allan Concept Economics and the New Zealand Centre for Advanced Engineering

36 interruption. USE is used as a yardstick in New Zealand for determining whether to proceed with new transmission investments. The study is in three stages. 55 The paper from the first stage in 2008 recommended that the then-current values for USE being used in New Zealand should be reconsidered using survey methods. They recommended using direct cost for businesses, and choice modelling for all user classes. Stage 2 is currently underway and involves trialling and then implementation of the choice modelling survey leading to a draft report, with a final report as stage For a description of the study, see 36

37 Part 8: Service quality incentive schemes Service quality incentive schemes are intended to provide incentives for electricity distributors to move their service levels towards optimum levels. Studies have suggested that utilities do respond to such incentive schemes. 56 Designing such schemes can be highly challenging as it ideally involves knowledge of both the costs of improving service quality and customers willingness to pay for such improvements. 57 Jamasb et al 2010 notes that: Sappington (2005) concludes that there are no simple policy solutions for effective regulation of quality of service but they depend on the information available to the regulator on consumer preferences and production technology. 58 As part 6 discusses, the international experience shows that a number of countries are starting to investigate and determine customer willingness to pay in the design of incentive schemes, for example, Great Britain and The Netherlands. The Council of European Energy Regulators considers that the results from cost-estimation studies on customer costs due to electricity interruptions are of key importance in order to be able 56 Jamasb and Pollitt Jamasb et al 2010, Joskow Jamasb et al 2010, p

38 to set proper incentives for continuity of supply and recommends that National Regulatory Authorities should perform nationwide cost-estimation studies regarding electricity interruptions and voltage disturbances. 59 The Council of European Energy Regulators has published guidelines for conducting such studies. 60 Studies on the marginal costs of improving service quality are relatively rarer. Coelli et al 2012 and Jamasb 2010 are two such studies. In a regulatory setting, the customer willingness to pay curve is likely to be the upper bound for a service quality incentive scheme while the marginal cost to improve service quality is likely to be the lower bound. 61 This can be seen in diagram 3 in part 5 where to the left of the point of equilibrium the marginal cost of improving reliability is less than customers willingness to pay. Accordingly, the regulator must decide whether to set the incentive scheme around customers willingness to pay or seek to estimate the marginal cost of improving reliability and set the incentives closer to these marginal costs. The first approach will tend to over-compensate the distributor, while the second approach requires significantly more information and is difficult to implement given the marginal cost curve is not constant but is rising as quality improves. The regulator will also have to consider how to design the incentive scheme. Some of the key design choices are: Symmetry: A symmetric scheme that both penalises and rewards performance or an asymmetric scheme that either just imposes penalties or just provides rewards; Power: How high-powered to make the scheme, that is the size of the rewards and penalties compared to total allowable revenues; Feeders: whether to adjust the scheme to favour particular feeders, such as CBD or rural feeders, or worst performing feeders. A symmetric scheme will provide greater incentives to improve performance. However, if quality is judged to have risen to a standard above which customers are not willingness 59 Centre for European Energy Regulators 2010, p Centre for European Energy Regulators Jamasb et al 2010, p

39 to pay for further improvements, then it may be better to have an asymmetric scheme that penalises any fall in quality. 62 A high-powered scheme will provide greater incentives for the distributor to improve quality rapidly. However, if a distributor is subject to a significant penalty in a highpowered scheme it may be deprived of the resources to improve quality or may even be threatened financially. It may be sensible to adjust the scheme to reward improvements in performance for particular feeders. As noted in part 6, the AER scheme rewards improvements in CBD performance at twice the rate as other parts of the network. This may appear sensible given there are more commercial and industrial customers located in the CBD than other areas of the network. At the same time, it is important to take into account willingness to pay and adjust the scheme to the areas where customers are willing to pay more. Evidence from the 2003 ESCOSA study by KPMG (although not the 2007 ESCOSA study) suggested remote and CBD customers are the most willing to pay for improvements than urban customers. 63 UK studies suggested London customers were willing to pay more for improvements than customers outside London ( 13 compared to 4) Evidence from the UK suggested customers were more keen on compensation for poor performance than on paying for improved performance, suggesting some value in an asymmetric scheme penalising poor performance: Brattle Group 2012, p KPMG 2003, pp and 69, contrast McGregorTan 2007, p.152, and 64 Brattle Group 2012, p

40 Part 9: Adjusting service quality over time Customer preferences for given levels of service quality are unlikely to be stable over time. This is because they are driven by factors such as the requirements of customers electrical appliances and changes in wealth. Changes in the use of electricity will tend to drive changes in preferences around service quality. Some appliances are more sensitive to poor power quality or the number of momentary interruptions. For example, momentary interruptions tend to be more costly in their impact on computer use than on television use. Thus, rising computer use is likely to have driven an increase in demands around reliability. 65 Over time, consumer preferences may change as different appliances are connected to the electricity system. Increases in wealth may also drive demands for improved service quality. It could be expected that demand for higher service quality would tend to increase with increases in average income or wealth among users. The challenge for market and regulatory arrangements around service quality will be for service providers and the regulatory system to respond to changes in demand for different service quality levels as these changes occur. This could involve refreshing measurements of willingness to pay for improvements or the value of lost load. 65 To some extent, this tendency has abated with improvements in computer operating systems to prevent loss of data following a power interruption. 40

41 Part 10: Regulatory lessons Estimating willingness to pay and marginal costs of improving service quality is always likely to be an imperfect exercise: Joskow Even assuming regulators are able reasonably to estimate the shape of these curves, they will still need to determine the best way forwards. Regulators can: Set high or low-powered incentives depending on the size of the bonuses or penalties involved in the scheme; Set bonuses and penalties at the upper bound of willingness to pay or the lower bound of marginal cost to supply; Provide greater scope for distributors to set or negotiate different prices in different parts of the network, for example higher priced but more reliable supply in industrial or commercial areas; Invite or permit greater engagement between the distributors and different user groups. This could enable distributors to adjust quality settings over time as user preferences change but the mechanism would need to overcome the fact that distributors have access to far more information than users about the costs of improving service quality. 41

42 Part 11: Literature survey MCE Energy and Resource Ministers Communiqué, 10 June 2011, accessed 2 August National Framework The Standing Committee on National Regulatory Reporting Requirements (SCONRRR) under the Utility Regulators Forum set a national framework for the consistent reporting of distribution service quality measures. The National Reporting Framework report is: Standing Committee on National Regulatory Reporting Requirements 2002, National regulatory reporting for electricity distribution and retailing businesses, March. and it can be found at: 4f b125&fn=National%20Regulatory%20Reporting%20for%20Electricity %20Distribution%20and%20Retailing%20Businesses%20March% pdf AER The AER is responsible for publishing service quality or performance reports for electricity distribution networks. In April 2011, the AER published its final decision and 42

43 approach on how it will require electricity distribution service providers to report performance. 66 The AER stated that the objectives of service quality performance reporting were: Education Transparency Accountability Improved performance 67 The AER s service quality performance reporting approach can be found at: The AER s statement of approach and final decision on priorities for distribution service quality monitoring are: AER 2011a, Statement of Approach: Priorities and objectives of electricity network service provider performance reports, April. AER 2011b, Priorities and objectives of electricity network service provider performance reports, April. These can be found at: In November 2009, the AER published its final decision providing its reasons for how it will measure aspects of reliability for the purposes of its service performance target incentive scheme: AER 2009, Final decision: Electricity distribution network service providers service target performance incentive scheme, November. The service performance target incentive scheme (version 1.2) is at: 66 AER 2011a 67 AER 2011b, p.3. 43

44 AER 2009a, Electricity distribution network service: Providers Service target performance incentive scheme, November. The AER publishes SAIDI and SAIFI statistics for different distribution areas within Australia at: AER 2011, State of the Energy Market NSW (IPART) IPART conducted an investigation in service quality issues in as part of the 2004 Distribution Pricing Review. The issues paper is: IPART 2003, Providing Incentives For Service Quality In NSW Electricity Distribution: An Issues Paper (Discussion Paper DP63), May. and can be found at: %20PROVIDING%20INCENTIVES%20FOR%20SERVICE%20QUALITY%20IN% 20NSW%20ELECTRICITY%20DISTRIBUTION%20- %20An%20Issues%20Paper%20-%20May%202003%20pdf.%20version%20- %20website%20document%20ISBN% pdf Submissions are at: =45 IPART s final findings were incorporated into its 2004 Pricing Determination at: %20to% %20-%20Final%20Determination.pdf.PDF Victoria (ESC) The ESC investigated service quality issues as part of its 2006 Distribution Pricing Determination. Its consultation paper is: 44

45 ESC 2004, Electricity Distribution Price Review 2006 Service Incentive Arrangements Consultation Paper No. 2, April. and it can be found at: 3A38FF1A3765/0/EDPR_ConsultPaperNo2_Apr04.pdf A summary of the ESC s 2006 Distribution Pricing Determination in relation to service quality issues can be found at: E B30/0/FactSheetNo4_ServiceStandardsOct05_Revised.pdf Queensland (QCA) The QCA conducted a review of whether to implement a service quality incentive scheme in 2003 and 2004 as part of its 2005 Distribution Revenue Determination. See: The QCA commissioned Meyrick and Pacific Economics Group to recommend on the design of a service quality incentive scheme. Meyrick s draft report (there was no final report, or it has not been released) is: Meyrick and Associates and Pacific Economics Group 2003, Development of an Electricity Distribution Service Quality Regime to take effect in Future Regulatory Periods: Draft Report, August. The QCA s final decision was to implement a service quality incentive scheme. See: QCA 2004, Final Decision: Service Quality Incentive Scheme for Electricity Distribution Services in Queensland, April. and it can be found at: However in the end the QCA did not proceed with implementation of the scheme. 45

46 Western Australia (ERA) The ERA commissioned Network Advisory Services to analyse the service quality aspects of the 2006 Revenue Determination for Western Power distribution network. The report is: Network Advisory Services 2005, Service Standards for Western Power Corporation s South West Interconnected System, September and can be found at: dards.pdf South Australia (ESCOSA) ESCOSA conducted an investigation into incorporating service quality incentives into its revenue determination. In 2003, it commissioned KPMG to report on consumer preferences and willingness to pay for improved service quality at: KPMG 2003 (for ESCOSA), Consumer Preference for Electricity Service Standards, September. In 2007, ESCOSA commissioned McGregor Tan to update this review: McGregor Tan 2007 (for ESCOSA), Consumer Preference for Electricity Service Standards, November. In 2008, ESCOSA reported on its service quality regime for the 2010 Revenue Determination at: ESCOSA 2008, South Australian Electricity Distribution Service Standards: , Final Decision, November. Tasmania (OTTER) A discussion of Tasmania s standards for performance monitoring can be found at: b001b41f2/ad67fcd9ec5050f8ca25721a00808e04?opendocument A working group comprising the regulator, Aurora (the distributor), and the Office of Energy Planning and Conservation developed service standards during 2006 and

47 Their recommended service standards are: Office of the Tasmanian Energy Regulator, Aurora Energy, Office of Energy Planning and Conservation 2007, Joint Working Group Final Report Distribution Network Reliability Standards Volume I Summary of Recommendations and Overview, February which can be found at: %20Dx%20Standards%2007%20Final%20Report%20v1.0%20Volume%201.pdf/$file/ R%20-%20Dx%20Standards%2007%20Final%20Report%20v1.0%20Volume%201.pdf Consumer Preference studies AEMO 2012, National Value of Customer Reliability (VCR), January. Aurora Energy 2002, Price Submission: Summary of the Customer Value Proposition Findings from EMRS Report, Hobart. CRA 2002, Assessment of the Value of Customer Reliability (VCR), December, for VENCorp. CRA 2007, Assessment of the Value of Customer Reliability (VCR), August, for VENCorp. Department of Environment and Heritage 2005, Making economic valuation work for biodiversity conservation, May. This paper is an excellent summary of using direct and indirect valuation methods to value quality. Monash 1997, Value of Lost Load Study, Report for Victorian Power Exchange, Report by Kahn and Conlon. Also see Khan M.E. and M. F. Conlon, Value of Lost Load, 1997, Centre for Electrical Power Engineering (CEPE), Department of Electrical and Computer Systems Engineering, Monash University, for the Victoria Power Exchange (VPX). Kariuki and Allan 1996, Evaluation of Reliability worth and value of lost load, IEE Proceedings, Generation, Transmission and Distribution, Vol. 143, No. 2, March, pp KPMG 2003 (for ESCOSA), Consumer Preference for Electricity Service Standards, September. McGregor Tan 2007 (for ESCOSA), Consumer Preference for Electricity Service Standards, November. 47

48 Oakley Greenwood, Valuing Reliability in the National Electricity Market: Final Report, March 2011, for the Australian Energy Market Operator. International Studies Ajodhia V., R. Hakvoort 2005, Economic regulation of quality in electricity distribution networks, Utilities Policy, Vol. 13, n. 3, pp All Island Project, 2007, The Value of Lost Load, the Market Price Cap and the Market Price Floor: A Consultation Paper, July. Brattle Group 2012, Approaches to setting electricity distribution reliability standards and outcomes, January, report for AEMC. The Brattle Group report above surveys reliability regulation across a number of countries including Australia, for the purpose of informing decision-making around best practice regulation of service quality. Coelli Tim, Axel Gautier, Sergio Perelman, and Roxana Saplacan-Pop 2012, Estimating the cost of improving quality in electricity distribution: A parametric distance function approach, CREPP WP No 2012/02, March, at www2.ulg.ac.be/crepp/papers/creppwp pdf Coelli, T.J., Crespo, H., Plagnet, M.-A. and E. Romano 2007, Incorporating quality of service in a benchmarking model: an application to French electricity distribution operators, CIRED, Vienna, May 2007 Conference Proceedings. Concept Economics and the New Zealand Centre for Advanced Engineering (CAENZ), Investigation of the Value of Unserved Energy: Stage 1, for the (then) New Zealand Electricity Commission, December Available at of use. Council of European Energy Regulators 2008, Fourth Benchmarking Report on Quality of Electricity Supply, Task Force on Quality of Electricity Supply, Brussels. Available from [ceer.eu.org]. Council of European Energy Regulators 2010, Guidelines of Good Practice on Estimation of Costs due to Electricity Interruptions and Voltage Disturbances, December. De Fraja G., A. Iozzi 2004, Bigger and better: a dynamic regulatory mechanism for optimum quality, Discussion Paper No. 4502, Centre for Economic Policy Research, London, UK, August. 48

49 Energy Institute Hrvoje Požar 2010, Assistance to regulators in introducing and improving service quality regulation in the Energy Community Energy Community Study Draft Final Report Page II, 2010, June. Fumagalli, E., Lo Schiavo, L. and F. Delestre 2007, Service quality regulation in electricity distribution and retail, Springer-Verlag Berlin Heidelberg, at 0#section=316814&page=2&locus=0 Fumagalli Elena, Luca Lo Schiavo 2009, Regulating and improving the quality of electricity supply: the case of Italy, European Review of Energy Markets - volume 3, issue 3, October Giannakis, D., T. Jamasb, M. Pollitt 2005, Benchmarking and Incentive Regulation of Quality of Service: An Application to the UK Electricity Distribution Utilities, Energy Policy, Vol 33(17): ; also to be found in Energy Policy, Vol. 22, pp , Gomez, T., & Rothwell, G. 2003, Electricity economics: Regulation and deregulation. Piscataway, NJ: IEEE Press. Growitsch, C., T. Jamasb and M. Pollitt 2005, Quality of service, efficiency and scale in network industries: An analysis of European electricity distribution, Working paper CWPE 0538 and EPRG 04, University of Cambridge, UK. Growitsch, C., Jamasb, T. and Pollitt, M. 2009, Quality of Service, Efficiency, and Scale in Network Industries: An Analysis of European Electricity Distribution, Applied Economics 41(20), Holt, L. 2004, Utility service quality: Telecommunications, electricity, water, Utilities Policy, 13(3), International Energy Agency, Energy Policies of IEA Countries, Italy 2009 review. Jamasb T., M. Pollitt 2007, Incentive regulation of electricity distribution networks: lessons of experience from Britain, Energy Policy, Vol. 35, n. 12, pp Jamasb, T., Orea, L., Pollitt M., 2010, Estimating Marginal Cost of Quality Improvements: The Case of the UK Electricity Distribution Companies, EPRG Working Paper 1027, University of Cambridge UK. Joskow, P. 2006, Incentive regulation in theory and practice: Electricity distribution and transmission networks, Cambridge, MA: MIT Center for Energy and Environmental Policy Research. 49

50 Joskow, P. 2008, Incentive Regulation and Its Application to Electricity Networks, Review of Network Economics Vol.7, Issue 4 December, p Kessides, I. N. 2004, Reforming infrastructure: Privatization, regulation and competition, Washington, D.C.: World Bank/ Oxford University Press. Lawrence, D. and E. Diewert 2006, Regulating Electricity Networks: The ABC of Setting X in New Zealand, in Coelli, T.J. and D. Lawrence (eds.), Performance Measurement and Regulation of Network Utilities, Edward Elgar Publishing, Cheltenham, McKenzie and Mookherjee. 2003, Distributive Impact of Privatization in Latin America: An Overview of Evidence from Four Countries, Economia, 3:2, pp Office of Gas and Electricity Markets (OFGEM) 2004a, Electricity Distribution Price Control Review: Appendix The Losses Incentive and Quality of Service, June 145e/04. London. Office of Gas and Electricity Markets (OFGEM) 2004b, Consumer expectations of DNOs and WTP for improvements in service, Ofgem Report 145f/04. Prepared by Accent Marketing & Research. Reichl J., A. Kollmann, R. Tichler and F. Schneider 2008, The importance of incorporating reliability of supply criteria in a regulatory system of electricity distribution: an empirical analysis for Austria, Energy policy, Vol. 36, n. 10, pp Revolo, Miguel J Regulation, monitoring, and ownership influence the quality of service of Latin American electric distribution utilities: a doctoral research proposal. Journal of CENTRUM Cathedra Publisher: Pontificia Universidad Catolica del Peru Sappington 2005, Regulating service quality: a survey, Journal of Regulatory Economics, Vol. 27, n. 2, pp Sintef Energy Research (Matthias Hofmann, Helge Seljeseth, Gro Holst Volden, Gerd H. Kjolle) 2010, Study on Estimation of Costs due to Electricity Interruptions and Voltage Disturbances, December. Ter-Martirosyan A. 2003, The effects of incentive regulation on quality service in electricity markets (Working Paper March 2003). Washington D.C.: George Washington University, Department of Economics. Ter-Martirosyan A., J. Kwoka Incentive regulation, service quality, and standards in the U.S. electricity distribution, Journal of Regulatory Economics, Volume 38, Number 3. 50

51 Weisman D. 2005, Price regulation and quality, Information Economics and Policy, Vol. 17, n. 2, pp Yu W., T. Jamasb and M. Pollitt 2007, Incorporating the price of quality in efficiency analysis: the case of electricity distribution regulation in the UK, Working Paper CWPE 0736 and EPRG 0713, University of Cambridge, UK. Yu, W., Jamasb, T., and Pollitt, M. (2009), Willingness-to-Pay for Quality of Service: An Application to Efficiency Analysis of the UK Electricity Distribution Utilities, Energy Journal, 30(4), Performance Monitoring Reports National (AER): No performance statistics reported as yet. NSW (IPART): Victoria (ESC): +Reports/ Queensland (QCA): Western Australia (ERA): performance_reports.pm South Australia (ESCOSA): Tasmania (OTTER): 1b41f2/7715a04d0c9ce4e7ca256cdd007d685c?OpenDocument 51

52 ACT (ICRC): 52