Regulation of continuity of supply in the electricity sector and cost of energy not supplied

1. Regulation of continuity of supply in the electricity sector and cost of energy not supplied Ilaria Losa (ERSE) – Osvaldo Bertoldi (Enginet) Presented by: Ilaria Losa June 17-19, 2009 IEW 2009, Venice

2. Reliability of electricity supply RELIABILITY refers to uninterrupted electricity service In a liberalized framework, investments in transmission grid should be evaluated through a Cost/Benefit analysis. “How much reliability is adequate from the customers’ perspective?” Shift from CRITERIA BASED APPROACH (N-1; N-2 security; EENS<Eupper) to VALUE BASED APPROACH (Cost/Benefit analysis; estimation of avoided costs)

3. Assessment of total cost of electricity/1 Total cost of electric service consists of two components: Cost of service received; Cost of unreliability. Consumers are then best served when their total costisminimized.

4. Assessment of total cost of electricity/2 The assessment of the best compromise between additional investment costs and corresponding benefits to consumers needs to quantitatively determine the value of continuity. This task can not be implemented as a direct method because no market for continuity of supply exists. An usually adopted approach is to assess its reverse, the cost associated to lack of continuity. It is not equal to value of continuity but can represent a lower bound.

5. Impact of supply failures

6. Consumer and interruption characteristics Costs of interruptions depends on customers’ and interruptions’ characteristics such as: Type of consumers: industrial, service, residential sector; Perceived reliability level: it depends both on the incidence of interruptions in the past both on dependency on electricity and standards of living; Time of occurrence of interruption: day/night, week/weekend and so on; Interruption duration: for the industrial sector marginal costs may decrease; Difference in notification: advance notice lower the consequences; Extent of interruptions: localized or extended. As a result of these different inputs interruption cost indicators can imply large range of values on the basis of the relative importance of each factor.

7. CRITERIA BASED APPROACH: SAIDI(System Average Interruption Duration Index) CAIDI(Customer Average Interruption Duration Index) SAIFI(System Average Interruptions Frequency Index) ENS (Energy Not Supplied) EENS (Expected Energy Not Supplied) Technical indicators, based on reliability criteria. Do not account for economic values of interruptions. Indices expressing costs of interruptions VALUE BASED APPROACH: • IEAR(Interruption Energy Assessment Rate) [€/kWh]. Combined with EENS it provides an estimation of expected annual economic damage borne by customers. • VOLL(Value of Lost Load) [€/kWh]. • WTP(Willingness To Pay) [€/kWh].

8. Methodologies/1 • Revealed preferences: observation of customer behavior (medium and large firms). • Reliable information deriving from actual customer behavior. • It is representative only of large firms’ behavior. • Stated preferences: based on customer surveys. • Interruption costs suitable for planning purposes and incorporates customers’ preferences. • It has high costs of implementations.

9. Methodologies/2 Proxy methods: inferences from variables closely related to cost of interruptions. Easy to apply (data available) and practically inexpensive. Might be limiting and based on unrealistic assumptions. Case studies: based on collection of as many data as possible immediately after large scale interruptions occur. Cost values are directly related real interruptions experienced by customers. Case studies are limited

10. Computing techniques to assess interruption cost indicators Computing of power system interruption cost indices Setting up customer interruption costmodels Processing of raw collected data Interruption Cost Indicators • WTP or Customer Interruption Costs • Normalizing individual customer data either by: -annual consumed energy (MWh) -peak load demand (MW) Combining interruption costs model, load and system model Usually based on Customer Damage Functions (CDF) D (economic loss) = F (outage attributes, customer characteristics, geographical attributes) • IEAR • VOLL

11. Continuity regulation Continuity regulation is intended as the set of measures aimed at improving the network reliability. Three approaches can be adopted by Regulators: Moral suasion; Minimum continuity standards; Continuity incentive/penalties scheme. Indices adopted to measure continuity of supply are SAIFI, SAIDI, MAIFI, ENS, AC (Average Continuity). Beneficial effects on supply continuity indicators that have been experienced are summarized in the following slide.

12. Effectiveness of continuity regulation Great Britain Hungary SAIDI: -19% SAIFI: -15% SAIDI: -65% Norway ENS: -40% Italy Ireland SAIDI: -53% SAIFI: -34% AC: +28%

13. Case study 1: Italy In 2007 AEEG, the Italian regulating Authority introduced a mechanism for stimulating the improvement of continuity of supply of the transmission service. The maximum amount of the penalties is equal to 1.5% of the revenues deriving from transmission service, while the maximum incentives are equal to 2%. The three indicators identified by AEEG to measure continuity of supply are: Number of Outages per Users (NOU), accounts for both short and long term outages and is calculated for each category of final users and for each Operative Area identified by TERNA (Italian TSO) (AOT). It is expressed in terms of outages/users.

14. Case study 1: Italy Standard Energy Not Supplied(ENSS) calculated using the correlation illustrated in the picture. Amount of Customers without Outages(ACO) if TERNA meets both the ENSS and the NOU target standards, the above incentives are increased by a factor equal to: 1 + 2  max [(LEACO –LPACO; 0)] • Cost of interruptions estimated: • Domestic 10€/kWh • Industrial 20€/kWh • Average 19€/kWh

15. Estimations of values of VOLL Ireland 62.0 US2007$/kWh 40.0US2007$/kWh Slovenia 1-3 €2007$/kWh Romania 0.8 €2007$/kWh Bulgaria 2.0 €2007$/kWh Great Britain 2.5-9 US2004$/kWh 4-10 US2004$/kWh Sweden 2.5-5 US2004$/kWh 6.2-18 US2004$/kWh 49 US2004$/kWh Finland 10 US1999$/kWh Norway 2.5-9 US2004$/kWh 5.0 US2004$/kWh Italy 10 €2004$/kWh 20 €2004$/kWh UNMIK 0.4 €2007$/kWh The Netherlands 10 US2004$/kWh All sectors Residential CommercialIndustry Croatia 2.56 €2007$/kWh

16. Conclusions/1 Four types of methods are categorized in the literature: Revealed Preferences, Stated Preferences, Proxy methods, Case Study. SP seems to be preferable. When an “ex ante” outage cost analysis is requested, (e.g. network expansion planning), power system interruption indices, such as SAIFI, SAIDI, ENS, are needed. Some values of VOLL available in the literature have been obtained through different approaches and computing methodologies so it is difficult to compare them to each other.

17. Conclusions/2 VOLL tends to be higher for developed countries than for developing ones, mainly depending on the respective shares of electricity to total energy consumption. Such differences could be smoothed by expressing VOLL in PPP (Power Purchase Parity) rather than in US$ and current international exchange rates. In the long term (2030) it has been estimated that VOLL values (in €/kWh) could lie in the intervals 5  25 and 2 5 for developed and developing countries respectively, with 90% confidence limit. The spread in VOLL values in absolute terms; in any case median values are closer to lower bound than to upper bound of each relevant interval.

18. Ilaria Losa Power System Development Department Ilaria.Losa@erse-web.it Via Rubattino, 54 - 20134 Milano - Italy Tel. +39 02 3992 5422 Fax +39 02 3992 5557

19. Assessment of IEAR Analytical state enumeration method: Montecarlo sequential simulation: Duration d used in analytical state method is an average value whereas d used in Montecarlo method is an actual distribution. Montecarlo method is preferable when duration of interruptions is high.

20. Assessment of VOLL VOLL as a function of interruption duration is directly derived from CDFs according to the following formula: • The expected VOLL value is calculated as:

21. Number of Outages per Users Number of Outages per Users (NOU),was introduced in order to foster the level of protection offered to the final customers also regarding short-lasting outages. It accounts for both short and long term outages and it is calculated for each category of final users of the transmission network and for each Operative Area identified by TERNA (AOT). It is expressed in terms of outages/user. AEEG chose, for the beginning of the regulatory period and for each AOT, a starting value equal to the average NOU calculated, in each area, during years 2006 and 2007: (LENDU-LONOU)*CNOU *Pij LENDU :actual NOU value; LONOU target value; CNOUis the cost of energy not supplied; Pij is the average power transmitted by AOT j during year i divided by the number of hours in a year

22. Standard Energy Not Supplied ENSS accounts for continuity of supply and it is a weighted average of the energy not supplied during ordinary outages and of the energy not supplied during major incidents. In order to mitigate the volatility that characterizes the latter, ENSS is assessed using average values calculated for three years periods and weighted with a limitation function that has a less than proportional trend.Incentives and penalties are equal to: (LEENSS - LOENSS)  CENSS LEENSS :actual ENSS value; LOENSS target value; CENSS is the cost of energy not supplied; The starting reference value of ENSS is the arithmetic average of three years averages calculated for years 2001-2007.

23. Case study 2: England Since 2005 Ofgem (English regulating Authority) has been providing NGC (TSO that operates in England) with an economic incentive (or penalty) to promote the improvement of continuity of supply of transmission grid. Index used to measure continuity of supply: energy not supplied, compared with the corresponding target value. The first target value is calculated as the average level of ENS recorded between 1991 and 2004. Maximum incentive equal to1.0% of the revenues of the TSO and a maximum penalty equal to 1.5%.

24. Case study 2: England Calculating the slope of the map illustrated above we can estimate a value of energy not supplied equal to 52940 €/MWh