C I R E D 18 th International Conference on Electricity Distribution Turin, 6-9 June 2005 CIRED2005 Session No 2 POWER QUALITY FACTORS IN EFFICIENCY BENCHMARKING Lassila J 1) ., Honkapuro S., Viljainen S., Tahvanainen K., Partanen J. Lappeenranta University of Technology Kivikko K., Antila S., Mäkinen A., Järventausta P. Tampere University of Technology. Finland, 1) Jukka.Lassila@lut.fi Abstract - In this paper methods to take power quality factors (e.g. number and duration of planned and unplanned interruptions, number of auto-reclosing operations) account into efficiency benchmarking as outage costs is presented. The effects of outage costs in efficiency benchmarking are evaluated by means of sensitivity analyses. Effects of power quality factors in different kind of regulation models in actual network planning task are estimated. INTRODUCTION The importance of power quality (PQ) – including both voltage quality and interruptions – is growing in regulation process and distribution business. In many countries, e.g. in Norway [1] and in Finland [2], PQ is already part of efficiency benchmarking. Although PQ has been monitored rather detailed (e.g. number and duration of planned and unplanned interruptions, number of auto-reclosing operations, voltage levels etc.) many years, PQ is taken into account quite simplified way in efficiency benchmarking. Usually only duration of interruptions is notified in efficiency benchmarking. The main reason is that quality of data of PQ statistics is not good enough to use them in benchmarking. Other reason is that use of more than one PQ factor in benchmarking requires sophisticated efficiency benchmarking methods. In Data Envelopment Analysis (DEA) it is possible to use factors, which are not commensurate with each other’s. This means that the factors with various units (time, number, currency etc.) can be used in benchmarking at the same time. DEA weights benchmarking factors so that efficiency score is as high as possible for every company. E.g. if company is best as a sense of one factor (e.g. PQ), DEA weights this property of company more than the factors which are not beneficial for the company in efficiency benchmarking. In practice this may cause problem in sense of insignificant factors. If PQ is included in DEA as four separated factors (e.g. number and duration of planned and unplanned interruptions), DEA may weight one or more of these factors so that the factor does not actually affect to the efficiency score at all. In this situation company may improve or worse these properties without affecting its efficiency score. One way to avoid this problem of insignificant factors is to combine PQ factors to one outage cost and add this cost to operational costs. The basic idea of outage cost is to determine unit costs for different kinds of outages for different kinds of customer types. In Finland interruption time of customers is one and only PQ factor in efficiency benchmarking at the moment. Discussions that how the other power quality components such as number of interruptions, auto-reclosing operations and voltage levels can be included to efficiency benchmarking are active. Some of this data is already collected from network companies annually. Regulator can calculate outage costs for each company by using this data. This is possible when unit prices of each power quality factors are defined. In Finland e.g. price of unplanned (unexpected) interruption for residential customer is 0,068 €/kW and 0,61 €/kWh [3]. Unit prices are defined for five customer types and four interruption types. PQ factor can be formed as a sum of separated PQ cost components. In efficiency benchmarking it is possible to add outage costs to company’s operational costs as presented in Fig. 1. Outage costs ( ) costs Outage costs l Operationa Customers Network Energy h Max 1 3 2 1 0 + ⋅ + ⋅ + ⋅ + ⋅ = v c u u u Residential customer Agriculture customer Industry customer Public customer Service customer - planned interruptions: 1,5 h - unplanned interruptions: 2,5 h - high speed auto-reclosing: 45 - delayed auto-reclosing: 13 Interruption statistics Efficiency benchmarking (DEA) + Unit costs Residential customer Agriculture customer Industry customer Public customer Service customer - planned interruptions: 0,034 €/kW and 0,30 €/kWh - unplanned interruptions: 0,068 €/kW and 0,61 €/kWh - high speed auto-reclosing: 0,068 €/kW - delayed auto-reclosing: 0,088 €/kW Fig. 1. Outage cost method and DEA-model. BACKGROUND OF POWER QUALITY REGULATION IN FINLAND The Finnish Energy Market Authority presented efficiency benchmarking in 1999. Efficiency scores were calculated by using Data Envelopment Analysis (DEA) with five factors [4]. Power quality was one of those factors. It was measured as a total interruption time of customers. The reason why only interruption time was included in to efficiency benchmarking was insufficient PQ statistics. There was no reliable statistics of other kind of interruption types like number of short interruptions (e.g. auto-reclosing operations). The basic form of efficiency benchmarking with DEA is presented in (1). costs l Operationa c time on Interrupti Customers Network Energy h Max 1 2 3 2 1 0 ⋅ + ⋅ − ⋅ + ⋅ + ⋅ = v v u u u (1) In (1) PQ is measured as a total interruption time of customers. Theory and features of DEA is presented e.g. in [5]. The problems considering insignificancy of certain factors when DEA was used as a regulation tool was presented in [2]. Actual outage cost for company (€/customer,h) could be calculated because of link between efficiency benchmarking and allowed rate of return [6] in distribution business as presented in (2). cost l Operationa time on Interrupti DEA Price Outage ⋅ ∆ ∆ = (2) Where