Monitoring Performance Of Electric Utilities
Monitoring Performance of Electric Utilities: Indicators and Benchmarking in Sub-Saharan AfricaMonitoringPerformance ofElectric UtilitiesIndicators and Benchmarkingin Sub-Saharan AfricaPrasad Tallapragada V.S.N.Maria ShkaratanAda Karina IzaguirreJaakko HellerantaSaifur RahmanSten Bergman2009
MonitoringPerformance ofElectric Utilities:Indicators andBenchmarkingin Sub-Saharan AfricaPrasad Tallapragada V.S.N.Maria ShkaratanAda Karina IzaguirreJaakko HellerantaSaifur RahmanSten BergmanWorld Bank2009
Table of ContentsI.Introduction4II.Defining Key Performance Indices (KPIs)6III.Making Sense of Performance Monitoring Indicators10IV.Benchmarking Main Performance Indicators18Capacity FactorLoad FactorOperating RatioElectric Power Consumption per CapitaHousehold Access to ElectricityQuality of Service, Customer Perspective: Outages and Delay withConnectionResidential TariffsAccounts ReceivableCost Recovery RatioOperating Expenses Covered by Revenues18202325303538414345Annex I. Sources of Data47Annex II. Indicators of Power Utility Performance in Literature47Annex III. Glossary of Indicators and Terms60Annex IV. Country Data Tables75Annex V. Country Data Graphs180Literature2561
PREFACEThis publication is an outcome of the initiative “Electric Utility - Capacity AssistanceProject for Africa” (EUCAP), which was developed in the Africa Energy Group of theWorld Bank and financed by the Energy Sector Management Assistance Program(ESMAP). The initiative was prepared as a component of the Regional strategy plan toexpand capacity in key African institutions and sectors. The core of the initiative iscreation of a knowledge-based information-sharing network of African electric utilitiesto pursue the goal of improved utility efficiency. Knowledge-based cooperation amongcountries is receiving more and more emphasis in regional strategy and approaches todevelopment in Africa. As the Africa Region’s Vice President Oby Ezekwesiliemphasized in her recent speech “Focus on Innovation, Results, and Knowledge Agenda”(October 14, 2009), “a stronger focus on results and the knowledge agenda” have becomecrucially important as “the global crisis has led to stronger demand for developmentimpact from the limited resources available”. Focus on knowledge-based cooperation wasre-emphasized by Colin Bruce (Director of Strategy and Operations, Africa Region) whostressed “a tremendous appetite” “to learn from best practices adopted in othercountries”.The World Bank lending to infrastructure in Africa, a large part of which benefits thepower sector, has been substantially increasing in the recent past. Talking to the press in2005, Michel Wormser (Director of Strategy and Operations, Africa Region), said: “In2000 we were lending about US 600 million to the African continent for infrastructureand this year we are going to lend US 1.8 billion. We are foreseeing a further 30%increase, so by the end of the next couple of years, we will probably be at US 2.4 billionto US 2.6 billion a year,” he said. This forecast was precise - the World Bank Africainfrastructure lending reached 2.4 billion in 2007. In 2009, the World Bank financingfor infrastructure-related programs and projects in Africa reached US 3.3 billion. Almost40% of it is power sector lending. Considering this high level of the World Bank'sinvestment in the power sector, it is crucial to assure that the African power utilities haverelevant capacity to use these resources efficiently and to their maximum benefit.The outcomes of the work under the umbrella of this initiative include creation of acomprehensive electricity sector database Africa Support Kiosk for Electric Utilities(ASK) and this publication. The initiative is planned to continue, with transferring thedata and the data collection methodology to African partner institutions and with a set ofactivities aimed at building capacity of knowledge-sharing among African utilities.2
ACKNOWLEDGEMENTThe authors are very grateful to S.Vijay Iyer (Sector Manager, AFTEG) and Tjaarda P.Storm Van Leeuwen (Adviser, AFTEG) for their review, valuable guidance, advice andsupport throughout the preparation of the publication. Invaluable advice and generalguidance of Inger Andersen (Director, AFTSN), John H. Stein (acting Director, AFTSN)and Jose Luis Irigoyen (Sector Manager, AFTSN) are highly appreciated. The authorswould like to express special gratitude for the advice and support received fromAmarquaye Armar (Program Manager, ESMAP). Cooperation with the AICD team wasvery important for the success of their work. The team expresses gratitude to VivienFoster and Cecilia Briceno-Garmendia (AICD Task Team Leaders), Sudeshna GhoshBanerjee, Fatimata Ouedraogo, Daniel Camos and Maria Shkaratan (AICD Energy sectorteam) for their valuable comments, many brain-storming meetings, cross-team supportand day-to-day cooperation with the authors in relation to the database design. Theauthors are grateful to the AICD team for allowing the use of the AICD data in thispublication.This publication was prepared as part of the Electric Utility Capacity Assistance Program(EUCAP) for Africa. The authors would like to thank Arun P. Sanghvi (AFTEG), andAbdolreza B. Rezaian (AFTEG), Marjorie K. Araya (ESMAP, AFTEG) and Marie LoloSow – team members of the Program – for their valuable involvement, ideas and support.The publication was made possible by close cooperation with the World Bank Instituteteam – Adarsh A. Desai, Arseny Malov, Kirill Puklyakov, Oxana Minchenko, JeeyeonSeo, Steffen Janus – who designed the Africa Support Kiosk for Electric Utilities (ASK)website. The team is thankful for their expertise and high quality outcomes. Importantadvice and country specific information were provided by the entire AFTEG team andthe ESMAP colleagues.Collaboration with the African Energy Commission (AFREC), Union of AfricanElectricity Producers, Distributors and Conveyors (UPDEA) and partner governmentswas essential for this work. The authors are grateful to the managers and specialists ofAfrican power utilities for cooperation and sharing the utility level data.The authors appreciate being able to find valuable data necessary for analytical work inthe following published sources: African Development Bank (AFDB), the United StatesAgency for the International Development (USAID), Energy Information Administration(EIA), International Energy Agency (IEA), Demographic and Health Surveys, WorldBank Group Enterprise surveys and IDA-14 Results Measurement System.3
I. IntroductionPerformance of electric utilities is essential for the reform of the electricity sector inthe Sub-Saharan Africa (SSA) countries. The World Bank is leading a number ofinitiatives to improve electric utility performance in SSA. The Africa Energy unit ofthe World Bank recently introduced the Electric Utility Capacity AssistanceProgram (EUCAP) for Africa. Among other activities, the EUCAP aims to collaterelevant utility performance data within the context of the Bank operations, with thedual objective of assessing the impact of reforms and motivating utilitymanagement to achieve better outcomes.In order to reach this objective, performance benchmarking approach wasdeveloped. In this approach, benchmarking starts with the selection of the KeyPerformance Indices (KPIs) reflecting major elements of utility day-to-dayoperations, including technical, operational and financial. Then a framework tocompare performance of the sector in various countries and among utilities usingthese indices is applied.Once the KPIs were identified and the benchmarking approach was developed, thenext step consisted of compiling indicators corresponding to each KPI. Data foreach indicator were collected from various published sources. When the neededindicators were not available from published sources, the data were obtained fromthe stakeholders (i.e., utility managers, engineers, planners, etc.).The resulting database Africa Support Kiosk for Electric Utilities (ASK)1 is theoutcome of a major data collection and presentation effort by a World Bank teamincluding specialists from the Africa Energy Group (AFTEG), Finance Economicsand Urban Department (FEU) and the World Bank Institute (WBIGM). Theobjective was to collect data for the selected electricity sector indicators from allsources available and present them on the web in a form that would be useful for alltypes of potential audiences within and outside the World Bank: utility managersand specialists, policy makers, energy sector practitioners, researchers and widerpublic. The program responds to a critical need for a central database withcomprehensive electricity sector data that has been expressed numerous times byboth practitioners and researchers.The program was coordinated with the Africa Infrastructure Country Diagnostic(AICD) study to maintain consistency in indicator selection and data presentation.AICD study is one of the most important sources of data for the ASK database. Theprogram also took into consideration the findings of a recent major electricity sectorperformance monitoring exercise – Latin America and the Caribbean (LAC)1The database can be found on the web: http://etoolsdev/ask4electricutilities new/4
electricity benchmarking study.The ASK database presents electricity sector data for the countries of the SubSaharan Africa. It is a comprehensive dataset and as such includes over 130 seriesand more than 23,000 data points for 47 countries and 42 electric utilities in SubSaharan Africa for the period from 1990 to 2007. It covers five areas: power systemcapacity, power system operations, service provision to customers and financialcharacteristics of the sector and the utility.In addition to being a centralized source of a wide range of power sector data, theASK database offers an analytical framework to conduct comprehensiveexamination of the SSA power sector and utility performance with regards to theirtechnical and commercial efficiency and financial soundness. This framework isreflected in the database structure and presentation on the web, the combination ofwhich enable, in a simple and user friendly way, in-depth examination of the powerutility and sector performance in the SSA region. The website users can view,compare, simulate and analyze the performance data of SSA electricity utilities,create a full picture of power sector performance in a particular country, or comparesector characteristics in different countries.The ASK database time series will be continued in the future to maintain thedatabase over the years and provide information for longer-term electricity sectormonitoring, which would help improve utility performance in a consistent manner,based on comparable time series data.The ASK database presents non-edited data, kept the same as they are in theoriginal sources. Available data, when put together, in many cases forms time serieswith gaps and reveals the inconsistency in data from different sources. The ASKdatabase authors did not edit or eliminate any of the data series, but rather aimed atmaking the database fully inclusive, consistent with its comprehensive character. Atthe same time, efforts were made to label the data in a clear way, so that the usercan make an informed decision on data selection and validity. Alternatively, theuser can choose to rely on the authors of the ASK database in the selection of thesource for a particular indicator in cases when more than one source is available: thedatabase marks one of the sources as preferred.The users have an option of editing the data and commenting on the data. Editingcan be done using downloadable Excel files on the ASK website. The contact e-mailaddress for edits and comments is provided on the website, under the menu option“Challenge the data”. Potential contributions of the database’s users to fill the gaps,expand coverage, and resolve inconsistencies in the data, all of which are critical forincreasing the value of the database, will be highly appreciated.5
II. Defining Key Performance Indices (KPIs)The final set of KPIs, compiled after extensive discussions and consultations withpractitioners, is presented in Table II.1. The KPIs form three categories:“Technical”, “Commercial” and “Technical and Operational Capabilities”. Thetable has the KPI’s name, code, unit of measurement and its broad definition. Thefinal set of KPIs formed the basis for the indicators of the ASK database: each KPIwas translated into one or more database indicators. After that, data correspondingto each indicator were collected from available published sources. Annex IV “ASKDatabase: Country Data Tables” presents a complete list of indicators and datafrom the ASK database for each of the Sub-Saharan Africa countries.Index NameTable II. 1. Final set of key performance indicesUnitBroad DefinitionTechnical IndicesGenerationCapacity/DemandratioCost of ElectricityGeneration /MWhOff-grid/On-gridDemandratioCustomers per kmcustomers/kmSystem Losses% ofsupplyNumber of Outagesper Year#/yrMeasures to what extent installed capacity meets demand.Demand equals actual demand plus demand from connectedcustomers who cannot be served.Measures the cost of producing 1 MWh of electricity. Shouldinclude the cost of power generated internally and procuredexternally by the utility. The total cost is divided by the totalnumber of energy units sold.Reflects how widespread independent grid demand is ascompared with on-grid demand. Due to high costs of off-gridpower, low level of this indicator usually means opportunitiesfor the utility to benefit from connecting off-grid customers tolower-cost power.Measures electrification density of the utility. When bothtransmission and distribution length are included in thedenominator, the measure is less clear, as it is affected by the“profile” of the utility of being transmission or distributionoriented. Therefore, it is best to have separate measures fortransmission and distribution.(Electricity supplied to grid (GWh) – Total electricity billed(GWh))/ Electricity supplied to grid (GWh). Reflects utility’seffort in measuring theft/illegal connections, possiblyaugmented with overloaded system parts. Total lossescombine technical and “non-technical” losses. Technicallosses are typically between 5-10%, while “non-technicallosses” can be 20- 30% and at local level as high as 50%.Measures quality of power supply. Consumer dissatisfactionwith service is often related to high level of outages. Outagescan be caused by generation or network failures.6
Index NameNumber ofTransformer Failuresper YearIllegal ConnectionRateUnit#/yr% oftotalconnectionsBroad DefinitionReflects one of the most common reasons for outages and highO&M costs. Could also reflect low oil based protection, due totheft or non-availability of oil.Estimates how widespread illegal connections are. Reflectsutility’s ability to monitor their customers.Commercial IndicesNational, Urban andRural Access toElectricityConnectivityPotential%Tariff Settings eeratioStaff cost/Total costratioCustomer BillCollection RateTotal O&MCost/Revenue%#%Measures household electrification rate, including connectionto the main grid and a local grid. This indicator might take intoaccount off-grid connections.Number of new households in the country (or the utility area)minus number of new connections per year. A growing valuewill indicate a growing problem.Measures utility’s ability to revise tariffs and adjust tariffschemes in order to cover costs with revenues. For manyutilities, tariff decisions are made politically and not on thecost basis. Often utilities are not compensated for resultinglosses.Indicates to what extent the utility can have cost reflectingtariffs and keep control of investments, costs and bill payment.Measures labor efficiency of utility. The ratio tends to behigher in well-managed, efficient utilities.Measures the weight of staff costs in the cost structure of theutility. Staff costs are a major factor of utility profitability.Revenues collected / Total electricity billed. Showseffectiveness of the utility in bill collection.Operation and maintenance cost as a percentage of utility totalrevenue. Too low O&M cost may result in a need in very highinvestment and O&M cost in the future. Too high O&M costindicate generic problems for the utility.Indices of Technical And Operational CapabilitiesService RestorationScore(0-10)Customer ServiceScore(0-10)Score(0-10)In-house Modeling &Analysis CapabilityMeasures utility’s capability to restore power to as manycustomers as possible in the shortest time possible. The scoreattempts to address typical questions, such as: Does the utilityhave an outage management and service restoration protocolin place? Are good utility practices being followed?Measures ability of the utility to provide customer service suchas handling outages, billing payment, dispute resolution, etc.The index will assess the in-house capability in engineeringcomputation and analysis, system modeling and planning.What software and hardware is available to engineers,planners and managers? Is it used?7
Index NameUnitOngoing Inventory ofSpares and AssetsScore(0-10)Training andManpowerDevelopmentProgramInformationTechnology UseScore(0-10)Availability ofinstallation andmaintenanceequipmentWorkshop and RepairFacilitiesScore(0-10)Technical standardsusedScore(0-10)Utility )Broad DefinitionIndicates how the utility manages its assets and inventory ofspare parts and equipment. Are good utility practices followed,e.g., is a GIS based facilities management system in use?Assesses how the utility addresses its manpower requirementfrom the apprentice linemen to the foremen and engineers. Isthere a training and manpower development program in place?Assesses the extent of IT use in the operation and managementof the distribution utility. These include remote telemetry,SCADA, database, etc. Does the utility use an Intranet? Doesthe utility have adequate web presence?Measures availability of necessary equipment for installationand maintenance of distribution system: vehicles, trucks,cranes, aerial lifts, etc. What percentage of the equipment is inworking order?Assesses availability and capacity level of workshop andrepair facilities in the utility. For example, can transformersand switchgears be repaired in-house?Measures use of appropriate technical standards. Is there asingle “one-system fits all” approach, or do standards varydepending on application, customer mix, local conditions,etc.? Are “low-cost” single-phase standards applied? Areplanning procedures and guidelines updated?Measures autonomy of the utility. Is there a board? Whoappoints the Board members? What role has the board? Howmany directors are there in the utility? Are there incentives forefficiency in daily operations? Is management performancemonitored? What is the role of the Energy Minister?Examples of scoring for selected KPIs:For the KPIs in the technical and operational capability category, some data wereobtained from utility databases or from utilities directly via surveys andquestionnaires. At the same time, some of the indices in this category wereestimated by utility managers and specialists. For this purpose, a scale from 0 (nonexistent) to 10 (best practice in the industry globally) was used. The minimumrequired by an SSA utility can be set at 5, as shown below for selected KPIs.Service Restoration: This index measures utility’s capability in restoring power toas many customers as possible in the shortest time possible. Does the utility have anoutage management and service restoration protocol in place? Are good utilitypractices being followed?8
ScoreZero1-45-78-10Scoring guidelinesUtility with no service restoration plan in placeUtility with ad-hoc restoration proceduresUtility with service-restoration plans and procedures but with resourcedifficult
table has the KPI’s name, code, unit of measurement and its broad definition. The final set of KPIs formed the basis for the indicators of the ASK database: each KPI was translated into one or more database indicators. After that, data corresponding to each indicator were collected from available published sources. Annex IV “ASK
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