Promoting Energy Access for the Urban Poor in Africa: Approaches and Challenges in Slum electrification ENERGY DEMAND CHALLENGE IN SLUM ELECTRIFICATION (A Case of Kibera Slum Electrification Project, Nairobi) By Eng. Jared Othieno, Regional Manager, Western Kenya KENYA POWER & LIGHTING COMPANY LTD. 26 th October 2009
Kibera Slum Nairobi, Kenya
Kibera Slum Electrification Project Statistical Data Population: About 750,000 Area Coverage: 6km x 1km Electrifiable households :300,000 Billing: 2.1 Gwhrs against 5.2Gwhrs (restricted load) Revenues: Ksh 2m (USD 25,000) against expected Ksh 5m (US$ 62,500) Pilot 2006 at Ksh 3.3m (USD 41,250) with first connection in March 2007 Phase 1&2 at Ksh 34.4m (USD 403,000) targeting 11,000 customers First 100 customers free internal wiring done with ready boards at Ksh 8m. Response still slow. Only 3,367 out of identified 44,000 paid with 2,611 connected.
Household Load Mapping Model Existing 5 no 315 KVA transformers at peripheral estates to central metering points inside slum. Load details per plot: assumed homogeneity in loads at 14 lighting points and 7 socket outlets with diversity of 0.6 Load mapping done assuming standard loading per plot Load limiters installed to restrict loads and transformers fused appropriately. High plot density restricted each transformer coverage to a radius of 300 m. Thus designed load was : 8 No. 315 KVA Substations.3.780 MVA 2 No. 630 KVA Substations.1.260 MVA Total load..3.780 MVA
Load Mapping Of Kibera
Load Survey Questionnaire
Load Limiters Connections
Typical Additional Unplanned Loads
Typical Additional Unplanned Loads
Bypassed Transformer fused element
Households electricity sources 60,0% 50,0% % of households "Local supplier" Car batteries electricity production equipement (generator / PV) 47,7% 40,0% 37,9% 30,0% 31,3% 20,0% 17,2% 10,0% 10,0% 0,0% 2,7% 0,5% 0,0% SLUM NDZ All zone 1,5% Figure 1: Households equipment rate for electric appliances Source: Customer Connection Policy 2006 EDF / Axenne / Abedares
80% 70% 60% 50% Distribution of economic activities according to the reason of non connection to KPLC grid 54% 69% 61% SLUM ZND All zones 40% 30% 32% 26% 20% 18% 10% 0% 5% 3% 4% Distance from grid 1% 1% 1% Electricity too expensive High cost of connection fees 1% 1% 1% High cost of wiring Rented premise 7% 5% 3% No information available 1% 1% 1% 2% 2% 2% No need for it No response from KPLC Figure 2: Distribution of economic activities according to the reasons of non connection to KPLC grid. Source: Customer Connection Policy EDF / Axenne / Aberdares
Monthly expenditures for the economic activities by type of energie Thermal engine 14% Generators 2% Local supplier electricity 10% Kerosene 48% Small batteries 21% Car batteries 3% Candles 2% Figure 3: Distribution of the economic activities expenditures by types of energy Source: Customer Connection Policy EDF / Axenne / Aberdares
Monthly households energy expenditures Audiovisual 437 17% Lighting C ooking and heating 1 338 54% 740 29% 2515 Ksh per household per month Figure 4: Households expenditures by use Source: Customer Connection Policy EDF / Axenne / Aberdares
Monthly households energy expenditures by energy Battery loading 55 2% Candles 12 0% Electricity 139 6% Fire wood 94 4% cells 466 19% Charcoal 640 25% Gas 81 3% Kerosene 1 028 41% 2515 Ksh per household per month Figure 5: Monthly household expenditures by energy sources Source: customer connection policy EDF / Axenne / Abadears
Competitive Energy Source
Socio-Economic Factors Affecting Energy Demand in Kibera Slum Electrification Demography: Dynamic shifts in usage in the households /businesses Cultural practices & lifestyles in the various villages Compartmentalization of Kibera into ethnic and economic groups. Conversion from other energy sources: Barriers by utility in wiring costs, connection charges and long processes. Local providers coercing and threatening would be customers. Goal incongruence between tenants and landowners Technology in use: Load limiters suppressed natural load growth. Obsolete technology (turrets) with no back up materials Pre-payment metering system provides load growth freedom but large cost outlay.
Socio-Economic Drivers Challenge in Energy Demand in Kibera Benefits to Utility Cont d Policy & Regulation Land tenancy affecting spending on fixed luxurious items (no refrigeration loads) Effects of the KENSUP upgrading program Use of Life-line tariff restricts natural load growth ERB tariff approval had no special slum tariff Limited financial gains for the utility. Others Aggressive demand side management interventions/renewable energy sources. Security of early entrants from cartels Customers payment mode and back up support system discourage growth.
Way Forward Engagement of social scientists to complement marketers in market survey. Use of integrated approach to inform on load growth patterns. Analytical methodologies for qualitative analyses of socio-economic drivers of energy demand. Campaign for tariffs that can benefit both slum users and utility. Source for funding of prepayment metering systems to enhance customer flexibility in energy use. Analytical methodologies to measure receptivity of slums dwellers to the slum electrification programs.
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