DEMAND MODELING APPROACH FOR ENERGY SERVICES MODELING COLLOQUIUM 31 JULY Dr R Maserumule Demand Modeling Specialist Department of Energy

Energy Demand in South Africa 2 This what we collect This what we need for the IEP

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South African Context Studies on end use once off – Institute Energy Studies (Early 1990s) – Eskom (2012) – Department of Energy (2009, 2012) 4

Three Basic Approaches to Forecasting Judgmental: Obtained by asking a group of experts about the behavior of the population. Econometric: Obtained by analysing the time series of historical population Engineering: Obtained through small scale studies of a controlled population

Hybrid Approach Phase One: Engineering- Use existing studies on the use of energy carriers for end use services (Institute for Energy Studies 1993, Frost & Sullivan 2012, Department of Energy 2012) Phase Two: Econometric- Project the demand for each energy carrier using historical data (DoE- Energy Balances, Eskom- Electricity Sales) 6

Hybrid Approach Phase One: Engineering- Use existing studies on the use of energy carriers for end use services (Institute for Energy Studies 1993, Frost & Sullivan 2012, Department of Energy 2012) 7

8 Total Energy Services ( TJ) Total Energy Carriers ( TJ)

Overview of Demand Models (112) SectorNumber of Demand Models Residential (4 sub sectors) Low Income Non-electrified Low Income Electrified Middle Income Electrified High Income Electrified 22 demand models Commercial6 demand models Industrial (9 sub sectors) Iron and Steel Basic Chemicals Non-ferrous Metals Rest of Basic Metals Gold Mining Coal Mining Platinum Mining Other Mining Rest of Manufacturing 72 demand models Agriculture9 demand models Transport3 demand models 9

Opportunities for Collaboration Continuous detailed sector studies on end use – Measure carbon footprint – Opportunities for deploying energy efficiency interventions 10

Hybrid Approach Phase Two: Econometric-Project the demand for each energy carrier using historical data (DoE-Energy Balances, Eskom-Electricity Sales) 11

Bottom Up Approach Sector/Sub SectorActivity Variable ResidentialTotal number of households CommercialCommercial floor space AgricultureTons of agricultural output Iron and SteelTons of iron and steel ChemicalTons of chemical Non-ferrous MetalsTons of non-ferrous metals Rest of Basic MetalsTons of output for the remaining metals Gold MiningTons of gold Platinum MiningTons of platinum Other MiningTons of other mining output Rest of ManufacturingTons of production for total manufacturing 12

Opportunities for Collaboration Common dataset for historical energy consumption – DoE energy balances – Eskom electricity sales – Other data sets Common dataset for macroeconomic data GDP growth Activity variables – Population (total number of households) – Physical Production (tons of coal, tons of gold) 13

THANK YOU 14