3: Energy Consumption and Demand Tilak Siyambalapitiya EE5003: Energy Systems 3: Energy Consumption and Demand Tilak Siyambalapitiya June 2015

Lecture 1: Energy Consumption and Demand Contents Energy consumption in developed countries and developing countries Regional consumption patterns Sectoral consumption Per-capita consumption Global/Sri Lanka demand for energy Demand growth and forecasting Energy and the economy

Sri Lanka Primary Energy Supply: 2013

Sri Lanka’s Energy Supply:2013 Status: year 2013 EE5053 Lecture 1: May 2009

Sri Lanka’s Secondary Energy Supply:2013 What is primary energy? What is secondary energy ? Secondary energy is the final or intermediate form in which energy is delivered to end-use customers. eg: electricity, charcoal, diesel, gasoline. Losses occur in refining, power generation, T&D. What was the conversion efficiency from primary to secondary energy in 2013 ? Why have petroleum product demand reduced in 2013, when compared with 2012? Similarly biomass ? Status: year 2013 EE5053 Lecture 1: May 2009

Where is the energy used? (2013) Is energy use in households, efficient and productive ? Households and commercial are the largest single consuming group, using almost 50% of the secondary energy. Household end-use efficiency is low (use of firewood). Thus they need a larger secondary energy input to serve the losses as well. Status: year 2013 EE5053 Lecture 1: May 2009

Do the indicators show that Sri Lanka’s Energy Efficiency is improving at Macro-level EE5053 Lecture 1: May 2009 7

Sri Lanka Energy Balance 2013 Read more on Sri Lanka’s Energy Supply and Demand, trends and future outlook Sri Lanka Energy Balance 2013 www.energy.gov.lk EE5053 Lecture 1: May 2009

Worldwide Primary Energy Consumption: Americas

Worldwide Primary Energy Consumption: Europe

Worldwide Primary Energy Consumption: ME and Africa

Worldwide Primary Energy Consumption: ME and Africa

Worldwide Primary Energy Consumption: Summary

ENERGY AND THE ECONOMY ENERGY IS A CATALYST FOR ECONOMIC GROWTH A VITAL INPUT TO MANY PRODUCTS AND SERVICES WIDE DISPARITIES EXIST IN PER CAPITA CONSUMPTION

GROSS DOMESTIC PRODUCT AND GROSS NATIONAL PRODUCT USEFUL DEFINITIONS GROSS DOMESTIC PRODUCT AND GROSS NATIONAL PRODUCT The summation of value added by all the sectors of an economy is known as the Gross Domestic Product (GDP). The estimate of GDP is limited to activities occurring within the country. The net income from abroad is added to GDP to calculate Gross National Product (GNP).

Expressed in two currency terms GDP AND GNP Expressed in two currency terms When measured in the currency of the year, GDP is given in current terms. When measured in the currency of a given reference year, GDP is given in constant terms. The data in constant terms, which do not have the effect of inflation, is useful to estimate the real growth of the economy or its sectors.

ENERGY INTENSITY IN THE ECONOMY ALSO KNOWN AS THE SPECIFIC ENERGY CONSUMPTION OF THE ECONOMY MEASURED IN A COMMON UNIT SUCH AS TONS OF OIL EQUIVALENT (TOE) PER MILLION RUPEES.

Sri Lanka Energy and the Economy

Energy-Economy Elasticities

INCOME (GDP) ELASTICITY OF ENERGY DEMAND TYPICAL VALUES OF INCOME (GDP) ELASTICITY OF ENERGY DEMAND Developing countries usually have high GDP elasticities of energy demand. Developed countries are more likely show GDP elasticities of about 1.0. A strong emphasis on energy conservation and a move towards less energy intensive industries, may even cause the elasticity to fall below 1.0.

CONCERNS OF POLICY/DECISION MAKERS What is the optimum level of petroleum prices with respect to other alternatives, such as wood fuel and electricity ? What is the technical and practical feasibility of substituting petroleum products with other forms of energy ? What is the price-elasticity of demand for each petroleum product ? What are the cross-price elasticities between petroleum products ? How does the income of the users affect the demand for these products ?

Price Elasticity of Demand Self-price Elasticity Sensitivity of the demand for an energy product to its own price Highly price elastic Price inelastic

Price Elasticity of Demand (Contd.) Cross-price Elasticity Sensitivity of the demand for an energy product to to the price of another energy product.

Self- and cross- price elasticities EXAMPLE Self- and cross- price elasticities of an energy market Gaso- Diesel Kero- Electri- LP Gas line sene city Gasoline -1.4 +0.3 +0.1 0.0 +0.1 Diesel +0.8 -0.9 +0.1 +0.2 0.0 Kerosene +0.3 +0.5 -0.2 +0.1 +0.1 Electricity +0.1 +0.2 0.0 -0.7 +0.1 LP Gas +0.2 0.0 +0.1 +0.2 - 0.5

Income Elasticity of Demand Sensitivity of the demand for an energy product to the income of its users (or the country).

Income Elasticity of Demand (Contd.) Energy Product IED Electricity 0.1 Kerosene - 0.2 LPG 0.2 Fuelwood - 0.4

ENERGY DEMAND FORECASTING The future is uncertain, and all forecasts, therefore, will be finally proved to be inaccurate !!!

THEN WHY PREPARE FORECASTS ? PLANS REQUIRE THEM !!! To develop capacity expansion plans. eg:- Power stations, transmission lines, oil refineries, fuelwood supplies. To develop financial plans for supply institutions. eg:- Investment plans, revenue forecasts, pricing studies To develop Institutional Plans eg:- Manpower For various other studies eg:- Energy Management

FORECASTING TIME-FRAME Long Term (15-30 years) for planning oil exploration, power stations or firewood supplies Medium Term (5-15 years) for facilities planning. eg. oil refinery, power transmission planning, pricing studies. Short Term (1-5 years) for distribution planning, cashflow analysis, budgeting Very Short Term (from the next hour up to 1 year) for operations planning of energy facilities.

COVERAGE OF VARIOUS FORECASTS

FORECASTING TECHNIQUES Time Trend Analysis Time Series Analysis Econometric Methods End-use Methods Combinations of two or more of the above techniques, are also common. These are known as hybrid techniques. eg:- Econometric end-use technique

The 20-year compound growth rate is, TIME-TREND ANALYSIS The 20-year compound growth rate is,

TIME-TREND ANALYSIS (CONTD.) EXPONENTIAL TREND MODEL LINEAR TREND MODEL EXPONENTIAL TREND MODEL

TIME-TREND ANALYSIS (CONTD.)

TIME-SERIES ANALYSIS Development of a function or functions to describe the quantity to be forecast, by means of its own values in the past. Time series analysis addresses issues related to a shorter time-step. This is because cyclic patterns are more evident on time steps shorter than 1 year.

TIME-SERIES ANALYSIS- MOVING AVERAGE AND EXPONENTIAL SMOOTHING MOVING AVERAGE EXPONENTIAL SMOOTHING

TIME-SERIES ANALYSIS- AN AUTOREGRESSIVE MODEL

ECONOMETRIC MODELS Analysis of historic correlation between energy demand and other economic variables and use such relationships to project future demand. A typical econometric equation EXOGENOUS VARIABLES (Independent of the demand) GDP, Population and Energy price ENDOGENOUS VARIABLES (Determined within the model)

ECONOMETRIC MODELS- DRIVING VARIABLES Macroeconomic Variables:- Economic activity, population, value added in industry, number of households, vehicles population, degree of rural electrification etc. Energy Prices Seasonality:- Weather data (temperature, relative humidity, wind speed, rainfall) and other factors giving rise to cyclic performance A complete econometric model to forecast energy demand will consist of a number of equations, with at least one equation for each energy product. There have to be an adequate number of equations to forecast endogenous variables.

Eg: DEMAND FOR TRANSPORT FUELS R-SQUARED and t-statistics are acceptable.

LINEAR FORM OF THE ABOVE RESULTS OF REGRESSION ANALYSIS DEMAND FOR TRANSPORT FUELS A DIFFERENT MODEL LINEAR FORM OF THE ABOVE RESULTS OF REGRESSION ANALYSIS R-SQUARED and t-statistics are acceptable. (National) Income elasticity of demand for transport fuels is 0.764.

OTHER MODELLING AND FORECASTING TECHNIQUES End-use Methods The demand forecast moves to the lowest possible level of disaggregation, often to the level of the device that converts energy to its useful service.

OTHER MODELLING AND FORECASTING TECHNIQUES Informed Opinion (Judgemental) Eg:- A group of knowledgeable persons may jointly discuss and understand all the underlying issues, study contributing factors such as historic price-elasticity of demand and world population growth, to make a judgemental forecast of the demand for crude oil in year 2020.