# Presentation: 672341

## Short-Term Energy Forecasting

- A Presentation to the Bangladesh Ministry of Energy and Natural Resources
- September 20 - 23, 1999
- Tancred C. Lidderdale
- Energy Information Administration
- U.S. Department of Energy

## Natural Gas Demand

## Bangladesh Natural Gas Demand per Capita

**Notes:**
U.S. per capita natural gas demand = 76,000 cu feet per year

## Bangladesh Natural Gas Demand

**Non-Energy**

**Power Generation**

**Industrial**

**Residential**

**Commercial**

## Natural Gas Demand Shares

**Bangladesh 1994-95**

**United States 1998**

## Slide 6

**Notes:**
Demand Side Inputs
 Residential sector - number of houses, weather
 Commercial sector - commercial employment, weather
 Industrial sector - price ratio (natural gas/residual fuel), weather, gas consumption for electric power by nonutilities
 Electric utilities - electricity generation by electric utilities
 Oil and gas well operations - natural gas production
 Pipeline fuel - total natural gas demand

Supply Side Inputs
 Domestic gas production - exogenous
 Net Imports - time trend
 Withdrawal from storage - balancing item
 Other gas fuels - constant with seasonal variation

## Bangladesh Natural Gas Demand

**Power Generation** = function of electricity generation from natural gas
**Non-Energy** = function or industrial production index or Real GDP
**Residential **= function of housing connected to natural gas, weather
**Commercial / Industrial** = function of industrial production index, weather
**Energy Sector Use and Loss** = function of total production

## Electricity Demand

## Bangladesh Electricity Demand per Capita

**Notes:**
U.S. per capita natural gas demand = 76,000 cu feet per year

## Bangladesh Electricity Demand

**Industrial Sector**

**Losses & Own Use**

**Residential**

**Other**

**Commercial**

## Electricity Demand Shares

**Bangladesh 1994-95**

**United States 1998**

## Slide 12

**Notes:**
Demand Side Inputs
 Residential sector - number of houses, weather, and time trends 
 Commercial sector - total employment, weather, and time trends
 Industrial sector - industrial output indexes, weather
 “Other” sector - real GDP

Supply Side Inputs
 Oil-fired generation - balancing item
 Gas-fired generation - market price ratios, total electricity generation, hydroelectric generation, nuclear generation, and geothermal generation
 Coal-fired generation - market price ratios, total electricity generation, hydroelectric generation, nuclear generation, and geothermal generation
 Nuclear power generation - exogenous
 Hydroelectric generation - exogenous
 Other renewables generation - time trend
 Net sales by nonutilities - exogenous
 Net Imports - exogenous
 Distribution losses and discrepancy - total electricity demand

## Evaluate Weather ImpactsWith Monthly Data Model

- Change in Electricity Demand With 10% Colder Weather

- Residential Sector

- Commercial Sector

- Total Demand

## Some Demonstrated Model Properties

## Energy Demand Impacts

**10% Colder Winter**

**Percent Deviation from Base**

- -1

- 0

- 1

- 2

- 3

- 4

- 5

- 6

- 04/97

- 07/97

- 10/97

- 01/98

- 04/98

- 07/98

- 10/98

## Energy Demand Impacts

- Total Energy

- Demand

- Total Petroleum

- Demand

- Total Nat. Gas

- Demand

- Total Coal

- Demand

- Total Electricity

- Sales

- Percent Deviation from Base

**0.0**

**0.5**

**1.0**

**1.5**

**01/97**

**04/97**

**07/97**

**10/97**

**01/98**

**04/98**

**07/98**

**10/98**

**Energy Demand Impacts**
**1 Percent per Year Higher Economic Growth**

## A U.S. Hydroelectric Power Scenario

**10**

**15**

**20**

**25**

**30**

**35**

**01/95**

**07/95**

**01/96**

**07/96**

**01/97**

**07/97**

**01/98**

**07/98**

**04/95**

**10/95**

**04/96**

**10/96**

**04/97**

**10/97**

**04/98**

**10/98**

**A U.S. Hydroelectric Power Scenario**
**Continued High Hydroelectric Availability**

**Base**

**No Change from**
**Previous Year**

**Billion Kilowatt-hours**

## U.S. Electricity Supply Impacts

**Elec. Utility**

**Hydro.**

**Generation Bill**

**Kwh**

**Elec. Utility Coal**

**Generation Bill**

**Kwh**

**Elec. Utility Nat.**

**Gas Gen. Bill**

**Kwh**

**Deviation from Base**

**-2**

**-4**

**-6**

**0**

**2**

**4**

**6**

**8**

**04/97**

**07/97**

**10/97**

**01/98**

**04/98**

**07/98**

**10/98**

**U.S. Electricity Supply Impacts**
**Continued High Hydroelectric Availability**

**Billion Kilowatt-hours**

## U.S. Natural Gas Market Impacts

**High Hydro Case**

**Total Natural Gas**

**In Underground**

**Storage**

**Natural Gas Spot**

**Price**

**Total Nat. Gas**

**Demand**

**Percent Deviation from Base**

**-1**

**-2**

**-3**

**-4**

**-5**

**-6**

**0**

**1**

**2**

**04/97**

**07/97**

**10/97**

**01/98**

**04/98**

**07/98**

**10/98**

## Evaluating Forecast Error

## Evaluating the Forecast Model

- Within-sample forecasting error
- Post-sample forecasting error with predicted values for right-hand side variables
- Post-sample forecasting error with actual values for right-hand side variables.

**Notes:**
Within-Sample Forecasting Error:
 Difference between actual historical outcomes and predicted outcomes using an equation that was estimated using all historical data.

## Measurements of Error

- Regression Model Error
- Mean Error
- Mean Square Error (MSE)
- Root Mean Square Error (RMSE)
- Mean Absolute Error (MAE)
- Mean Percentage Error (MPE)
- Mean Absolute Percentage Error (MAPE)
- Thiel Statistics

## Forecast Uncertainty

- Account for the stochastic nature of model equations and exogenous (right-hand side) variables
- Use a Monte Carlo procedure
- Requires information on
- regression equation error distributions
- regression equation estimated parameter covariances
- probability distribution of exogenous variables
- Repeated simulations following random “draws” from the distributions of the equation error, parameters, and exogenous variables

## Slide 24