Accuracy of electric power consumption forecasts generated by alternative methods: The case of Hawaii

Journal Article · · Energy Sources; (United States)

DOI:https://doi.org/10.1080/00908319408909079· OSTI ID:7074517

Leung, P S; Miklius, W ^[1]

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1. Univ. of Hawaii, Honolulu, HI (United States). Dept. of Agricultural and Resource Economics

A number of alternative methods can be used to generate forecasts of electricity consumption. However, it is seldom possible to compare the accuracy of forecasts generated by different statistical methods. Hawaii provided a unique opportunity for such a comparison because of the availability of the Hawaii Energy Demand Forecasting Model (HEDFM). HEDFM is an econometric-based simulation system designed to provide detailed annual consumption forecasts for various fuel types from 1978 to the year 2005 for the State of Hawaii. This article evaluates the accuracy of electricity consumption forecasts using various commonly employed methods and compares them with forecasts from HEDFM. Traditional forecasting methods based on average historical growth rates or the historical relationships between electricity consumption and key economic and demographic variables such as de factor population and per capita income did not perform well. Quadratic exponential smoothing outperformed all other methods. HEDFM, an econometric model, tracked reasonably well. In particular, simulation results have shown that econometric models such as HEDFM can produce accurate forecasts if independent variables can be predicted with a reasonable degree of certainty.

• OSTI ID: 7074517
• Journal Information: Energy Sources; (United States), Journal Name: Energy Sources; (United States) Vol. 16:3; ISSN 0090-8312; ISSN EGYSAO
• Country of Publication: United States
• Language: English

Related Subjects

29 ENERGY PLANNING, POLICY, AND ECONOMY
296000* -- Energy Planning & Policy-- Electric Power
298000 -- Energy Planning & Policy-- Consumption & Utilization
ACCURACY
COMPARATIVE EVALUATIONS
COMPUTER CODES
DATA
DEMAND
DEVELOPED COUNTRIES
ELECTRIC POWER
ENERGY CONSUMPTION
EVALUATION
EXPERIMENTAL DATA
FORECASTING
H CODES
HAWAII
INFORMATION
NORTH AMERICA
NUMERICAL DATA
POWER
POWER DEMAND
USA