Probabilistic methods in forecasting hourly loads

Technical Report · Thu Apr 01 04:00:00 EST 1993

OSTI ID:6502751

Engle, R; Granger, C; Ramanathan, R; Vahid-Araghi, ^[1]

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1. Quantitative Economic Research, Inc., San Diego, CA (United States)

EPRI has investigated the use of independent hourly statistical models for short-term load and probabilistic forecasting. Model outcomes compared favorably with observed and predicted loads. The models performed satisfactorily in generating short-run forecasts of system loads in tightly controlled experiments against a wide range of altemative models and methodologies. In addition to load forecasting, the models also forecast the probability that the predicted load would exceed a prespecified level at each hour of the day. Changes in operational practices and personnel turnover are creating a situation in which new forecasting methods are needed. This report demonstrated that statistical models can be developed to reliably predict hourly loads and form probabilities of extreme events.

• Research Organization: Electric Power Research Inst., Palo Alto, CA (United States); Quantitative Economic Research, Inc., San Diego, CA (United States)
• Sponsoring Organization: EPRI; Electric Power Research Inst., Palo Alto, CA (United States)
• OSTI ID: 6502751
• Report Number(s): EPRI-TR-101902
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
240100* -- Power Systems-- (1990-)
99 GENERAL AND MISCELLANEOUS
990200 -- Mathematics & Computers
COMPUTERIZED SIMULATION
DATA COVARIANCES
DEMAND
FORECASTING
HOURLY VARIATIONS
LOAD MANAGEMENT
MANAGEMENT
MATHEMATICAL MODELS
POWER DEMAND
PROBABILISTIC ESTIMATION
PROBABILITY
SIMULATION
STATISTICAL MODELS
VARIATIONS