Incorporating DSM impacts in econometric models: Results from a recent model enhancement study by the New York State Electric & Gas Corporation

Technical Report · Mon May 01 04:00:00 EDT 1995

OSTI ID:103269

Golemboski, W J ^[1]; Ferris, F S ^[2]

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1. Applied Energy Group, Inc., Binghamton, NY (United States)
2. New York State Electric & Gas Corp., Binghamton, NY (United States)

Many utilities in the U.S. today continue to offer full-scale DSM programs aimed at reducing energy consumption and peak demand usage. Indeed, recent impact evaluation studies purport to show significant cumulative energy reductions that have been quantified in billing analysis studies of energy savings. Load forecasters now confront a clear need to account for these impacts in company sales forecasts. This is a particularly challenging task for utilities that still rely on econometric models to forecast sales. To-date, there is still no clear consensus with regard to how the impacts of DSM programs should be accounted for in econometric models and forecasts. This paper presents the results from a recent study conducted by the Applied Energy Group for New York State Electric & Gas focusing on an evaluation an assessment of alternative techniques for integrating DSM impacts from the company`s programs within the existing set of short-range econometric models used to forecast customer class sales. Specifically, this study will examine the following forecast adjustment methods currently used by utilities across the U.S. to account for DSM impacts; (1) Ex-post adjustments to the sales forecasts w/no modifications to the models. (2) The use of dummy and spline variables in econometric models to account for DSM impacts over time. (3) Adding-in DSM impact estimates to the sales history and re-estimating the models. (4) Incorporating index variables reflecting changes in appliance/equipment stock average efficiencies resulting from company DSM programs. This paper will review the strengths and weaknesses of each of these approaches with particular attention placed on the construction of energy efficiency index variables to capture the impacts of DSM. The index variable method will be illustrated using sales data, econometric models and simulation analysis results developed in the NYSEG study.

• Research Organization: Electric Power Research Inst., Palo Alto, CA (United States); Pacific Consulting Services, Albany, CA (United States)
• OSTI ID: 103269
• Report Number(s): EPRI-TR--105012; CONF-930969--
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
ECONOMETRICS
ELECTRIC POWER
ELECTRIC UTILITIES
ENERGY CONSUMPTION
FORECASTING
LOAD MANAGEMENT
PLANNING
POWER DEMAND