Load Forecasting Benchmarking and Best Practices

Table of Contents

• Table of Contents
• Energy Insights Opinion
• Executive Summary
• The Main Points
  • Energy and peak forecasting
  • Day-ahead forecasting
  • Revenue forecast
  • Forecasts of economic factors
  • Weather data
  • Resources
  • Business processes
• Introduction
• Overview
  • Scope of electric load forecasting
  • Electric load forecasting clients
  • Table: Study Respondents
  • Figure: Scope of Electric Load Forecasting Activities
  • Figure: Internal Clients for Electric Load Forecasts
  • Figure: Regulatory Requirements
• Electric Energy and Peak Forecasting
  • Forecast structure
    • Energy forecast structure
    • Figure: Unit of Analysis for Energy Forecast
    • Figure: Forecast Level for Energy Forecast
    • Figure: Energy Forecast Cycle
    • Peak forecast structure
    • Figure: Unit of Analysis for Peak Forecasts
    • Figure: Time Horizon for Peak Forecasts
    • Figure: Peak Forecast Cycle
  • Forecasting approach
    • Energy forecasting approaches and software tools
    • Figure: Modeling Approach for Energy Forecasts
    • Peak forecasting approaches and software tools
    • Figure: Modeling Approach for Peak Forecast
    • Figure: Peak Forecasting Software Tools
    • Forecasting load factor
  • Forecast adjustments
    • Conservation and DSM programs
    • Figure: Utilities That Incorporate Energy Conservation or DSM Programs into Forecast
    • Self-generation
    • Figure: Utilities That Incorporate Self Generation into Forecast
  • Evaluating the forecasts
  • Figure: Accuracy Target for Energy Forecasts
    • Peak
  • Forecast scenarios and risk assessment
  • Figure: Types of Scenarios for Energy Forecasts
  • Forecast review and approval
    • Analyzing variance
    • Weather-normalizing sales
    • Figure: Frequency of Variance Analysis
    • Figure: Approach for Weather-Normalizing Actual Sales
    • Figure: Time Horizon for Day-Ahead Forecasts
  • Accuracy
  • Forecast scenarios
  • Figure: Accuracy Target for Day-Ahead Forecasts
• Forecasting Revenue
• Figure: Time Horizon for Revenue Forecast
• Forecasting Economic Factors
• Figure: Sources of Economic and Demographic Variables
• Forecasting Switching Rates for Customer Choice
• Weather Data
  • Energy and peak forecast
  • Figure: Sources of Weather Data for Energy and Peak Forecast
  • Figure: Location of Forecasting Department Within Organization
  • Staffing
  • Figure: Number of Load Forecasting Staff by Utility Size
  • Budget
  • Figure: Load Forecasting Budget
  • Consultants
  • Figure: Use of Consultants for Energy and Peak Forecasts
  • Conferences and groups
• Business Practices
  • Communication with other utility departments
  • Hot issues now and then
• Appendix - Load Forecasting Benchmarking and Best Practices Study Topic Guide 2005
  • Introduction
  • Screening
  • A. Utility Overview
  • B. Load Forecasting Scope
    • B1. Energy forecasting
    • B2. Peak demand forecasting
    • B3. Day-ahead or next-day forecasting
    • B4. Forecasting Revenue
    • B5. Forecasting Load Factor
    • B6. Forecasting Economic Factors (including Customer Growth)
    • B7. Forecasting Switching Rates for Customer Choice
    • B8. Summary and discussion of other forecasts
    • C. Weather data and other forecast data
    • D. Other forecasting topics
    • E. Staffing and budget
    • F. Wrap up
    • G. Confidentiality
  • Synopsis