Decision-Based Model for Forecasting Tools Selection in the Energy Demand Sector

  • Saud Nasser AlSaleh

Student thesis: Master's Thesis

Abstract

Energy planning tools and methods are vital to maintaining energy security and efficient resource utilization at different time horizons and at different levels: neighborhoods, cities, and even country-wide. The planning process requires adequate and informative historical data, which then can be employed in variety of models for forecasting and predictive purposes. This manuscript surveys these energy-planning tools and classifies them into bottom-up approaches (mainly MARKAL and LEAP), Regression based approaches, time-series modeling, and artificial intelligence based tools. The survey will further discuss these tools and their implementations at different scales, purposes, regulatory environments and energy sources. The presented study concludes that the process of selecting an energy planning tool is not structured and is not guided through an objective decision making methodology. This thesis proposes a Decision-based approach that integrates Quality Function Deployment (QFD) with Analytical Hierarchy Process (AHP) as a basis of the selection process. QFD’s ability to prioritize the voice of customer and map it to the forecasting model’s technical requirements is used to develop criteria for the AHP model that will turn subjective information into numerical that can be weighted and synthesized to find the best energy forecasting model.
Date of AwardMay 2014
Original languageAmerican English
SupervisorMohammad Omar (Supervisor)

Keywords

  • Forecasting Methods; Energy Planning Models; Energy Demand Sector.

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