A Framework for Estimating and Communicating the Financial Performance of Energy Efficiency Improvements in Existing Commercial Buildings While Considering Risk and Uncertainty

A Framework for Estimating and Communicating the Financial

Performance of Energy Efficiency Improvements in Existing

Commercial Buildings While Considering Risk and Uncertainty

Alireza Bozorgi, MArch, MSc

Ph.D. Candidate in Design Research | MBA

College of Architecture and Urban Studies | Pamplin College of Business

Virginia Polytechnic Institute and State University

James R. Jones, Ph.D.

Associate Professor of Architecture

College of Architecture and Urban Studies

Virginia Polytechnic Institute and State University

Abstract

There is substantial evidence suggesting that property professionals, such as owners, investors and

lenders who are involved in the investment decision-making process are increasingly interested in

energy efficiency improvements (EEIs). One of the primary barriers to EEI is a lack of clear

information regarding the true value, both revenue and risk, of EEI investments. EEI investments

often include many non-quantifiable benefits as well as risks that current energy performance

assessment tools and methods do not simultaneously incorporate. Nor are the outcomes typically

presented in appropriate terms to be understood and utilized in the investment decision-making

process.

In this paper, an analytical method and systematic framework is proposed to evaluate the financial

performance of EEI alternatives in existing commercial buildings, while simultaneously addressing the

risks and uncertainties associated with the process. The framework is a robust valuation process that

takes EEI alternatives, uses current energy simulation programs to forecast estimates of the energy

efficiency outcomes, links the predicted building performance to financial model inputs, and derives

ranges/distributions of their bottom line financial performances. A Monte Carlo simulation model,

based on the Discounted Cash Flow approach, is suggested for modeling the uncertainties of

valuation process and estimating the...