Comparison of Methods for Verification of Energy Efficiency Improvements
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Grant #: 98-04
Principal Investigator: Ron M. Nelson
Co-Principal Investigator: Daniel A. Ashlock
Organization: Iowa State University
Students Supported: Zhiqiang Chen
Mission Area: Energy Efficiency
Background and Significance
The purpose of this project is to investigate methods for verifying post-retrofit energy savings using available data from existing buildings. Common methods for determining energy savings are being classified and a new method is being developed. The outcome of this work is expected to increase the reliability of assessing post-retrofit energy savings in buildings and therefore increase the acceptance and implementation of more energy-efficient improvements.
Energy savings can be determined by first documenting the performance of the existing building before a retrofit is implemented. Pre-retrofit information, such as utility, occupancy, and weather data, is used to develop a baseline model of how much energy the building would have used if the retrofit had not been made. Then, the energy savings can be calculated as the difference between the baseline model (using post-retrofit input information) and the actual post-retrofit energy use.
The models used to determine retrofit savings require very little building design data and are not building simulation models. Commonly used models for assessing the effects of energy improvements, such as the degree day and bin methods, are less accurate than more detailed models. Models that use hourly data are more accurate, but they generally require advanced data analysis methods to take advantage of the additional data. Data loggers and sensors are becoming less expensive, making hourly data collection on buildings practical. Buildings with energy management and control systems can be modified to collect hourly data without significant additional costs. Increased computing power has made the more advanced data analysis methods feasible and easier to use.
The work for this project is to conduct a thorough literature search of methods and procedures for verifying energy savings and assess each method for cost, ease of use, accuracy, amount of data needed, computer power needed, noise tolerance, ability to handle missing data, etc. A new method for predicting energy use in buildings from existing data is being developed. Data from two buildings is being used to test and evaluate all of the models.
Project Objective:
The objective of this project is to assess and improve the state-of-the-art for estimating and predicting energy use for existing buildings using available data from those buildings. This project has three major tasks: (1) document available methods for predicting building energy use from existing data, (2) develop a new method, and (3) experimentally evaluate all methods.
Summary of Work to Date:
The work on each of the major tasks for this project is summarized below.
Document Available Methods
There are many methods that can be used to model the energy use of a building using energy and performance data from that building. The methods for baselining building energy use that have been considered so far include:
- Degree Day Method
- Bin Method
- Multiple Linear Regression
- Principal Component Analysis
- Calibrated Simulation
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Objectives
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