CEE 143/243: Predicting and Measuring Building Energy Use

Overview: Spring 2012

Overview
Organization
Reading

 

Class overview:

Building Energy prediction and performance monitoring is quickly becoming a key issue in the building life cycle. Advanced methods incorporate performance predictions from early design that are updated as a project evolves. This life cycle approach minimizes operational energy use by comparing measured building data against performance predictions as provided by a whole-building energy simulation model. 

The class will perform a multi-year, in-depth analysis of building energy systems monitoring and performance analysis and report on the conclusions of the class about how to validate performance predictions given monitored results and how to assess and validate the effectiveness of engineering system interventions to improve energy performance. It explores building measurements and the most appropriate tools and techniques for detailed understanding of holistic building operation.

The class will:

  • Explore methods to retrieve, plot, analyze and interpret the significance of monitored energy system performance over time, relate design intent and predictions to measurements and develop guidance for performance analysis on how to use these methods in practice;
  • Apply these methods to in-depth, time-based analysis of a modern building (Stanford's Y2E2 building) for which detailed energy use data and building engineer reports are available for analysis;
  • Explore the building spaces systems in person with a guided building visit providing background and manual energy audits to make independent measurements, note occupancy and occupant assessment of comfort, and relate audited information with automatically monitored data;
  • Make assessments to the owner about effectiveness of interventions to building and systems operations that have been made during previous years;
  • Make recommendations to the owner about methods to model the building, methods to do energy analysis, methods to collect actual energy performance data, methods to interpret intended, predicted and measured performance, methods to validate predictions and methods to validate engineering changes. These recommendations have the potential to make a real-world impact on the facility itself and, over time, on other many buildings throughout the county.

Background: in 2009, students looked at stated Y2E2 building objectives for energy system and component performance and compared them with quantitative predictions and measured values obtained from the online monitoring system. Findings of the 2009 class study included that students with no prior background could successfully access and interpret measured energy performance data from the data acquisition computer; overall building energy use met code objectives but dramatically exceeded initial design objectives; some HVAC components and systems worked well and others did not work as planned, and a gifted set of students together worked about a thousand hours to interpret only about ten percent of the available data, which strongly indicates that the current process to access and interpret data is not sufficiently routine and automated to allow effective continuous energy system commissioning on a significant commercial scale. Using more highly-developed analysis tools, students in 2010 looked at a large existing facility that had significant sensing but more limited than Y2E2. Findings were that analysis methods were much easier to use; some systems and components worked well while many did not.

Methods: The class will run as a seminar in which participants investigate different issues and share with each other. There will be a few formal lectures. A guided building visit will provide guidance and background. Students will create, submit and discuss responses to queries throughout the quarter. There will be a final project presentation and report.

Homework is designed to allow student to quickly begin to analyze real building performance.  Individual assignments in the first two weeks will give experience in using building databases, energy simulation tools and methods for data processing.  Beginning in the third week, group-based work will focus in detail on individual building systems and begin to analyze the performance of that system in depth and compare it with performance predicted by energy simulations.

Prerequisites: admission to the class at the discretion of the instructor. It is desirable to have energy systems or modeling experience, e.g., from prior or concurrent registration in CEE 176A, 226E or 256.

Evaluation: Class grades will be based on query submissions during the quarter, the final project and the contribution to the collective knowledge of the class.

Last updated 31 March 2012