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Hourly Methods Discussions Continue

4/30/2018

Week Twelve CalTRACK Update

During week twelve, we continued our discussion of hourly methods. In the upcoming week, we will analyze test results for hourly methods on GitHub. We will also be talking about how to log ideas for future improvements. The standing meeting to discuss hourly methods will be on Thursday, May 3rd at 12:00 (PST).

Homework:

Use Hourly Method Tools on test data
Report findings on Github
Offer test criteria for hourly models
Attend standing meeting on Thursday, May 3rd at 12:00 (PST)

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Hourly Methods Approach & Testing Considerations

4/23/2018

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Week Eleven CalTRACK Update

Week eleven was the first week of hourly methods discussion. Developing hourly methods will require discussion and empirical testing of topics unique to hourly methods before we can make final specifications.
Topics that must be addressed include:

Data sufficiency requirements
Modeling approach
Model selection criteria
The effect of aggregating hourly models on portfolio uncertainty

Time Of Week Temperature Models (TOWT):
A proposed model for hourly methods is the TOWT model from Lawrence Berkeley National Labs (LBNL) is shown below.

Notes:

The number of temperature ranges and the balance points will need to be defined. The LBNL model had 5 ranges ( < 55F, 55-65 F, 65-75 F, 75-90 F, 90 F <).
The methods for defining if a building is occupied or not is explained in detail in Phil Price’s Everything I Know About Building Energy Modeling, But Never Told Anyone Before (18:30-30:00).

Homework:

Use Hourly Method Tools on test data
Report findings on Github
Offer test criteria for hourly models

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Building Qualifications Results & Recommendations

4/17/2018

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Week Ten CalTRACK Update

The CalTRACK working group finalized discussions on Building Qualifications during the first half of Thursday’s (4/12) meeting and dove into the hourly methods during the second half. Bill Koran from SBW consulting provided a helpful overview of hourly models and the ECAM energy data analysis tool. The major findings of this meeting are summarized below:

Video of 4/12/2018 Meeting

Building Qualification Observations and Recommendations:
Main observations that were driving the recommendations:

Stricter building-level thresholds do not necessarily result in more confidence in portfolio savings.
Thresholds would vary by data granularity. Distributions of building-level metrics also vary widely by building type, location and climate zone.
Bias must be minimized for portfolio aggregation to work.

The building qualification recommendations are dependent on use case:

For use cases where confidence in portfolio-level performance is required (e.g. aggregator-driven pay-for-performance, non-wires alternatives (NWA) procurements), we recommend using a permissive building-level CVRMSE threshold (100% is recommended as a default), but requiring that a portfolio-level metric be respected (e.g. portfolio fractional savings uncertainty).

The portfolio-level threshold will be a policy decision and may differ depending on the use case (e.g. NWA procurement may require less than 15% uncertainty, regular pay-for-performance program may require 25% etc.)

For use cases where confidence in individual building results is required (e.g. customer-facing performance based incentives), ASHRAE Guideline 14 thresholds may be used.

Notes:

The FSU thresholds will be context-specific because the value of certainty is not uniform across projects and procurers. For example, a utility may be willing-to-accept a portfolio with 25% uncertainty in the context of a pay-for-performance program. The same utility may require 15% uncertainty for a non-wires alternative project.

CVRMSE and FSU are different metrics andare described in this paper: (A Comparison of Approaches to Estimating the Time-Aggregated Uncertainty of Savings Estimated from Meter Data)

Goals for Hourly Methods:
Hourly models are necessary for estimating the load impact of energy efficiency. This makes hourly energy savings important information for aggregators and utilities in an energy efficiency marketplace.
Our goal is to establish suitable methods for calculating whole building hourly energy savings for residential and commercial buildings. Additionally, the methods will include guidelines for aggregating site-level savings.

Discussion Topics:
We have allotted three weeks to test and discuss hourly methods. Below are some important topics that will need to be addressed:

Data Requirements and Sufficiency:
- Hourly weather data can be unreliable. We will need to establish guidelines for hourly weather data sufficiency and methods for accommodating missing weather values.
- Data sufficiency requirements for hourly meter data are needed.
- Hourly data cleaning methods must be defined.
Methods:
- It may be beneficial to adjust our model selection criteria for hourly methods.
- Aggregating many hourly models will result in high portfolio uncertainty. As a result, it may be necessary to reassess the calculation of portfolio uncertainty in hourly savings.
Models:
- We will need to determine the most suitable hourly model for CalTRACK. Two open source models to begin the discussion are:
  1. The TOWT model (time-of-week and temperature) from Lawrence Berkeley National Lab
  2. ECAM model from SBW consulting

We look forward to future discussions on GitHub regarding these topics.

Homework:

Use Hourly Method Tools on test data
Report findings on Github
Offer test criteria for hourly models
Watch Phil Price Video about energy modeling and hourly methods: Everything I Know About Building Energy Modeling, But Never Told Anyone Before

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Building Qualification Criteria Discussions

4/9/2018

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Week Nine CalTRACK Update

During week nine of CalTRACK, there were continued discussions on building qualification criteria and some introductory comments on hourly methods. The working group meeting will be held on Thursday, April 12th at 12:00 (PST). We will discuss:

Final comments on building qualification
Proposals for hourly methods testing

Hourly Methods Overview:
Hourly methods are a new addition in CalTRACK 2.0 and were not in the first version of CalTRACK. This task involves testing various hourly modeling methods and recommending a standardized approach to hourly modeling, which can reveal the time value of energy efficiency.
Importance of Hourly Methods:

Hourly methods are a more granular time interval than daily or billing period methods. These granular time intervals are valuable for determining the temporal value of energy savings, by associating savings with grid demand and energy price.

Time Of Week and Temperature Models:
To start the discussion of hourly methods, it is helpful to consider to existing open source tools. Lawrence Berkeley National Lab has developed an open source time of the week and temperature (TOWT) model to calculate hourly energy savings and is part of the RMV2.0 - LBNL M&V2.0 Tool. A TOWT model predicts hourly energy savings by utilizing hourly temperature data instead of daily or billing period HDD and CDD. Another is ECAM (ENERGY CHARTING & METRICS) developed by Bill Koran at SBW consulting.

We look forward to discussion on the working group call about these approaches, and more to frame the approach to empirical tests for the CalTRACK 2.0 hourly methods.

Final Note:
It is important to remember that CalTRACK methods development is an iterative process. The finalized methods for CalTRACK 2.0, just like v. 1.0, will benefit from field deployment and may need to be revised in future years. We expect this process to result in improved and refined methods with successive iterations.

Homework:

Review final results for building qualifications and provide final edits
Review existing tools, practice and concepts for hourly methods
Discuss and provide suggestions for hourly methods on GitHub
Attend the bi-weekly meeting on Thursday April 12th at 12:00 (PST)

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Hourly Methods Discussions Continue

Hourly Methods Approach & Testing Considerations

Building Qualifications Results & Recommendations

Building Qualification Criteria Discussions

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