Seasonal Consumption Controls

Foreword

This document has been prepared by the OpenEAC Alliance, a collaborative group of energy engineering and measurement and verification professionals focused on creating transparent and standardized methods to measure the environmental impacts of demand side interventions. These methodologies are designed to align with best practices and reflect input from industry experts. The OpenEAC Alliance aims to enhance accountability and consistency in documenting energy and carbon savings from distributed energy resources (DERs).

About the OpenEAC Alliance

The OpenEAC Alliance is an organization of professionals dedicated to standardizing the measurement and verification of DERs. By focusing on clarity and rigor, the Alliance aims to overcome challenges that have hindered the proper valuation of DERs for their climate benefits. Central to this effort is the Energy Attribute Certificate (EAC), a standard that provides a detailed, auditable record of energy project impacts, including attributes such as type, timing, and location of energy production or reduction.

The OpenEAC Alliance collaborates to develop open-source methodologies, ensuring that DER projects can be accurately measured, verified, and valued in a way that promotes trust and drives market adoption.

Introduction

This document introduces a standardized approach for quantifying energy and carbon savings achieved through the introduction of controls to devices that are seasonally used, and otherwise assumed to be always on during those seasons, for the purposes of generating Energy Attribute Certificates (EACs).

Scope

This document outlines the methodology, assumptions, and data sources used to quantify energy and carbon savings. The primary purpose is to specify how quantified changes in energy use and emissions avoidance can be translated into Energy Attribute Certificates (EACs).

Terms and Definitions

• Device: The lowest level of physical granularity that can be measured with sensors

• Site: A specific geographic location (i.e. a single roof) where a group of devices are collectively installed

• Noise threshold: A power value at which any observations lower than that value are assigned 0 W.

• Seasons

  • Off-season: The calendar months where the device would not be expected to be in use during normal operations.

  • Shoulder-season: The calendar months where the device may be in partial use during normal operations.

  • On-season: The calendar months where the device would be expected to be in 100% during normal operations.

• 90th percentile non-zero power value: Given a set of non-zero power values, the value below which 90% of the data fall. This is used to compute the counterfactual in order to avoid overly attributed savings that would be caused by power spikes in the readings.

Data Requirement Definitions

• Hourly observed values, taken from an individual device, are required to perform this calculation. Each device must also define a unique geographical site where it is located.

• No savings are attributed during the summer season.

• The sensor is only measuring the electricity used by the device and no other loads.

Methodology

1 Impact Calculation

1.1 Calculate observed electricity consumption for the device for every hour in the shoulder-season and on-season for all completed calendar months.

1.1.1 Collect N readings per hour and record the maximum power reading for that hour. If there are no readings in that hour or the maximum reading is below the noise threshold, set that observed value to 0.

1.1.2 The maximum power reading for each hour represents the observed hourly energy consumption.

1.2 Calculate counterfactual electricity consumption for every hour in which an observed electricity consumption value has been computed.

1.2.1 For each day, compute the 90th percentile non-zero power value based on the below considerations:

1.2.1.1 If it is the shoulder-season or on season and there is at least one non-zero hourly observed power value for a given day, calculate the actual 90th percentile non-zero value from the hourly observed power values.

1.2.1.1.2 Otherwise, if it is the on-season**,** use the Default 90th Percentile by Calendar Month in section 2. This could be either because all values are 0 throughout the day (the device was off) or that there are no observed readings during the day (the device and the breaker containing the sensor were off)

1.2.1.1.3 Otherwise, set the 90th percentile value to 0.

1.2.1.2 Assign each hour of each day a counterfactual power value based on the above 90th percentile calculation. This hourly average power value represents the counterfactual hourly energy consumption.

2 Default 90th Percentile by Calendar Month

2.1 For a given calendar month, calculate that month’s default 90th percentile of all non-zero hourly observed power values for all devices at the site. If this value is 0 or null, calculate that month’s default 90th percentile of all non-zero hourly observed power values for that device across that calendar month and the 4 preceding calendar months. If this value is 0 or null, then set that month’s default 90th percentile value to 0.