Opower, Inc.

Garner Chung

Erik Shilts

Suelyn Yu

David Royer

Benjamin Packer

Richard Tyler Curtis

Agustin Fonts

Ben Packer

Aspects of the subject technology relate to a system that analyzes customers' AMI load curves, identifies evening peak users as defined by their load curves, and provides Energy Efficiency (EE) advice related to their periods of high use. For example, identified high evening users can be sent an email with normative comparisons on evening load use, along with tips to reduce energy usage. Other aspects relate to the additional targets/communications. Aspects of the subject technology relate to categorizing a user's energy consumption tendencies based on a user's load curve and providing customized content based on the user's category. By taking into consideration the user's actual energy consumption patterns, the system may be able to provide more relevant content to the user.

Users campaign for peaking energy usage

The subject disclosure relates to systems and methods for calculating a thermal sensitivity score. In some aspects, the method includes steps for receiving temperature information for a first geographic location, receiving resource consumption data for each of a plurality of similar consumption locations in the first geographic location, and generating, by the processors, a thermal sensitivity model based on the temperature information and the resource consumption data for each of the plurality of similar consumption locations. In some aspects, the steps can further include computing a thermal sensitivity score for each of the similar consumption locations using the thermal sensitivity model. Systems and machine readable media are also provided.

System for providing remote building efficiency audits

Aspects of the subject technology relate to a system that analyzes customers' AMI load curves, identifies evening peak users as defined by their load curves, and provides Energy Efficiency (EE) advice related to their periods of high use. For example, identified high evening users can be sent an email with normative comparisons on evening load use, along with tips to reduce energy usage. Other aspects relate to additional targets/communications. Aspects of the subject technology relate to categorizing a user's energy consumption tendencies based on a user's load curve and providing customized content based on the user's category. By taking into consideration the user's actual energy consumption patterns, the system may be able to provide more relevant content to the user.

Notification techniques for reducing energy usage include detecting a weather event for a location of at least one consumer, determining, based on the weather event, at least one modified behavior to reduce energy usage for the at least one consumer, and providing a notification to the at least one consumer regarding the at least one modified behavior for the weather event.

Notification techniques for reducing energy usage

The subject disclosure relate to a method for calculating a wind sensitivity score. In some aspects, a method of implementing the technology can include steps for receiving wind speed information for a first geographic location over a first time period, receiving resource consumption data for each of a plurality of similar consumption locations in the first geographic location over the first time period; and generating a wind sensitivity model based on the wind speed information and the resource consumption data for each of the plurality of similar consumption locations. In some aspects, the method may further include steps for computing a wind sensitivity score for each of the similar consumption locations using the wind sensitivity model.

System for providing remote building efficiency audits for wind sensitivity

An occupancy schedule determining method and system that receives usage data indicating a quantity of a resource supplied by a utility that is used at the location over a plurality of days, each of the plurality of days being subdivided into a plurality of predetermined time periods, and the usage data indicating the quantity of the resource supplied by the utility that is used during each of the predetermined time periods, aggregates the usage data for each of the plurality of predetermined time periods over the plurality of days, and uses the aggregated usage data to determine the occupancy schedule at the location using a processor.

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Oakland, CA, United States of America

Garner Chung