Cloud-Based Energy Flexibility Modeling Software for Wastewater Treatment Plants

We collaborated with WE3Lab from Stanford University to develop a product MVP.

About the project

Water & Energy Efficiency for the Environment Lab (WE3Lab) from Stanford University partnered with Lexunit to develop a cloud-based software that uses SCADA data from wastewater treatment plants and user metadata to model energy consumption and identify energy flexibility optimization opportunities.

Location:

United States

Industry:

Climate Tech

Services:

Digital product development

Business type:

University

Challenges

One of the key challenges was to gather the necessary domain knowledge to understand how wastewater treatment plants (WWTP), their modeling, and their energy consumption are working.  The development consisted of four main steps:

  • Data Acquisition and Processing
  • Energy Consumption Modeling API
  • Cloud-based Infrastructure
  • User Interface

Solution

An automated system for data acquisition and processing from multiple sources, including schematic drawing of the WWTP, energy consumption information, and equipment data. Data validation is implemented to prevent faulty input. The data cleaning pipeline provided by the Client was deployed to a Prefect server to handle processes in the background.

Developing a flexible modeling API using optimization software developed by the Client to predict energy consumption and generate WWTP financial models based on historical data.

Designing and implementing a scalable, secure, and accessible infrastructure using Amazon Web Services.

Building a network that contains a WWTP facility, processing the SCADA data, creating alternative scenarios, and setting up simulations require a lot of tweaking and iterations from the user, and therefore main components of the software were developed in a way to support high interactivity.

Results

We have successfully developed the MVP during this project which enabled the founders to gather customer feedback. With sufficient input the data the tool can calculate the operational sweet spot for wastewater treatment plants in a few hours. Further iterations are expected to follow.

Other success stories

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