AI Case Study

Saxnas Hydroplant increased profits by 35% after using machine vision to digitise a legacy pumping plant

Using digital cameras with machine vision technology meant that the Saxnas hydroplant was able to digitise the output from its analogue meters. This enabled a digital model that automated the unmanned plant's configuration to optimise productivity and to respond to data on electricity prices. This drove a claimed 16% improvement in production and profitability of 35%.

Industry

Energy

Renewable Energy

Project Overview

According to Inovia:
"The solution was to start using sensors for all interesting parts to monitor its performance. It concerned measuring and collecting data from the speed of the turbine, heat on the turbine bearings, monitoring analogue gauges with AI based image recognitions, measuring rainfall, measuring water depth in the upstream lake, etc. All the sensors where provided by Inovia and the data was collected and sent to Insight [a data management and analysis platform] for analyzing to understand the performance of the hydro plant. To increase the analytical part even further, external data was added such as weather forecasting to understand if / when rain is going to fall, which means filling up the pond with water. Furthermore, data from the power spot market was added, to understand when the price for electricity is the highest to know when to produce/sell at the right time. The IoT solution not only increased the monitoring capability but also predicting future behaviour and being able understand when and how to get the most of the investment."

Reported Results

Inovia claims record productivity and financial outcomes: production up 16% and profitability by 35% without needing to add staff. The capital cost was a fraction of that which would have been required for a traditional digital upgrade.

Technology

Function

Operations

General Operations

Background

Saxnäs is a family operated Hydro plant in northern Sweden. Because it is unmanned machine outage could cause significant lost production and optimising it - in an era of increasingly sophisticated electricity purchasing - was a challenge.

Benefits

Data