Better focus on energy targets through digital transformation
Forecasting solution helps enhance performance at industrial facilities.
One more digital transformation initiative was recently added to the long list of technologies that Aramco employs in its continuous pursuit of excellence.
The Process and Control Systems Department, in collaboration with the Hawiyah Gas Plant Department (HGPD), recently celebrated the piloting of an advanced energy demand forecasting solution that helps set improved energy targets for industrial facilities, thereby enhancing performance.
“The initiative stems from Aramco’s focus on digital transformation, and on reaping benefits of the Fourth Industrial Revolution,” said Walid A. Al Naeem, acting P&CSD manager.
It is another tool that our facilities can use to manage energy consumption, and thereby support our company’s effort toward de-carbonization.
— Walid A. Al Naeem
HGPD was the first facility to host this solution as a team from the two departments worked together for a year to internally develop, validate, and implement the model.
HGPD manager Rashed M. Al Dossary said they saw an opportunity to enhance excellence in operations and that the collaboration proved successful.
The solution employs a highly advanced model built around machine learning as it gathers data from the facility, such as steam and power consumption and generation rates.
The collected data is placed into equations that calculate current energy intensity, as well as providing predictions of it for the future.
Energy intensity, which measures the amount of energy used to achieve production, helps assess energy performance, enabling the wise use of this resource. And the solution minimizes reliance on human calculations in its predictions, providing better accuracy.
Not only that, but it is also easier to use as the solution features a visual dashboard, as well as a reporting function that enables data analysis.
Performance improved, time reduced
Endorsed by the Energy Management Steering Committee, the solution is planned to be implemented in the other facilities over the next three years.
By setting achievable and challenging energy targets maintainable through operation excellence, the solution drives improvement in energy performance and is expected to reduce corporate consumption over time, thereby resulting in cost avoidance and improved environmental performance.
And with automated result, the number of man-hours required for this exercise have been reduced by about 60% while improving energy demand accuracy up to 99%.
This is in line with the company’s other efforts toward energy efficiency that have reduced its energy intensity in recent years.
Succeeding through teamwork
Teamwork between P&CSD and HGPD was essential throughout the process as the engineers and operators progressed through the challenging task, all the while developing capabilities the fields of data analytics and machine learning.
“The challenge was to ensure all inputs are boiled down into a meaning and accurate dashboard that can be easily used,” said P&CSD’s project lead Mussa H. Alamri.
Following development, a testing phase was completed to verify the accuracy and effectiveness of the outputs.
“Energy intensity is an essential tool that we use to monitor our overall operation, and this solution helps us to track it and project it accurately and efficiently,” said HGPD process engineer Khalid S. Babtain.