By Muhammad Abbas
The winning project, the Energy Demand Forecasting Solution, entails forecasting energy demand for an oil and gas process facility.
On behalf of Aramco, Ali H. Qahtani receives the Middle East Region’s Energy Innovative Project of the Year Award from Bill Kent, AEE executive director, as Omar Naeem (left) and Muhammad Abbas (right) look on.
At an award ceremony held in Atlanta, Georgia, Aramco’s Engineering Services team received the Innovative Energy Project of the Year Award for the Middle East Region. The award was given by the Association of Energy Engineers (AEE), U.S. as part of the events leading to the 2022 AEE Energy Conference and Exposition. AEE is a prestigious nonprofit organization focusing on extensive activities worldwide in the area of energy efficiency promotion and training.
The winning project, the Energy Demand Forecasting Solution (EDFS), entails forecasting energy demand for an oil and gas process facility, which is far more challenging compared to buildings and nonindustrial facilities. It involves several variables that influence the energy consumption, and is specific to the type, configuration, location, and loading of a process facility. As part of the project, Aramco’s team developed machine learning models that uses artificial intelligence (AI) to predict energy in real-time based on plant loading and specified constraints. This project revolutionized the approach to predict energy, with high accuracy, significantly reducing man-hours for data analytics and modeling, and saving energy by optimizing plant operation.
“Winning an AEE award for our Energy Demand Forecasting Solution is testament to the hard work and in-depth focus by the Aramco energy team to identify and implement the innovative solutions to improve energy efficiency performance,” said Ali H. Qahtani, general supervisor of the Energy Systems Division.
Accurate energy demand forecasting for oil and gas process facilities is required to set the optimal targets for energy key performance indicators, so that operating departments can achieve energy efficient operations. Until recently, Aramco’s energy team has been using historical data of plants and MS Excel-based offline linear regression models to forecast energy demand. These models are static, and require manual involvement for data collection, preprocessing, and model updates.
The team undertook a project to develop AI-based models, using machine learning software, which can be updated with changing of the operating variables, thereby providing highly accurate predicted energy demand. The solution was developed for two Aramco departments in 2020-2021 — one gas processing department, and one crude producing department, comprising of 15 gas-oil separation plants. Subsequently, the solution is being implemented at additional departments.
The solution uses AI as it gathers data from the facility, such as steam and power consumption, to continuously updates the predictive equations and coefficients. Using highly advanced models built based on machine learning, the collected data is placed into equations that calculate current as well as predict future EI. EI measures the amount of energy used to produce unit production, and helps to assess energy performance of the facility. The solution was endorsed by Aramco’s Energy Management Steering Committee, and is being implemented in the other facilities during the next three years. Such innovative solutions lead to significant reductions in corporate energy consumption, resulting in cost avoidance and improved environmental performance.
“The project joins hands with Aramco’s other efforts to continuously improve the energy efficiency performance, which has enabled the company to successfully reduce its EI profile over the last few years,” said Waliyoddin M. Asaad, manager of the Energy Transition Engineering Department.
This project is another example toward utilizing the digital and innovative technologies for converting conceptualized engineering techniques and methodologies into effective solutions. Winning an award from an internationally recognized organization will go a long way in boosting the success of the project team.
— The Arabian Sun: September 28, 2022