What are the Benefits of C/ETRM Digitization?
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What are the Benefits of C/ETRM Digitization?

By Energy CIO Insights | Wednesday, May 13, 2020

Digitization is the center of all major sectors and the C/ETRM space will reap the benefits of digitization in the near future.

FREMONT, CA: The C/ETRM space is going through digital transformation. The digitization of C/ETRM helps in improving the efficiency of business processes across different companies in the commodity/energy space. Growth-oriented trading companies are leveraging automation to get an edge over their competition. Artificial intelligence (AI), Machine learning (ML) is the emerging technologies used for the digitization process. Robotic process automation (RPA) is also used to improve the efficiency and speed of the workflows, and eliminate repetitive processes with the help of a virtual worker.  Similar to industrial robots, virtual workers can be deployed 24/7 and drive higher levels of productivity.

To digitize the C/ETRM, a neural network method is used where historical price and demand data is used to forecast weather data and calendar attributes. The historical input data in the neural network method is divided into train and test sets. The method uses the train data set to perform optimizations iteratively, and the outcome is an optimized model parameter. The test data is used for model validation, and once the models are validated, the optimized model parameters are uploaded in the model for load and/or price forecasting.   

To stimulate or to optimize operations, the algorithms are used in the trading world. Moreover, to see the impact of price and volume changes on portfolios and profit and loss, modern ETRM systems support the ability to create different possibilities. Supporting the market strategies based on set levels, averages, deltas, or targets for volume and price is possible by setting up mechanisms. A live ETRM enables the reception of real-time market information, position changes, and having direct interfaces with various trading exchanges. A linear programming simplex method is suitable for gas flow optimization and allows users to schedule gas from one point to another. Based on the constraints such as location, pipelines, contracts, delivery paths, and supply and demand side, the system can optimize the flow or manual operation is also a possibility. Flow optimization enables automation of complex equity gas nominations and the gas flow optimization to meet demand. Digitization has a lot of benefits, and it is changing the C/ETRM space.

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