Challenge
Data Intelligence
Currently, we have large volumes of information and data to analyze, and at the same time there is data that is difficult to capture, complicating decision making. How can we improve analytics to predict the behavior of facilities and improve their performance?
Context
Currently, Transelec has a large volume of information and data, which generates an opportunity to structure and exploit them analytically. On the contrary, some data is difficult to capture, such as line conditions in the field. Due to both factors, generating reliable and time-consistent predictions, estimates for failure prevention, or asset health decisions becomes a challenge.
In addition, due to the isolated location of some transmission lines and substations, the Internet connection is not always available. Therefore, capturing and sending data is often complex to achieve results in real time.
The challenge
This challenge seeks to improve decision-making through the analysis of operational data obtained from Transelec’s transmission facilities, equipment, and systems. One of the main systems is called SCADA which has electrical variables information measured every second. The objective is to predict the behavior of the facilities, avoid asset failures, optimize the maintenance process of the transmission lines and substations, and implement constant monitoring of each one.
What are we looking for?
This challenge seeks solutions, models, techniques, platforms, tools, capabilities, etc. that can help Transelec to discover, model, and exploit current or new data (constantly captured and compatible or complementary with an offline approach) to generate predictions and estimates. The aim is to support and improve the decision-making process over time.
Guiding questions
Below you can find some questions that will allow you to broaden your vision regarding the problems and the opportunities associated with the challenge. Your solution does not need to solve all the variables to apply:
- How could we measure or estimate our real-time electrical transmission (DLR) capacity?
- How could we make an accurate estimate and predictions regarding high-voltage electrical conductors’ condition and lifetime?
- How could we detect any anomaly on the distribution line without going in person?
- How can we use historical data and real-time data to do models and predictions?
- How could we predict and anticipate the failure occurrence using data?
- How could we capture more data from our facilities? Ex: temperature, vibrations, etc.
- How could we analyze, filter, and prioritize data to deliver timely alerts to decision-makers?
We take your existing solution or co-create one, test it in our facilities and, if successful, scale it commercially.
