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Automatic Configuration of sub-stations fo solar power plants based on AI-technology - AutoConfig

Reference number
Coordinator Linköpings universitet - Department of Management and Engineering
Funding from Vinnova SEK 3 000 571
Project duration October 2020 - September 2023
Status Completed
Venture Strategic innovation programme for process industrial IT and automation – PiiA
Call PiiA: Digitalization of industrial value chains, spring 2020

Purpose and goal

The project´s goal is to rationalize the bidding and design of switchgear for solar farms. Currently, these are handled as one-off projects where a low degree of reuse is applied. Despite the great value of the knowledge base that exists within the companies, a lot is found with each new tender. As there is access to a lot of data, models and knowledge, digitization and rationalization need to be done in order to move from project-based to more standardized and automated ways of handling tender procedures.

Expected results and effects

The project result shows that by using a standardized way of working with the support of configurator, the process for offering switchgear can go from a project-based approach where a number of individuals work with a quote over a number of working days and which can drag on due to the different actors waiting for information from each other, the new approach can do most of the work completely automatically in just a few minutes. Video of the framework can be seen at the following link: https://youtu.be/HSnrS_jbj0o

Planned approach and implementation

This project has been carried out in 6 work packages (AP1 Identification and mapping AP2 Standardization AP3 Configuration AP4 Optimization AP5 Machine learning AP6 Validation) where the focus has first been to analyze the current situation where after identifying a new standardized way of working to then develop and validate different computer-based techniques for how this process can be fulfilled.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 16 November 2023

Reference number 2020-02823

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