| I&T Solution |
AI Switchroom - Intelligent Electrification
(REF: S-1351) |
| Trial Project |
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| Solution Feature |
- To build the database and AI detection algorithm based on the historical data, available knowledge database, and professional research
- To train and refine the built machine learning model by possible python libraries and real time data
- To implement the AI model and initiate the operation alert when abnormalities found
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| Trial Application and Expected Outcome |
- The research area includes: 1. Busbar High Impedance Detection 2. Potential Damage to Load Equipment 3. Energy Loss Estimation
- Busbar High Impedance Detection, By Support Vector Machine, separating supervised data based on different dimensions regression. The monitoring details will be at the ACB and MCCB levels where the PQ data and busbar temperature data available.
- Potential Damage to Load Equipment, By Classification Machine, and according to the NEMA three phase unbalance and EN50160 standard with THD limit value, to define the abnormalities which impact to the load equipment and the accumulated potential damage to its lifetime if possible. The monitoring details will be MCCB levels
- Energy Loss Estimation, By Artificial Neural Network, to compare the relationship the PQ data of incoming and outgoing circuits, to estimate and report the energy lost against the switchboard and loading circuits. The level of monitoring details will be at the switchboard and MCCB levels where the PQ data available.
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| Additional Solution Information |
230215 - Siemens - Proposal on AI Switchroom - Intelligent Electrification.pdf
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| Info on I&T Solution Provider |
| Solution Provider | : | Siemens Ltd. | | Address | : | 10/F, Tower B, Manulife Financial Centre, 223-231 Wai Yip Street, Kwun Tong, Kowloon, Hong Kong | | Contact Person | : | Wong Tsz Ming |
| Position | : | Head of Digital Business and Electrical Products | | Tel | : | 61362835 | | Email | : |
keithtm.wong@siemens.com |
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