PV Investigator – AI tool for Automatic Fault Detection and Diagnosis (AFDD) of photovoltaic (PV) systems

I&T Wish PV Investigator – AI tool for Automatic Fault Detection and Diagnosis (AFDD) of photovoltaic (PV) systems
(REF : W-0509)
Matched I&T Solution
Trial Project
Summary and Challenges
  • The maintenance strategy adopted currently for PV systems requires massive manpower for regular inspection and it is hard to detect system abnormality until there is a fault. As a result, the maintenance cost is high but the effectiveness is not good.
  • We wish to develop a low-cost and reliable PV maintenance strategy that could detect system abnormality at early stage to minimize the system downtime with less manpower with artificial intelligence technologies.
Expected Outcome
  1. Develop an artificial intelligence model from historical big data and third-party weather data to forecast solar energy generation through real-time temperature and irradiance data.
  2. Automatic Fault detection and diagnosis to support preventive maintenance.
  3. On-site evaluation for the performance of the artificial intelligence tool.
Expected Trial Duration 12-month
Contact Information
I&T Wish Proposer:Electrical and Mechanical Services Department (EMSD)
Contact Person:CHEUNG Yiu Yeung
Position:Engineer/Energy Efficiency B3/2
Tel: 3528 6330
Email: yycheung@emsd.gov.hk
Initiating Department Electrical and Mechanical Services Department
Upload Date 2023-10-05
Closing Date 2023-10-19
Propose I&T Solution Closed