WSQ Data Management of Solar Photovoltaic (PV) Systems (Classroom and Asynchronous)

Training Provider: Sustainable Energy Association of Singapore (SEAS)
Course Reference: TGS-2022015562
S$300
Original: S$600
Save S$300

About This Course

After the course, learners will be able to:
- Apply an Internet of Things (IoT)-based approach for the remote monitoring of solar PV systems
- Manage automated tools and systems for solar PV systems
- Interpret data generated for the optimisation of solar PV systems

What You'll Learn

It is not easy to study the performance of solar PV systems because it varies constantly with differing conditions of parameters and system components. Timely detection of faults and issues are critical so that prompt remedial actions can be taken to reduce damage and cost. Real time monitoring will be needed to keep up with the required observation of the performance of the solar PV system around the clock. Having an Internet of Things (IoT)-based energy management approach will allow for real time monitoring and optimisation of energy consumption to enhance the performance of the solar PV systems.

Learners attending the course will be equipped with knowledge and skills to carry out remote monitoring of solar PV systems using an Internet of Things (IoT)-based approach.

Entry Requirements

Learners are assumed to be:
● Knowledgeable of electrical engineering competencies
● Able to listen and speak English at a proficiency level equivalent to the Employability Skills System (ESS) level 4
● Able to read and write English at a proficiency level equivalent to ESS level 4
● Able to process numbers at a proficiency level equivalent to ESS level 4
● Possess at least 1 year working experience in engineering-related jobs
● Possess broad knowledge of solar PV systems operation and maintenance
● Minimum Qualifications: ITE NITEC or equivalent
● Minimum Age: 21 years old

SEAS shall assess the suitability of learners by requesting for their CVs.

Learners keen to join without the necessary pre-requisite knowledge and experience stated above may be assessed if they have other relevant experience to access the course, on a case-by-case basis.

Course Details

Duration 21 hours
Language English
Training Commitment Part Time
Total Enrolled 36 students
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