Postgraduate Diploma in Event Analysis with PMU/Smart Metering
Online 800-hour Postgraduate Diploma in Event Analysis with PMU/Smart Metering. 8 modules covering IEEE C37.118.1 (synchrophasor measurements), IEC/IEEE 60255-118-1 (PMU requirements) and openPDC. Dedicated tutor and enrolment open.
Take the controls.
Run a real engineering trade-off from this programme. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Explain the principles of synchrophasor measurement.
Use smart meters as sensors on the distribution network.
Apply automatic event detection algorithms.
Identify and characterise electromechanical oscillations.
Locate faults and reconstruct incidents using synchronised data.
Apply advanced analytics to large volumes of measurement data.
Propose operational applications based on these analyses.
Who it's for
- Grid event analysis engineer wishing to specialise in Event Analysis with PMU/Smart Metering.
- WAMS systems specialist wishing to specialise in Event Analysis with PMU/Smart Metering.
- Smart metering data analyst wishing to specialise in Event Analysis with PMU/Smart Metering.
- Protection engineer wishing to specialise in Event Analysis with PMU/Smart Metering.
- Network operation engineer wishing to specialise in Event Analysis with PMU/Smart Metering.
- Power sector data scientist wishing to specialise in Event Analysis with PMU/Smart Metering.
- Graduates in engineering or science seeking to join system operators.
What you'll work with
- IEEE C37.118.1 (synchrophasor measurements)
- IEC/IEEE 60255-118-1 (PMU requirements)
- IEEE C37.118.2 (synchrophasor data transfer)
- IEEE C37.244 (phasor data concentrators)
- IEC 61000-4-30 (power quality measurement methods)
- EN 50160 (voltage characteristics)
8 modules · 800 h
1.1The concept of the synchrophasor and time reference1.2GPS synchronisation and IEEE 1588 PTP1.3IEEE/IEC 60255-118-1 standard1.4PMU classes: P and M1.5Total vector error (TVE)1.6Frequency estimation and ROCOF1.7IEEE C37.118.2 protocol1.8Phasor data concentrators (PDC)1.9WAMS architectures1.10Laboratory: analysis of C37.118 frames from a PMU
2.1Smart meter functionalities2.2Load profiles and event logs2.3Quality logs: voltage dips, overvoltages and outages2.4Last gasp alarms2.5Time resolution and clock synchronisation2.6DLMS/COSEM protocols2.7PRIME and G3-PLC concentrators2.8Data access and privacy2.9Limitations compared with power quality analysers2.10Practice: extracting events from a concentrator
3.1Classification of events in the power system3.2Detection of abrupt changes in data series3.3Adaptive threshold methods3.4Spectral analysis and wavelets3.5Oscillation detection3.6Identification of generation trips3.7Islanding and separation detection3.8Filtering erroneous PMU data3.9Event labelling for training3.10Workshop: event detector on real PMU data
4.1Inter-area and local modes4.2Prony analysis and matrix pencil4.3Real-time modal estimation4.4Damping and alarm thresholds4.5Forced oscillations and source location4.6Dissipated energy flow method4.7Subsynchronous oscillations with converters4.8Cases recorded by ENTSO-E4.9Integration with stabiliser control4.10Laboratory: modal estimation with matrix pencil
5.1Fault location with phasors5.2Reconstruction of event sequences5.3Correlation with oscillography records5.4Analysis of cascading trips5.5Fault location in distribution using meters5.6Phase and broken conductor detection5.7Calculation of energy not supplied5.8SAIDI and SAIFI indices from meters5.9Preparation of incident reports5.10Case study: reconstruction of a regional disturbance
6.1Supervised learning for event classification6.2Convolutional neural networks on waveforms6.3Unsupervised clustering of disturbances6.4Fusion of PMU, SCADA and meter data6.5Big data and streaming platforms6.6Linear state estimation with PMUs6.7Low-voltage topology from meter data6.8Measurement anomaly detection6.9Model explainability6.10Practice: machine learning event classifier
7.1Stability monitoring in control centres7.2Wide-area protection schemes7.3Validation of dynamic models with PMUs7.4Power quality monitoring in distribution7.5Predictive network maintenance7.6Cybersecurity of PMUs and meters7.7Optimal PMU deployment7.8Equipment specification and procurement7.9Return on investment in WAMS7.10Case study: PMU deployment plan for a distribution utility
8.1System selection and data sources8.2Data preparation and cleansing8.3Automatic event detection8.4Classification and characterisation8.5Oscillation or fault analysis8.6Validation of results8.7Proposal of operational applications8.8Deployment plan and costs8.9Dissertation and presentation8.10Final review with the tutor
How you'll learn
Training is 100% online on the SEIUM campus, with downloadable materials, recorded classes and a dedicated technical tutor. There are no fixed timetables: students progress at their own pace within the enrolment period, which makes it easy to combine with work.
Each module combines theory, guided reading of the original standard and applied exercises. The software used is openPDC, MATLAB, Python (NumPy, SciPy), DIgSILENT PowerFactory, in free, academic or evaluation versions. Practicals cover real analysis procedures on real PMU records, forensic event reconstruction and oscillation detection in field data. Assessment is continuous, module by module, plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Explain the principles of synchrophasor measurement.
Use smart meters as sensors on the distribution network.
Apply automatic event detection algorithms.
Identify and characterise electromechanical oscillations.
Locate faults and reconstruct incidents using synchronised data.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. A university degree is not required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient Spanish to follow technical standards documentation.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme comprises 800 hours in total, spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.
You will work with openPDC, MATLAB, Python (NumPy, SciPy) and DIgSILENT PowerFactory. Free, academic or evaluation versions are used, and the tutor will indicate the free alternative where one exists.
A SEIUM own diploma upon passing the continuous assessment and the integrating project. This is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a Course or Postgraduate Diploma in the same area are credited towards the advanced programme. Please check the recognition policy when you enrol.
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