Diploma in Network Operation Forecasting/Optimization
Online postgraduate diploma of 800 hours in grid operation forecasting and optimisation: 8 modules covering power system operation under Regulation (EU) 2017/1485, demand forecasting, renewable generation forecasting, load flow and state estimation, operational optimisation, distribution network operation and AI in grid operation, with an assigned technical tutor.
Diploma in Network Operation Forecasting/Optimization — studying from South Africa
South Africa has a growing digital economy, with strong demand for data scientists, analysts and simulation specialists in finance, mining, telecoms and government. Major banks, mining houses and telecommunications operators such as MTN and Vodacom rely on advanced analytics for planning and operations. Universities including the University of Cape Town and Wits contribute research in machine learning and computational modelling. Protection of personal data is governed by national legislation, which shapes how analytics work is carried out.
Fees for South Africa: R 33 400 (South African rand), with instalments and employer sponsorship available.
Relevant bodies in South Africa
Typical roles
Questions from South Africa
Is a SEIUM qualification recognised by any South African professional body for data and AI?
South Africa has no single statutory register for data scientists or AI practitioners, and bodies such as the Computer Society of South Africa and the South African Qualifications Authority set their own standards. SEIUM is a private online institute whose qualifications are not state degrees and are not accredited by a national body. Recognition is decided by employers or the relevant body, so ask them directly before enrolling.
Do South African employers in data and AI value private online qualifications?
Demand for data and analytics skills in South Africa spans banking, insurance, telecoms, retail and government, and employers often assess skills through portfolios, technical interviews and experience. A private online qualification may support your CV, but it does not guarantee a job or salary outcome. Show prospective employers the syllabus and your project work to gauge their interest.
How does the workload fit with a job, and what English level do I need?
The programme is fully online and taught in English, so you need confident reading and writing skills. As it is remote, no student visa is needed to study from home. Master's programmes total 1,900 hours, postgraduate diplomas 800 hours and specialist courses 300 hours, with an assigned technical tutor and a final project. Fees can be paid in instalments, and employer sponsorship may be possible.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Describe power system operating processes and their regulation.
Develop deterministic and probabilistic demand forecasting models.
Forecast renewable generation using meteorological data.
Compute load flows and estimate the state of the network.
Formulate and solve operational optimisation problems.
Manage distribution networks with flexible resources.
Evaluate AI applications in grid operation.
Who it's for
- System operation engineers working in control rooms and operational planning.
- Energy forecasting analysts producing demand and renewable forecasts.
- Power network engineers responsible for load flow and security studies.
- Energy data scientists applying machine learning to grid data.
- Electricity market analysts working on dispatch, balancing and prices.
- Optimisation engineers modelling unit commitment and optimal power flow.
- Engineering or science graduates looking to move into power system operation.
What you'll work with
- Regulation (EU) 2017/1485 (SO GL) (guideline on electricity transmission system operation)
- Regulation (EU) 2017/2195 (balancing) (guideline on electricity balancing)
- Regulation (EU) 2016/631 (RfG) (network code on requirements for grid connection of generators)
- Red Eléctrica Operating Procedures (operating procedures of the Spanish system operator)
- IEC 61970 (CIM) (Common Information Model for energy management systems)
- ENTSO-E CGMES (Common Grid Model Exchange Standard)
- IEC 62325 (framework for energy market communications)
- pandapower
- PyPSA
- Pyomo
- Grid2Op
- PowerFactory
8 modules
1.1Structure of the system and the market1.2Functions of the system operator1.3Balance between generation and demand1.4Ancillary and balancing services1.5Regulation (EU) 2017/1485 on system operation1.6Red Eléctrica operating procedures1.7The N-1 security criterion1.8Integration of renewables1.9Planning horizons1.10Workshop: sequence of operating processes over one day
2.1Drivers of electricity demand2.2Regression models with temperature2.3ARIMA and exponential smoothing models2.4Gradient boosting for forecasting2.5LSTM and temporal convolutional networks2.6Hierarchical forecasting by node2.7Probabilistic forecasting by quantiles2.8Effects of holidays and events2.9MAPE and pinball loss metrics2.10Lab: hourly demand forecast with LightGBM
3.1Numerical weather prediction3.2Wind forecasting with power curves3.3Solar forecasting with satellite imagery3.4Nowcasting with sky cameras3.5Model combination and ensembles3.6Ramp forecasting3.7Probabilistic forecasting and scenarios3.8Regional aggregation of forecasts3.9Forecast evaluation3.10Lab: photovoltaic forecast with meteorological data
4.1Load flow formulation4.2Newton-Raphson and decoupled methods4.3DC load flow4.4Weighted least-squares state estimation4.5Bad data detection4.6Network observability4.7ENTSO-E CGMES models4.8Phasor measurement units4.9Contingency analysis4.10Practical: state estimation with pandapower
5.1Economic dispatch of generation5.2Unit commitment with integer programming5.3AC and DC optimal power flow5.4Management of technical constraints5.5Optimisation with storage5.6Reserves and balancing services5.7Stochastic and robust optimisation5.8Solvers and modelling with Pyomo5.9Locational marginal prices5.10Lab: unit commitment with Pyomo
6.1Network reconfiguration6.2Voltage control with DER6.3Local congestion management6.4Local flexibility markets6.5Forecasting at transformer level6.6Optimisation with electric vehicles6.7Microgrid operation6.8Coordination with ADMS6.9RfG connection requirements6.10Case study: congestion management with local flexibility
7.1Reinforcement learning for grid control7.2Grid2Op and the L2RPN competitions7.3Surrogate models for load flow7.4Graph neural networks for power systems7.5Explainability for operators7.6Model safety and robustness7.7Decision support systems7.8Automation risks7.9Model governance at system operators7.10Case study: decision assistant for the operator
8.1Definition of the system and horizon8.2Demand and generation data8.3Forecasting models8.4Load flow and state estimation8.5Operational optimisation model8.6Evaluation with scenarios8.7Cost and security analysis8.8Recommendations for the system operator8.9Report and presentation8.10Final project: final review with the tutor
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so you can combine it with your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is pandapower, PyPSA, Pyomo, Grid2Op and PowerFactory, in free, academic or evaluation versions. Practical work is based on real procedures for demand and renewable generation forecasting, state estimation in transmission networks, and dispatch and unit commitment optimisation. Assessment is continuous by module, plus the final project.
Standards covered: Regulation (EU) 2017/1485 (SO GL), Regulation (EU) 2017/2195 (balancing), Regulation (EU) 2016/631 (RfG), Red Eléctrica Operating Procedures, IEC 61970 (CIM), ENTSO-E CGMES, IEC 62325.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- An internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
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 totals 800 hours over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with pandapower, PyPSA, Pyomo, Grid2Op and PowerFactory, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
Prior technical training or professional experience in the sector (no university degree required), a computer able to run the programme software and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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