EMS Course in Hybrid Renewable Plants
Online 300-hour course in EMS for hybrid renewable plants. 6 modules covering Regulation (EU) No 1227/2011 (wholesale energy market integrity and transparency, REMIT), Regulation (EU) 2017/2195 (electricity balancing) and Python (Pyomo). Assigned tutor and open enrolment.
EMS Course in Hybrid Renewable Plants — studying from New Zealand
New Zealand's energy sector is distinctive for its high share of renewable generation, drawn from hydroelectric, geothermal and wind resources. Transpower operates the national grid, while distribution networks are run by regional lines companies, and the Electricity Authority regulates the wholesale and retail markets. Energy engineers are employed across generation, transmission, distribution and retail, with demand growing as the country works towards its renewable electricity goals.
Fees for New Zealand: NZ$1,580 (New Zealand dollar), with instalments and employer sponsorship available.
Relevant bodies in New Zealand
Typical roles
Questions from New Zealand
What professional recognition applies to energy and network engineers in New Zealand?
Engineering New Zealand administers Chartered Professional Engineer registration, which is widely used in the energy sector. The Electricity Authority oversees the electricity market, and the Electricity Engineers' Association is an industry body. SEIUM's qualifications are private and not accredited by any national body, so recognition is decided by employers or the relevant body.
Who employs energy and network engineers in New Zealand?
Major employers include electricity lines companies, generators, transmission operators, gas network businesses and consultancies. Roles often value registration, field experience and knowledge of New Zealand's grid and regulation. A private qualification may support your CV, but it does not guarantee employment or a particular career outcome.
Can I study from New Zealand with a full-time job, and does an employer need to fund it?
Yes. The programmes are 100% online and taught in English, so you can study from New Zealand without a student visa. You will have an assigned technical tutor and complete a final project. Specialist courses take 300 hours, diplomas 800 and master's programmes 1,900. Fees can be paid in instalments, and employer sponsorship is 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
Identify the economic objectives of an EMS in electricity markets.
Develop price and generation forecasts for scheduling.
Formulate MILP and stochastic optimisation problems for plants with storage.
Build bidding strategies for day-ahead, intraday and balancing markets.
Evaluate strategies through backtesting and ex post analysis.
Deploy the EMS with governance and cybersecurity criteria.
Design a revenue optimiser for a renewable plant with storage.
Who it's for
- Energy optimisation engineer who wants to specialise in EMS for hybrid renewable plants.
- Renewable energy trader who wants to specialise in EMS for hybrid renewable plants.
- Data scientist in electricity markets who wants to specialise in EMS for hybrid renewable plants.
- EMS developer who wants to specialise in EMS for hybrid renewable plants.
- Market operations analyst who wants to specialise in EMS for hybrid renewable plants.
- Renewable portfolio manager who wants to specialise in EMS for hybrid renewable plants.
- Engineering or science graduates looking to enter the renewables sector.
What you'll work with
- Regulation (EU) No 1227/2011 (Wholesale Energy Market Integrity and Transparency, REMIT)
- Regulation (EU) 2017/2195 (Electricity Balancing)
- Regulation (EU) 2019/943 (Internal Market for Electricity)
- OMIE Day-Ahead and Intraday Market Operating Rules
- Operating Procedures 3.1 and 7.2 of Red Eléctrica
- Law 24/2013 on the Electricity Sector
- IEC 62443 (Industrial CyberSecurity)
6 modules · 300 h
1.1Functions of the EMS in the business1.2Day-ahead and intraday markets1.3Balancing markets1.4Imbalances and their cost1.5Technical constraints of the operator1.6Price signals1.7Multi-criteria operating objectives1.8Relationship with the market representative1.9Data architecture1.10Case study: revenues of a plant in the Iberian market (MIBEL)
2.1Price forecasting2.2Solar and wind forecasting2.3Probabilistic quantile forecasts2.4Scenario generation2.5Error metrics2.6Intraday forecast updating2.7Forecasting of auxiliary consumption2.8Meteorological data sources2.9Model combination2.10Laboratory: price forecasting with LightGBM
3.1MILP formulation of the problem3.2Battery model with degradation3.3Evacuation constraints3.4Stochastic optimisation with scenarios3.5Robust optimisation under uncertainty3.6Dynamic programming for storage3.7Gurobi and HiGHS solvers3.8Computation times3.9Solution validation3.10Practice: MILP optimisation with Pyomo
4.1Building bids4.2Complex and block bids4.3Continuous intraday market4.4Secondary and tertiary regulation4.5Revenue stacking4.6Position management4.7Settlement and revenue calculation4.8Ex post analysis4.9Reinforcement learning4.10Workshop: bidding strategy for a typical day
5.1Software architecture5.2SCADA integration5.3Market APIs5.4KPI monitoring5.5Strategy backtesting5.6Model governance5.7Cybersecurity of the bidding system5.8Scaling to a portfolio5.9Vendor management5.10Case study: backtesting one year of operation
6.1Definition of the plant and markets6.2Starting data6.3Forecasting models6.4Optimiser formulation6.5Bidding strategy6.6Backtesting of results6.7Sensitivity analysis6.8Deployment architecture6.9Report and presentation6.10Final review with the tutor
How you'll learn
A 100% online course on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: students progress at their own pace within the intake, which makes it possible to combine the course with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python (Pyomo), Gurobi, HiGHS, LightGBM, Apache Airflow, in free, academic or evaluation versions. Case studies are based on real market price forecasting procedures, stochastic scheduling optimisation with batteries, and backtesting of bidding strategies. Assessment is continuous per 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.
Identify the economic objectives of an EMS in electricity markets.
Develop price and generation forecasts for scheduling.
Formulate MILP and stochastic optimisation problems for plants with storage.
Build bidding strategies for day-ahead, intraday and balancing markets.
Evaluate strategies through backtesting and ex post analysis.
Where this takes you
Requirements
- No prior qualification is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient Spanish to follow technical regulatory texts.
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 300 total hours spread over 3 to 5 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
You work with Python (Pyomo), Gurobi, HiGHS, LightGBM, Apache Airflow. Free, academic or evaluation versions are used, and the tutor indicates 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 title from the Ministry.
Yes. Modules passed in a Course or Postgraduate Diploma in the same area are recognised towards the advanced programme. Check the recognition policy when you enrol.
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