Master’s in Grid Planning for e-Mobility Engineering — Impact Studies, DSO/TSO, Flexible Demand
Online master's programme of 1,900 hours in grid planning engineering for e-mobility — impact studies, DSO/TSO and flexible demand. 12 modules covering distribution network modelling, charging demand forecasting, grid impact studies, transmission planning, smart charging, local flexibility markets, investment optimisation, power quality, grid digital twins and regulation, with an assigned technical tutor.
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
Model distribution networks for e-mobility studies.
Forecast charging demand using probabilistic methods.
Assess the impact of charging on distribution and transmission networks.
Quantify the flexibility provided by electric vehicle demand.
Design local flexibility products and markets.
Optimise network investments against flexible solutions.
Prepare a complete grid planning study.
Who it's for
- Network planning engineers at distribution and transmission companies.
- Energy flexibility analysts.
- Grid study engineers carrying out hosting capacity and impact assessments.
- E-mobility consultants advising cities and CPOs.
- Energy data analysts working with smart meter and mobility data.
- Electricity regulation specialists.
- Engineering or science graduates seeking to enter electricity distribution.
What you'll work with
- EN 50160 (voltage characteristics of public networks)
- Directive (EU) 2019/944 (internal electricity market)
- Regulation (EU) 2023/1804 (AFIR, alternative fuels infrastructure)
- IEC 61000-3-12 (harmonic current limits for equipment)
- Royal Decree 1183/2020 (grid access and connection in Spain)
- IEC 61968 (CIM for distribution management)
- ISO 15118-20 (vehicle-to-grid communication interface)
- Regulation (EU) 2016/1388 (demand connection network code)
- OpenDSS
- DIgSILENT PowerFactory
- pandapower
- QGIS
- Python with Pyomo
12 modules · 1900 h
1.1Structure of the Spanish power system1.2TSO and DSO roles1.3Electric vehicle penetration forecasts1.4Energy demand from charging1.5Charging profiles by segment1.6Energy transition and electrification1.7Binding transmission planning1.8Distribution company investment plans1.9Mobility data for planning1.10Case study: charging demand for a city
2.1Medium- and low-voltage network topologies2.2Modelling lines and transformers2.3Load flow in radial networks2.4Unbalanced three-phase networks2.5ZIP load models and profiles2.6Smart meter data2.7GIS tools for networks2.8Model validation with measurements2.9Time-series simulation2.10Lab: load flow in OpenDSS
3.1Agent-based models3.2Simulation of mobility and travel patterns3.3Arrival probability and duration3.4Monte Carlo methods3.5Machine learning for forecasting3.6Electric vehicle adoption scenarios3.7Fleet charging versus private charging3.8Seasonality and weather3.9Forecast uncertainty3.10Practical: Monte Carlo model of residential charging
4.1Transformer overloading4.2Thermal limits of cables4.3Voltage deviations4.4Phase imbalance4.5Charger harmonics4.6Additional technical losses4.7Transformer ageing4.8Hosting capacity per node4.9DSO acceptance criteria4.10Workshop: impact study on an urban network
5.1Impact of high-power hubs5.2High-voltage connection of charging stations5.3N-1 contingency analysis5.4Stability and reserve5.5TSO-DSO coordination5.6Planning of electricity infrastructure5.7Access and connection to the transmission network5.8Charging corridors for heavy-duty vehicles5.9Long-term scenarios5.10Case study: connection of a truck charging hub
6.1Electric vehicle flexibility6.2Time-shifting of charging6.3Price signals and time-of-use tariffs6.4Direct load control6.5Implicit and explicit demand response6.6Aggregation of distributed resources6.7Quantifying available flexibility6.8User behaviour and acceptance6.9Battery and mobility constraints6.10Lab: price-based charging optimisation
7.1Local flexibility markets7.2Platforms such as Piclo and NODES7.3Flexibility products for the DSO7.4Congestion mechanisms7.5Verification and baselines7.6Remuneration of flexibility services7.7Coordination with wholesale markets7.8Electricity Market Directive 2019/9447.9European local flexibility experiences7.10Practical: design of a flexibility product
8.1Traditional versus flexible planning8.2Cost of network reinforcements8.3Stochastic investment optimisation8.4Value of flexibility as an alternative8.5Cost-benefit analysis of networks8.6Optimal location of charging points8.7Joint planning of charging and network8.8Regulated remuneration of distribution8.9Investment risk analysis8.10Workshop: optimisation with Pyomo
9.1Continuity of supply and TIEPI indices9.2Voltage quality to EN 501609.3Harmonic emissions from chargers9.4Flicker and fluctuations9.5Protection with bidirectional flows9.6Voltage dips and disconnection9.7Grid codes for chargers9.8IEC 61000 compatibility standards9.9Power quality monitoring9.10Case study: harmonic analysis in a car park
10.1Smart meters and data concentrators10.2Low-voltage monitoring10.3Sensors in transformer substations10.4Integration of CPO and DSO data10.5Digital twin of the distribution network10.6Low-voltage state estimation10.7Advanced demand analytics10.8Data governance and protection10.9Interoperability with CIM IEC 6196810.10Practical: state estimation with AMI data
11.1Access and connection regulation11.2CNMC circulars11.3Network tariffs and charges11.4Review of DSO investment plans11.5Role of the DSO in charging11.6AFIR Regulation and grid obligations11.7Municipal electrification strategies11.8Public consultation and participation11.9European regulatory comparison11.10Workshop: analysis of an access circular
12.1Definition of scope and scenarios12.2Modelling the study network12.3Charging demand forecast12.4Grid impact study12.5Assessment of available flexibility12.6Comparison of reinforcement alternatives12.7Cost-benefit analysis of the alternatives12.8Planning recommendations12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: you progress at your own pace within the intake, so it can be combined with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is OpenDSS, DIgSILENT PowerFactory, pandapower, QGIS and Python with Pyomo, in free, academic or evaluation versions. Testing is studied through real procedures for hosting capacity studies, Monte Carlo simulation of charging demand and power quality analysis in networks with charging. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: EN 50160, Directive (EU) 2019/944 (internal electricity market), Regulation (EU) 2023/1804 (AFIR), IEC 61000-3-12, Royal Decree 1183/2020 (access and connection), IEC 61968, ISO 15118-20, Regulation (EU) 2016/1388 (demand connection network code).
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
- A university degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- An internet connection and a computer able to run 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 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with OpenDSS, DIgSILENT PowerFactory, pandapower, QGIS and Python with Pyomo, 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 Master's Thesis. 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 in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A university degree in engineering, science or architecture, or equivalent professional experience, plus 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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