Postgraduate Diploma in Tariffs, Dynamic Pricing and Revenue Management
Online 800-hour Postgraduate Diploma in Tariffs, Dynamic Pricing and Revenue Management. 8 modules covering Regulation (EU) 2023/1804 (AFIR), Royal Decree 184/2022 and Python (pandas, scikit-learn). Assigned tutor and enrolment open.
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
Analyse the cost structure and business models of electric vehicle charging.
Design transparent tariff structures that comply with the AFIR.
Assess exposure to electricity market prices and their hedging.
Build charging demand forecasting models.
Implement dynamic pricing algorithms based on ethical criteria.
Apply revenue management techniques to charging networks.
Verify regulatory and consumer protection compliance.
Who it's for
- Electric mobility pricing managers who want to specialise in Tariffs, Dynamic Pricing and Revenue Management.
- Revenue managers of charging networks who want to specialise in Tariffs, Dynamic Pricing and Revenue Management.
- Energy data analysts who want to specialise in Tariffs, Dynamic Pricing and Revenue Management.
- Product managers of eMSP services who want to specialise in Tariffs, Dynamic Pricing and Revenue Management.
- Electric mobility consultants who want to specialise in Tariffs, Dynamic Pricing and Revenue Management.
- CPO business managers who want to specialise in Tariffs, Dynamic Pricing and Revenue Management.
- Engineering or science graduates seeking to join charging point operators.
What you'll work with
- Regulation (EU) 2023/1804 (AFIR)
- Royal Decree 184/2022
- Directive (EU) 2019/944
- Circular 3/2020 of the CNMC
- Royal Decree 148/2021
- Regulation (EU) 2016/679 (GDPR)
- ISO 15118-20:2022
- OCPI 2.2.1
8 modules · 800 h
1.1Cost structure of a charging point1.2CAPEX and OPEX at fast-charging stations1.3Capacity charge and energy charge1.4Network access tariffs and system charges1.5Utilisation rate and break-even point1.6CPO, eMSP and hub business models1.7Price elasticity of charging demand1.8Benchmarking public tariffs in Europe1.9Public subsidies and their effect on profitability1.10Workshop: calculating the levelised cost per kWh
2.1Per-kWh tariffs versus per-minute tariffs2.2Session fees and occupancy charges2.3Penalties for prolonged parking2.4Subscriptions and charging bundles2.5Ad hoc pricing and bank card payment2.6Price transparency under the AFIR2.7Differentiated tariffs for fleets2.8Roaming tariffs between operators2.9Tariffs for heavy vehicles and buses2.10Case study: tariff redesign for an urban hub
3.1How the day-ahead and intraday markets work3.2Voluntary price for small consumers3.3PPA contracts and forward hedges3.4Managing contracted capacity excesses3.5Time-of-use discrimination and tariff periods3.6Volatility and exposure to spot prices3.7Solar self-consumption and batteries at the station3.8Demand aggregation and flexibility services3.9Access contracts with the distribution company3.10Laboratory: cost simulation with hourly prices
4.1Time series of sessions and energy4.2Daily, weekly and annual seasonality4.3ARIMA models and exponential smoothing4.4Gradient boosting to predict occupancy4.5Exogenous variables: traffic, weather and events4.6Vehicle arrivals per site4.7Error metrics: MAPE and RMSE4.8Hierarchical forecasting by network and by charger4.9Probabilistic forecasting by quantiles4.10Practice: forecasting model using OCPP data
5.1Occupancy-based pricing in real time5.2Time slots and time-of-use tariffs5.3Revenue optimisation with limited capacity5.4Discrete choice models for drivers5.5Multi-armed bandits for price experimentation5.6Reinforcement learning applied to tariffs5.7Ethical limits and user acceptance5.8Communicating the price on app and screen5.9Competitor pricing and strategic response5.10Laboratory: pricing engine in Python
6.1Perishable capacity by charging slot6.2Bookings, overbooking and no-shows6.3Customer segmentation and fare fences6.4Nested booking limits by segment6.5Smart charging and power allocation6.6Queue management at high-power hubs6.7Revenue indicators per charger and average ticket6.8Integration with the CPO backend6.9Forecasting booking cancellations6.10Case study: RM plan for an intercity corridor
7.1AFIR price information obligations7.2Royal Decree 184/2022 framework7.3Competition law and abusive pricing7.4Consumer protection and clear terms7.5Invoicing, VAT and energy receipts7.6GDPR in personalised pricing7.7Auditing algorithmic decisions7.8CNMC supervision and complaints7.9Payment accessibility and non-discrimination7.10Workshop: tariff compliance checklist
8.1Selection of the network and scenario8.2Cost analysis and competitive benchmarking8.3Proposed tariff structure8.4Demand forecasting model8.5Dynamic pricing engine8.6Revenue simulation and sensitivity8.7User communication plan8.8Regulatory and risk assessment8.9Report and presentation8.10Final 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. No fixed timetables: students progress at their own pace within the intake, which makes it possible to combine the programme with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Python (pandas, scikit-learn), Gurobi, Power BI, Microsoft Excel Solver, Tableau, in free, academic or evaluation versions. Case studies draw on real tariff simulation procedures using real OCPP session data, elasticity analysis of an urban charging network, and the design of a revenue management plan for a fast-charging hub. Assessment is continuous by module, plus the final integrative project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Analyse the cost structure and business models of electric vehicle charging.
Design transparent tariff structures that comply with the AFIR.
Assess exposure to electricity market prices and their hedging.
Build charging demand forecasting models.
Implement dynamic pricing algorithms based on ethical criteria.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient English to follow technical regulatory reading.
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 spread over 6 to 8 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
You will work with Python (pandas, scikit-learn), Gurobi, Power BI, Microsoft Excel Solver, Tableau. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An own diploma from SEIUM Institute upon passing the continuous assessment and the integrative project. It 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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