EU Energy & Cleantech Research Methodology

A systematic approach to understanding Europe's energy markets through data-driven analysis and clear visual insights.

Our Methodology Framework

Designed for clients who need clear, reliable answers about Europe's real energy and technology markets. Everything we deliver is grounded in per-unit metrics (€/MWh, €/kWh, MW, GWh) and backed by:

Hourly System Data

Regulatory Analysis

Project Constraints

Technology Economics

Applies across power markets, BESS, EV charging, solar, wind, batteries, and cleantech supply chains — with each market using only the modules that are relevant.

1

Clear Scope, Objectives & Research Questions

Every study begins with a tight scope so the analysis stays focused and practical.

Geographic coverage:

  • EU-27 plus UK, Norway, Switzerland
  • Or priority markets such as Germany, France, UK, Spain, Italy, Nordics, CEE

Segments we analyse:

  • Generation: solar, wind, hydro, thermal, nuclear
  • TSOs/DSOs and grid infrastructure
  • Wholesale markets: day-ahead, intraday, balancing
  • Retail and C&I supply
  • Storage (BESS, pumped hydro)
  • Hydrogen, flexibility, EV charging, batteries, cleantech manufacturing

Example objectives:

  • Map market structure and competition
  • Analyse price trends and volatility
  • Evaluate technology economics and revenue stacks
  • Assess policy and regulatory impacts
  • Identify risk-adjusted opportunities and bottlenecks

Key questions:

  • How are prices changing across EU markets?
  • What drives volatility today?
  • Where do grid constraints block growth?
  • Which countries and technologies offer the best risk-return?
2

Data Collection & Sources

We build a country-hour panel dataset wherever possible to ensure insights are grounded in actual market behavior.

Primary Data (per-unit, granular)

ENTSO-E Transparency Platform
  • Hourly/15-min demand
  • Generation by fuel
  • Cross-border flows
  • Outages
  • Day-ahead & intraday prices
  • Curtailment indicators
Market Exchanges
  • EPEX Spot, Nord Pool, OMIE, BSP, EEX
  • Day-ahead, intraday, balancing prices (€/MWh)
  • Congestion and redispatch costs
Eurostat & ACER
  • Retail C&I and household tariffs
  • Taxes/levies
  • Quarterly wholesale benchmarks

Secondary Data

  • Ember, S&P, IEA, Fraunhofer, Bruegel
  • LCOE (€/MWh)
  • Fuel prices (€/MWh equivalent)
  • Carbon prices (€/tCO₂)
  • Technology performance
  • Regulators (e.g., BNetzA, CRE, Ofgem)
  • Tariff codes
  • Capacity mechanism payments
  • Auction rules
  • Grid access regulations

Sampling & Time Window

  • Focus on major bidding zones: DE-LU, FR, UK, IT, Nordics
  • 2020–2025 historic data
  • Forward curves where available to 2030
  • Normalisation to per-unit values for cross-country comparison
3

Data Processing & Normalisation

We clean and standardise all inputs to ensure fair comparisons across countries.

Per-unit standardisation:

  • €/MWh for wholesale
  • €/kWh for retail
  • MW for capacity
  • GWh for generation
  • Weighted averages based on load

Triangulation:

  • Cross-verify ENTSO-E vs exchanges vs Ember
  • Adjust for bidding zone splits
  • Account for market coupling influences

Feature engineering:

  • Volatility (σ €/MWh)
  • Frequency of negative prices
  • Merit-order curve estimation
  • LCOE vs wholesale price differentials
  • Balancing market spread analysis

Tools used:

  • Python, Pandas for data cleaning
  • Jupyter environments for modelling
  • Automated scripts for hourly data aggregation
4

Market & System-Level Analysis

We convert raw system data into clear, comparable market insights.

Market structure:

  • Generation mix by fuel
  • Ownership concentration (HHI)
  • Utility vs IPP capacity distribution

Price & demand behavior:

  • Hourly, daily and seasonal price patterns
  • Distribution of spikes and negative prices
  • Load curve analysis
  • Temperature–demand correlations

Cross-country comparison:

  • Average prices
  • Volatility levels
  • RES penetration
  • CO₂ intensity
  • Interconnection ratios
5

Drivers of Price & Volatility

We isolate what truly moves EU power prices.

Econometric & time-series models:

  • ARIMAX / SARIMA
  • Panel regression across markets
  • GARCH models for volatility clustering

Inputs include:

  • Load (MW)
  • Wind & solar output (GWh)
  • Fuel prices (€/MWh)
  • ETS prices (€/tCO₂)
  • Interconnector flows
  • Outages
  • Weather

Scenario-based driver analysis:

  • Gas price spikes
  • Nuclear outages
  • Wind droughts
  • Hydro shortages
  • Policy changes
  • New interconnectors

We also back-test how much each driver contributed to historical price movements.

6

Technology Economics & Competitiveness

We benchmark technology performance and cost evolution using consistent metrics.

Includes:

  • Capex, opex, efficiency
  • LCOE estimates (€/MWh)
  • WACC sensitivity
  • Carbon cost sensitivity

 

  • Storage cycle economics (€/kWh, €/MW-yr)
  • Module/turbine cost trends
7

Revenue Stack & Bankability

For each asset class, we map out all revenue sources and risks.

Revenue sources:

  • Energy market revenues
  • Intraday and balancing opportunities
  • Ancillary services
  • Capacity payments
  • CfDs, FiTs, premiums
  • PPA structures (corporate + utility)

 

This section is essential for investors and lenders to understand:

  • Merchant exposure vs contracted revenue
  • Revenue stability
  • Risk-adjusted returns
8

Policy, Regulation & Market Design

We translate complex policy frameworks into practical implications.

EU-level review:

  • ETS reforms
  • Market design packages
  • Taxonomy classification
  • State-aid guidelines

Country regimes:

  • Auction rules
  • Permitting requirements
  • Grid connection rules
  • Curtailment compensation
  • Tariff design
  • Flexibility policies

Regulatory risks:

  • Price caps/floors
  • Retroactive changes
  • Windfall taxes
  • Local acceptance issues
9

Grid, Infrastructure & System Adequacy

We analyse how infrastructure limits or enables market growth.

Grid & interconnection:

  • Congestion hotspots
  • Curtailment patterns
  • TSO/DSO investment plans
  • Interconnector pipeline

Adequacy & security of supply:

  • LOLE, reserve margins
  • Role of gas, nuclear, hydro, storage
  • Stress tests for extreme conditions
10

Modelling Validation & Scenarios

We check all models for realism and reliability.

Validation techniques:

  • Backtesting (MAE/RMSE)
  • Scenario sensitivity (+/-20% RES output, fuel prices)
  • Rapid Evidence Assessment of literature
  • Stakeholder feedback loop

 

This ensures accuracy and transparency in all our analyses and recommendations.

11

Reporting & Visualisation

Everything is packaged in clear visual formats for easy understanding.

Visual outputs:

  • Price heatmaps (€/MWh)
  • Load and RES patterns
  • Merit-order curves
  • LCOE stacks
  • Curtailment & congestion maps

 

  • Policy dashboards
  • Technology scorecards
  • Country opportunity matrices
12

Stakeholder & Expert Insights

When required, we conduct structured interviews to add real-world judgment where data alone is not enough.

Interviewees include:

  • Utilities & IPPs
  • TSOs & DSOs
  • OEMs
  • Infra funds and lenders

 

  • Policymakers
  • Industry associations

Ready to Apply This Methodology?

Our team of energy analysts can deliver custom research tailored to your specific needs.

Contact Our Research Team