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Power Price Projections

A 360° approach to long-term wholesale power price data.

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Power Price Projections

At last, an alternative choice is available in future power price data. Our Power Price Projections service gives you annual wholesale price projections backed by the energy modelling expertise of Enerdata and its globally recognised POLES model. The ultimate strategic tool for energy investors and developers to estimate their long-term returns on investments.

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Key Features

Annual projections (in US$/MWh), from three detailed scenarios through 2050.
Projections based on latest available data.
Up-to-date historical data.
32 countries covered.
Output in both table and graph format, available as an Excel export.
Fully updated annually.


The proven methodological foundation of Power Price Projections is our proprietary POLES model: A robust, multi-country power projection model that is used by numerous energy companies, utilities, investors and developers worldwide.

Power Price Projections data utilises historical spot prices, which are indexed to the POLES model’s wholesale price projections going forward.

Main Differences Between POLES and “Pure Optimisation” Power Models

The first advantage of the POLES modelling approach for capacity and production planning is that it avoids the ‘winner-takes-all’ effect often observed in pure optimisation models. Due to the consideration of historical capacity and production mixes, along with the introduction of non-economic competition parameters, POLES allocates electricity generation technologies on the basis of LCOEs and variable costs, but also by taking into account non economical parameters (policies, mix diversification, and more).

The POLES model considers technology classes with their technical, economic and environmental parameters, with a year-by-year, recursive approach presenting two main advantages compared with optimisation models:

  • The POLES approach is more suited to depicting real energy systems with their imperfections and barriers: Where optimisation models often use a perfect foresight approach – allowing economic agents to dispose of all information over the whole time horizon – POLES implements an iterative process, accounting for long-term capacity needs and ensuring a user-defined reserve security is reached on top of peak demand.
  • The so-called ‘bang-bang’ or ‘penny-switching’ effects cannot be found in the POLES approach, where overall, the user has more control over modelling and parametrisation. (These effects, often observed in pure optimisation models, refer to achieving a completely different solution based on a negligible change to one or several input parameters.)

Overview of POLES Power Module

  • Two problems addressed: capacity planning and dispatch
  • 20+ technologies detailed, including CAPEX, variable cost, fuel cost, carbon taxes, subsidies, lifetime, load factor, efficiency and more.

Capacity Planning

  • Based on LCOE + constraints (potential and backup for RES, acceptance of nuclear, etc.)
  • Competition on seven duration loads (from 8760h/year to 730h/year)
  • Market share of each technology is distributed, thanks to a multinomial logit distribution function.
  • Recursive approach: Capacities to be installed at year y+1 are computed at year y.


  • Based on variable costs, including subsidies and taxes.
  • Market share of each technology in the merit order is distributed, thanks to a multinomial logit distribution function,
  • Must run and fatal technologies’ power generation computed separately.
  • Dispatch at year y depends on capacity installed at year y.
  • Year y is split into two typical days and 12 two-hour slices each.

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T: +33 4 7642 2546