Power Price Projections

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.)

The other clear added-value of POLES is that sectoral energy demand is endogenous and can be modelled/refined by the user, who will find logical retroactions between supply and demand of electricity. Energy system optimisation models, in contrast, generally use energy demand as an exogenous input parameter – once again reflecting either a fixed long-term assumption or a perfect long-term foresight for agents of the energy system.

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.

Dispatch

• 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.