The European energy sector has entered a phase of rapid and substantial changes, with important consequences over the decades to come.
Challenges arise from environmental concerns including increasingly ambitious greenhouse gas emission reductions, the pursuance of policies striving towards the more rational and efficient use of energy, market transformations such as the liberalisation of the European energy supply sectors and the creation of a single European energy market, the advent of innovative – partially fluctuating – power generation technologies that would change the simplistic industrial pattern of centralised producers and decentralised consumers , as well as increasing concerns about energy security of supply.
An energy model that is suitable for the analysis of impacts of policies on the EU energy markets needs to appropriately reflect these trends and address the mechanisms that explain them. Novel technologies are required to be accurately represented, both on the supply and on the demand side.
At the same time, the implications of moving an important part of the generation capacities to decentralised production need to be captured, including possible impacts on networks. In such a dynamically changing environment, a high level of technological disaggregation and the appropriate representation of technology dynamics, in the context of different policy regimes, need to be adequately captured by the model both for energy consumers and suppliers.
Finally, as policy-induced accelerated changes can lead to premature replacement of equipment the model should be able to explicitly address the corresponding stranded investment costs.
In order to address these major changes of the energy system, the Joint Research Centre of the European Commission's has developed a new energy sector economic model named POTEnCIA (Policy-Oriented Tool for Energy and Climate Change Impact Assessment).
POTEnCIA is a modelling tool for the EU energy system that follows a hybrid partial equilibrium approach. It combines behavioural decisions with detailed techno-economic data, therefore allowing for an analysis of both technology-oriented policies and of those addressing behavioural change. The model runs on an annual basis, based on historic time series and with a typical projection timeline to 2050.
Each country is modelled separately as to appropriately capture the existing differences in energy system structures, levels of energy service, technology characteristics, resources availability etc. Vintage equipment characteristics are explicitly considered, allowing for an accurate representation of the features of the energy system at each point in time.
Thus, the tool provides a consistent framework for representing the complex interactions of the energy system and its response to a wide variety of alternative assumptions and policies or policy initiatives.
Each demand and supply sector in POTEnCIA is formulated by means of a representative agent that implicitly seeks to minimise its cost and/or to maximise its benefit (profit, utility, etc.) under constraints related to behavioural preferences, technology availability, level of activity desired, degree of comfort sought, equipment installed, fuel availability and environmental considerations.
The behaviour of the representative agents within POTEnCIA is captured by causational equations (in many cases highly non-linear). Other non-linear relationships are introduced in the model as to represent the scarcity of resources, the level of exploitation of existing infrastructure and technology dynamics.
A variety of sector-specific assumptions are applied within the model. These concern the different planning horizons, the formation of expectations about prices, technologies, resources, etc., and the role of those expectations in economic decision making. Expectations about future markets are also accounted for.
At the level of the overall energy system, the model determines the equilibrium across the different sectors by means of price signals (equivalent to Lagrange multipliers in a purely optimizing modelling context) for all scarce resources (not only the traditional energy carriers, but also renewable energy, other efficiency and environmental -CO2 related- costs in relation to their potentials).
In this process different agents act as price-takers, price makers or simultaneously both. The equilibrium for network supplied energy forms (i.e. electricity, distributed steam/heat and natural gas) is treated by means of chronological load curves (at the level of representative days).
These curves are computed by the model following a bottom-up approach that links the exogenously defined load profiles at the level of individual energy uses to the corresponding energy requirements.
The equilibrium is static (determined on an annual basis) and repeated in a time-forward path while incorporating dynamic relationships as to reflect the previous decisions of each economic agent from one year to the next. Given the complexity of the problem as such and taking advantage of the annual time steps in which the model solves, POTEnCIA makes use of the equilibrium prices with a one year lag. This approach is adequate considering the (observed) delays with which price signals pass to economic agents.
POTEnCIA, though a partial equilibrium model, can also contribute to analyse, in an implicit manner, the effects that the implementation of policies may generate for the economy as a whole.
Changes in the foreseen levels of production, induced as a response to the implementation of policies, may either be interpreted as equivalent reductions in the economic activity of the corresponding sector or as shifts towards products with different value added characteristics.
POTEnCIA is based on the Integrated Database of the European Energy Sector (JRC-IDEES), which is a public one-stop data-box offering a consistent set of disaggregated energy-economy-environment data, compliant with the EUROSTAT energy balances.
JRC-IDEES is developed and maintained by the European Commission's Joint Research Centre.
The output of the model consists of:
- detailed energy balances and energy- and process- related CO2 emissions
- energy system costs and prices
- activity indicators
- installed equipment capacities, characteristics and rate of use (both for the demand and the supply side)
- dynamic technology improvements for the demand side
POTEnCIA is designed to assess the impacts of alternative energy and climate policies on the energy sector, under different hypotheses about surrounding conditions within the energy markets. The model covers each EU Member State separately, while offering, in addition, the option of addressing the EU energy system as a whole.
The typical projection period that can be analysed by POTEnCIA is up to year 2050 in annual steps. Special mechanisms and features are implemented in the model as to appropriately represent the transformation of today’s energy systems and to assess a variety of current and future energy related policies and measures. As an annual-step model, it can also be used to examine the short-term impact of new energy programs and policies.
The main use of such an instrument is for comparative scenario analysis. In other words, the projections produced by the model are not to be seen as statements of what will most likely happen (a forecast) under certain assumptions and with a certain degree of probability.
They rather act as an assessment of what might be the impact of a given specific set of assumptions (defining a certain variant scenario) with respect to a plausible central (or reference) scenario, given the formulation and the methodological characteristics of the specific tool.
POTEnCIA is designed to represent the economically driven operation of the European energy markets and the corresponding interactions of supply and demand. In that context it incorporates a large variety of instruments that can be used to analyse the effects of:
- existing and proposed legislation (EU wide and/or Member State specific) related to energy production and use;
- policies accelerating or delaying technology progress and deployment, as well as introducing standards and/or labelling;
- greenhouse gases reduction policies;
- policies aiming at the increased use of renewable energy sources;
- policies focusing on increased efficiency of energy use;
- policies promoting the use of alternative fuels;
- different pricing regimes and taxation policies;
- price peaks caused by scarcity of certain energy carriers;
- different regimes for the electricity market related to decentralisation and liberalisation;
- alternative behaviours of representative agents (both energy suppliers and consumers) affecting both their investment decisions and use of equipment;
- policies related to the development of energy networks (including the impact of modifications in the cross-country interconnection capacities)
The subsequent changes in the structure and characteristics of the energy system, including its costs and prices, are not purely based on economic grounds, but are also affected by decisions of extra-economic nature (lifestyle, etc.). To account for this, POTEnCIA represents the economic behaviour of the energy suppliers and consumers, with the appropriate level of detail, taking into account such (observed) market imperfections rather than seeking a pure cost-optimisation reaction under perfect market conditions.
Comparing the effects of the introduction of different policy assumptions to the projection of the main scenario (which only reflects current policies in place) allows quantifying their impact on the evolution of the energy system.
There are also a number of applications that go beyond the scope and the boundaries of the model and therefore cannot be addressed explicitly:
- Engineering analysis that refers to explicit technological options beyond the level of detail present in the model cannot be carried out. For instance, policies related to specific eco-design and/or labelling are addressed in an implicit manner at the level of disaggregation present in the model. However, information on the evolution of the overall characteristics of technology groups can be provided; for this purpose these groups were defined in line with eco-design definitions.
- Phenomena that occur in fractions of an annual step, such as random fluctuation in intermittent renewable energy sources supply, cannot explicitly be modelled. However, the impact of such fluctuations on the energy system can be analysed through specific snapshots, that can subsequently be incorporated in a Monte-Carlo analysis framework, contributing in this way to the assessment of the impact of alternative scenarios on given future structures (as derived from a policy scenario under default settings).
- By construction, the model cannot assess energy policy impacts on the economy unless when linked to a general equilibrium model. POTEnCIA can nevertheless provide quantified information on the impact of such policies at the level of activity for the various sectors within the energy system.
- Issues relating to a higher spatial resolution than the one used in POTEnCIA (Member State level), including for example the electricity and gas grids infrastructure, locations of wind parks etc., cannot be addressed. However, the model can implicitly capture the volume and investment cost for networks capacity expansions at country level. It also performs a dynamic update of the resource potential (re-powering) for renewable energies