Model classsification

Energy models aim at representing one or various aspects of the energy system, such as, energy production and technological development; energy consumption and consumer behavior; and linkages with the economy, other sectors and the climate.

Models can be classified according to different dimensions:

Top-down models include a detailed representation of the economy and model the energy sector with an aggregate production function. General equilibrium models are typical top-down models.

Bottom-up models feature a detailed description of the energy technologies and have exogenous assumptions on the development of the economy.

Hybrid models aim at including a detailed representation of both the econony and the energy sector by combining top-down and bottom-up approaches.

System Dynamics (Forrester, 1961; Sterman, 2000) is a simulation and mapping method based on causal modelling. System Dynamics applies a stock and flow notification to represent a system's structure on an aggregated level. The central elements of System Dynamics are feedback loops - chains of causal interlinkages that form a back-coupled cycle. Technically the simulation model is a system of differential, integral and auxiliary equations.

Sterman, J. (2000). Business Dynamics: McGraw-Hill.
Forrester, J. W. (1961). Industrial Dynamics. Cambridge, MA: The M.I.T. Press.

Models are usually developed to address specific questions and are therefore only suitable for the purpose they were designed for. General purposes reflect how the future is addressed in the model.

Forecasting models extrapolate the historical trends into the future to forecast the development of the energy system.

Exploring the futureis done by scenario analysis , in which a limited number of "intervention" scenarios are compared with a "business as usual" reference scenario.

"Backcasting" models construct visions of desired futures by interviewing experts in the fields and subsequently look at what needs to be changed to accomplish such futures.

Econometric models are frameworks that use statistical methods to extrapolate past market behavior into the future.

Optimization techniques are used in a large range of energy system models to determine an optimal development or state of the economy or the energy system. Partial, general equilibrium and optimal growth models use optimization techniques. Partial equilibrium models focus on equilibria in parts of the economy, such as the equilibrium between energy demand and supply. General equilibrium models are particularly concerned with the conditions which allow for simultaneous equilibrium in all markets. Optimal growth models maximize intertemporal welfare subject to equilibrium constraints and, in most cases, assume perfect foresight about future production and consumption.

Simulation models are descriptive models based on a logical representation of a system.

A deterministic model has no probabilitic elements while in a stochastic one or more variables are random. A stochastic model estimates the probability of ocurrance of different outputs.

Geographical coverage: Single region, multi-region and global

Single and multi-sectoral

A dynamic model represents the time dependent changes in the system while a static model is time-invariant. Dynamic models can have short- and long- time horizons.

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