Such models often employ scenario analysis to investigate different assumptions about the technical and economic conditions at play.
IPCC-style integrated assessment models, which also contain a representation of the world energy system and are used to examine global transformation pathways through to 2050 or 2100 are not considered here in detail.
[2] The IPCC reports that climate change mitigation will require a fundamental transformation of the energy supply system, including the substitution of unabated (not captured by CCS) fossil fuel conversion technologies by low-GHG alternatives.
Single-year models – set in either the present or the future (say 2050) – assume a non-evolving capital structure and focus instead on the operational dynamics of the system.
Single-year models normally embed considerable temporal (typically hourly resolution) and technical detail (such as individual generation plant and transmissions lines).
Long-range models, usually spanning decades, attempt to minimize both the short and long-run costs as a single intertemporal problem.
The demand-side (or end-user domain) has historically received relatively scant attention, often modeled by just a simple demand curve.
[4][5] Long-range models are often limited to calculations at yearly intervals, based on typical day profiles, and are hence less suited to systems with significant variable renewable energy.
[6] Implementing languages include GAMS, MathProg, MATLAB, Mathematica, Python, Pyomo, R, Fortran, Java, C, C++, and Vensim.
[3]: S30–S31 A 2014 paper outlines the modeling challenges ahead as energy systems become more complex and human and social factors become increasingly relevant.
For instance, given the presence of national interconnectors, the western European electricity system may be modeled in its entirety.
Engineering-based models usually contain a good characterization of the technologies involved, including the high-voltage AC transmission grid where appropriate.
LEAP allows policy analysts to create and evaluate alternative scenarios and to compare their energy requirements, social costs and benefits, and environmental impacts.
Portions of the model may also be used for the commitment and dispatch phase (updated on 5 minute intervals) in operation of wholesale electric markets for RTO and ISO regions.
These ISO and RTO regions also utilize a GE software package called MARS (Multi-Area Reliability Simulation) to ensure the power system meets reliability criteria (a loss of load expectation (LOLE) of no greater than 0.1 days per year).
Further, a GE software package called PSLF (Positive Sequence Load Flow) and a Siemens software package called PSSE (Power System Simulation for Engineering) analyzes load flow on the power system for short-circuits and stability during preliminary planning studies by RTOs and ISOs.
The TIMES model generator was also developed under the Energy Technology Systems Analysis Program (ETSAP).
TIMES is a technology rich, bottom-up model generator, which uses linear programming to produce a least-cost energy system, optimized according to a number of user-specified constraints, over the medium to long-term.
[44] NEMS has been used to explicitly model the demand-side, in particular to determine consumer technology choices in the residential and commercial building sectors.
[47] To improve transparency and public acceptance, some models are undertaken as open-source software projects, often developing a diverse community as they proceed.