Table 13 Formula implementation and variable description of the MUSE-RASA calculations of metrics that serve to evaluate the long-term transition of the climate-energy-economy system of this research, with a focus on the residential sector.

From: MUSE-RASA captures human dimension in climate-energy-economic models via global geoAI-ML agent datasets

MUSE-RASA calculations

Formula implementation

Service demand

\(\mathop{\sum }\limits_{i=1}^{na}{\left.\left(\frac{(1+w\ast {t}^{n})}{(1+{t}^{n})}\right)\ast \left(\frac{a\ast (1+{t}^{n})}{(1+b{e}^{GDP\ast c})}\right)\right|}_{SA{g}_{na}}\)

Supply

\(\mathop{\sum }\limits_{i=1}^{na}{(Ins{t}_{cap}\ast {\rm{UF}}\ast {E}_{out})| }_{SA{g}_{na}}\)

Fuel/electricity consumption

\(\mathop{\sum }\limits_{i=1}^{na}{(Ins{t}_{cap}\ast {\rm{UF}}\ast {E}_{in})| }_{SA{g}_{na}}\)

CAPEX

\(\mathop{\sum }\limits_{i=1}^{na}{\left.\left({{\rm{TC}}}_{reg}\ast {\left(\frac{Ins{t}_{cap}}{Re{f}_{cap}}\right)}^{tce}\right)\right|}_{SA{g}_{na}}\)

LCOE

\(\mathop{\sum }\limits_{i=1}^{na}{\left.\left(\frac{{\sum }_{t=1}^{n}\frac{{I}_{t}+{M}_{t}+{F}_{t}}{{\left(1+r\right)}^{t}}}{{\sum }_{t=1}^{n}\frac{{E}_{t}}{{\left(1+r\right)}^{t}}}\right)\right|}_{SA{g}_{na}}\)

Emissions

\(\mathop{\sum }\limits_{i=1}^{na}{({\rm{FC}}\ast {\rm{ef}})| }_{SA{g}_{na}}\)

  1. SAg: Spatial agent, na: number of agents per region. w: weights; t: foresight time (5 years is assumed); a: 1e6*constant*population; n: 4; b: constant; GDP: Gross Domestic Product; c: constant; Instcap: Installed capacity; UF: Utilisation factor; Eout: Energy out of the technology supply; Ein: Energy into the technology supply; TC: Technology cost; reg: region; Refcap: Reference capacity in base year; tce: technology scaling capacity exponent; It: Investment expenditures in year t (including financing); Mt: Operations and maintenance expenditures in year t; Ft: Fuel expenditures in year t; Et: Energy generation in year t; r: Discount rate; n: Life of the system; FC: fuel consumption; ef: emission factor.