Energy Modeling Framework. Model for Energy Supply Strategy Alternatives and their General Environmental Impact (MESSAGE). MESSAGE is a systems engineering optimization model used for medium- to long-term energy system planning, energy policy analysis, and scenario development (Messner and Strubegger, 1995). The model provides a framework for representing an energy system with all its interdependencies from resource extraction, imports and exports, conversion, transport, and distribution, to the provision of energy end-use services such as light, space conditioning, industrial production processes, and transportation.

References in zbMATH (referenced in 13 articles )

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  1. Moret, Stefano; Babonneau, Frédéric; Bierlaire, Michel; Maréchal, François: Decision support for strategic energy planning: a robust optimization framework (2020)
  2. Chen, Huayi; Ma, Tieju: Optimizing systematic technology adoption with heterogeneous agents (2017)
  3. Edelev, Alexey; Sidorov, Ivan: Combinatorial modeling approach to find rational ways of energy development with regard to energy security requirements (2017)
  4. Ma, Tieju; Chen, Huayi: Adoption of an emerging infrastructure with uncertain technological learning and spatial reconfiguration (2015) ioport
  5. Chen, Huayi; Ma, Tieju: Technology adoption with limited foresight and uncertain technological learning (2014)
  6. Weber, Klaus; Martinsen, Dag: From system cost minimization to sustainability maximization -- a new fuzzy program approach to energy systems analysis (2013)
  7. Gritsevskyi, Andrei; Ermoliev, Yuri: Modeling technological change under increasing returns and uncertainty (2012)
  8. Powell, Warren B.; George, Abraham; Simão, Hugo; Scott, Warren; Lamont, Alan; Stewart, Jeffrey: SMART: A stochastic multiscale model for the analysis of energy resources, technology, and policy (2012)
  9. Kosugi, Takaki Takanobu: Assessments of `greenhouse insurance’: a methodological review (2010)
  10. Ma, T.; Grubler, A.; Nakamori, Y.: Modeling technology adoptions for sustainable development under increasing returns, uncertainty, and heterogeneous agents (2009)
  11. Wittmann, Tobias; Bruckner, Thomas: Agentenbasierte modellierung urbaner energiesysteme (2007) ioport
  12. Henning, Dag; Amiri, Shahnaz; Holmgren, Kristina: Modelling and optimisation of electricity, steam and district heating production for a local Swedish utility (2006)
  13. Kainuma, Mikiko; Matsuoka, Yuzuru; Morita, Tsuneyuki: The AIM/end-use model and its application to forecast Japanese carbon dioxide emissions (2000)