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A knowledge representation model for the optimisation of electricity generation mixes

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  • Chee Tahir, Aidid
  • Bañares-Alcántara, René

Abstract

Energy models such as MARKAL, MESSAGE and DNE-21 are optimisation tools which aid in the formulation of energy policies. The strength of these models lie in their solid theoretical foundations built on rigorous mathematical equations designed to process numerical (quantitative) data related to economics and the environment.

Suggested Citation

  • Chee Tahir, Aidid & Bañares-Alcántara, René, 2012. "A knowledge representation model for the optimisation of electricity generation mixes," Applied Energy, Elsevier, vol. 97(C), pages 77-83.
    • Handle: RePEc:eee:appene:v:97:y:2012:i:c:p:77-83
    DOI: 10.1016/j.apenergy.2011.12.077
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    2. Balaji, Bharathan & Bhattacharya, Arka & Fierro, Gabriel & Gao, Jingkun & Gluck, Joshua & Hong, Dezhi & Johansen, Aslak & Koh, Jason & Ploennigs, Joern & Agarwal, Yuvraj & Bergés, Mario & Culler, Davi, 2018. "Brick : Metadata schema for portable smart building applications," Applied Energy, Elsevier, vol. 226(C), pages 1273-1292.
    3. Wierzbowski, Michal & Filipiak, Izabela & Lyzwa, Wojciech, 2017. "Polish energy policy 2050 – An instrument to develop a diversified and sustainable electricity generation mix in coal-based energy system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 51-70.
    4. Sung-Yoon Huh & Chul-Yong Lee, 2017. "A Demand-Side Perspective on Developing a Future Electricity Generation Mix: Identifying Heterogeneity in Social Preferences," Energies, MDPI, vol. 10(8), pages 1-19, August.
    5. Oree, Vishwamitra & Sayed Hassen, Sayed Z. & Fleming, Peter J., 2017. "Generation expansion planning optimisation with renewable energy integration: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 790-803.

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    Keywords

    Modelling; Ontologies; Policies;
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