Energy models are optimisation tools which aid in the formulation of energy policies. Built on mathematics, the strength of these models lie in their ability to process numerical data which in turn allows for the generation of an electricity generation mix that incorporates economic and the environmental aspects. Nevertheless, a comprehensive formulation of an electricity generation mix should include aspects associated with politics and society, an evaluation of which requires the consideration of non-numerical qualitative information. Unfortunately, the use of energy models for optimisation coupled with the evaluation of information other than numerical data is a complicated task. Two prerequisites must be fulfilled for energy models to consider political and societal aspects. First, the information associated with politics and society in the context of energy policies must be identified and defined. Second, a software tool which automatically converts both quantitative and qualitative data into mathematical expressions for optimisation is required. We propose a software framework which uses a semantic representation based on ontologies. Our semantic representation contains both qualitative and quantitative data. The semantic representation is integrated into an Optimisation Modelling System which outputs a model consisting of a set of mathematical expressions. The system uses ontologies, engineering models, logic inference and linear programming. To demonstrate our framework, a Prototype Energy Modelling System which accepts energy policy goals and targets as inputs and outputs an optimised electricity generation mix has been developed. To validate the capabilities of our prototype, a case study has been conducted. This thesis discusses the framework, prototype and case study.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:600521 |
| Date | January 2011 |
| Creators | Chee Tahir, Aidid |
| Contributors | Bañares-Alcántara, Rene |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:2c1f7a3c-4464-4bd0-b40b-67a0ad419529 |
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