Optimization of energy systems under the aspect of sustainability

One of the basic ideas of technology assessment (TA) is to point out alternatives to any approached problem solution. This includes, for instance, with respect to the aim of sustainable development, the requirement of better solutions for technical applications. This idea of TA can be taken as an optimization problem. Optimization of a technical application is aimed to its energy efficiency, its material intensity, or its sustainability, respectively. The application of usual optimization procedures is limited especially in the case of a multicriterial evaluation. Restraints could be nonlinear problems, or problems with many parameters, or many restrictions due to the programming effort and memory demand of the computer. Natural optimization techniques, named as selective, genetic, or evolutionary techniques, orient on principles of evolutionary biology. These techniques do not have requirements to linearity, differentiation or a certain problem structure and have often a less programming effort, for they are predestined to apply to TA. In this contribution a new optimization technique based on a combination of soft computing methods is presented and applied to energy conversion technologies. The technology mix building an energy supply system is evaluated with a fuzzy logic based approach and optimized with a genetic algorithm. The results are properties and compounds required for future energy conversion technologies under the aspects of a sustainable development