Description

Global greenhouse gas emissions significantly accelerate climate change and adversely affect life on earth. To mitigate these effects, greenhouse gas emissions need to be cut-down by significant reductions in primary energy consumption. Primary energy consumption can be reduced by increasing the efficiency of energy supply, which is mainly fixed during the synthesis of energy systems. Optimal synthesis of energy systems can be realized by mathematical optimization, however the solvable problem complexity is limited. In contrast, energy systems encompass highly complex energy conversion technologies and an increasing number of time-varying operation conditions. Thus, the synthesis of real-world energy systems usually result in large-scale optimization problems, which are computationally prohibitive.

In this thesis, a solution framework is proposed to enable large-scale synthesis of energy systems. The framework exploits the two-stage character of synthesis problems: the decisio

OptimizationBased Synthesis of LargeScale Energy Systems by TimeSeries Aggregation

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Global greenhouse gas emissions significantly accelerate climate change and adversely affect life on earth. To mitigate these effects, greenhouse gas... Read more

    Publisher: Verlag G. Mainz
    Publication Date: 1/15/2018
    ISBN13: 9783958862401, 978-3958862401
    ISBN10: 3958862403

    Non Fiction , Technology, Engineering & Agriculture , Education

    Description

    Global greenhouse gas emissions significantly accelerate climate change and adversely affect life on earth. To mitigate these effects, greenhouse gas emissions need to be cut-down by significant reductions in primary energy consumption. Primary energy consumption can be reduced by increasing the efficiency of energy supply, which is mainly fixed during the synthesis of energy systems. Optimal synthesis of energy systems can be realized by mathematical optimization, however the solvable problem complexity is limited. In contrast, energy systems encompass highly complex energy conversion technologies and an increasing number of time-varying operation conditions. Thus, the synthesis of real-world energy systems usually result in large-scale optimization problems, which are computationally prohibitive.

    In this thesis, a solution framework is proposed to enable large-scale synthesis of energy systems. The framework exploits the two-stage character of synthesis problems: the decisio

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