Description

Climate change mitigation requires a reduction of greenhouse gas (GHG) emissions. The main emitter of GHG emissions is the energy sector, which today is based on fossil fuels. To mitigate climate change, we need to transform the energy systems to low-carbon technologies. For this purpose, new energy system designs are required along with appropriate operational strategies. In principle, these new designs and operational strategies can be identified best using mathematical optimization. However, low-carbon technologies impose challenges in solving and assessing the resulting optimization problems.

Low-carbon technologies are volatile, which increase the complexity of optimal synthesis and operation. To cope with the complexity of operational optimization, we develop a time-series decomposition method. The method decomposes the complex, time-coupled operational problem into smaller subproblems, while still providing feasible, near-optimal solutions. For the increased complexity

Optimization of LowCarbon Energy Systems from Industrial to National Scale

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Paperback by Ph.D. Baumgartner Dr Nils Julius

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Climate change mitigation requires a reduction of greenhouse gas (GHG) emissions. The main emitter of GHG emissions is the energy... Read more

    Publisher: Verlag G. Mainz
    Publication Date: 1/31/2021
    ISBN13: 9783958863859, 978-3958863859
    ISBN10: 395886385X

    Non Fiction , Technology, Engineering & Agriculture , Education

    Description

    Climate change mitigation requires a reduction of greenhouse gas (GHG) emissions. The main emitter of GHG emissions is the energy sector, which today is based on fossil fuels. To mitigate climate change, we need to transform the energy systems to low-carbon technologies. For this purpose, new energy system designs are required along with appropriate operational strategies. In principle, these new designs and operational strategies can be identified best using mathematical optimization. However, low-carbon technologies impose challenges in solving and assessing the resulting optimization problems.

    Low-carbon technologies are volatile, which increase the complexity of optimal synthesis and operation. To cope with the complexity of operational optimization, we develop a time-series decomposition method. The method decomposes the complex, time-coupled operational problem into smaller subproblems, while still providing feasible, near-optimal solutions. For the increased complexity

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