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Ant Colony Optimization for Optimized Operation Scheduling of Combined Heat and Power Plants

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11454))

Abstract

In the worldwide expansion of renewable energies, there is not only a need for weather-dependent plants, but also for plants with flexible power generation that have the potential to reduce storage requirements by working against fluctuations. A highly promising technology is provided by Combined heat and power (CHP) plants, which achieve high efficiencies through the simultaneous generation of electricity and heat. This is why they are also being promoted by the European Union. Also, the construction of biogas plants is usually linked to the construction of CHP plants in order to generate energy from the emission-free produced biogas. However, until now CHP plants have mostly been operated by heat demand (just like boilers), causing the generated electricity often to put additional stress on the power grid. The planning of a CHP plant, whose generated heat always finds a consumer and the generated electricity is simultaneously optimized with regard to an optimization objective, requires nonlinear optimization approaches due to the physical effects in the heat storage. This paper presents a methodology for optimized planning of CHP plants using Ant Colony Optimization. The selected optimization objectives are the power exchange, the tenant electricity and CO\(_2\). It could be shown that all optimizations are at least 10% better than the heat-led operation. The best results were achieved with the electricity exchange optimization that can be up to 24% more profitable than a CHP in a heat-led mode.

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Mast, J., Rädle, S., Gerlach, J., Bringmann, O. (2019). Ant Colony Optimization for Optimized Operation Scheduling of Combined Heat and Power Plants. In: Kaufmann, P., Castillo, P. (eds) Applications of Evolutionary Computation. EvoApplications 2019. Lecture Notes in Computer Science(), vol 11454. Springer, Cham. https://doi.org/10.1007/978-3-030-16692-2_7

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  • DOI: https://doi.org/10.1007/978-3-030-16692-2_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-16691-5

  • Online ISBN: 978-3-030-16692-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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