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AutoMoG: Autoated data-driven Model Generation of multi-energy systems using piecewise-linear regression

机译：Automog：使用分段线性回归的自动数据驱动模型生成多能量系统

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摘要

Operational optimization of multi-energy systems requires a mathematical model that is accurate and computationally efficient. A model can be generated in a data-driven way if measured data is available. Commonly, data is then used to model each component of the multi-energy system independently. However, independent modeling of each component may lead to models that are unnecessarily complicated and, thus, inefficient in practice. In this work, we propose the method AutoMoG for Automated data-driven Model Generation of multi-energy systems using piecewise-linear regression. AutoMoG provides Mixed-Integer Linear Programming models of multi-energy systems. To accurately model the overall multi-energy system, AutoMoG balances the errors caused by each component. Model accuracy is measured in terms of operating cost. In a case study, AutoMoG provides a multi-energy system model with less linear sections than single-component regression Still, AutoMoG retains high accuracy. Thereby, AutoMoG enables efficient data-driven modeling as the basis for multi-energy system optimization.
机译：多能量系统的操作优化需要一种准确和计算效率的数学模型。如果测量数据可用，则可以以数据驱动方式生成模型。通常，然后使用数据来独立地模拟多能量系统的每个组件。然而，每个组件的独立建模可能导致不必要地复杂的模型，从而在实践中效率低下。在这项工作中，我们提出了使用分段线性回归的多能量系统自动数据驱动模型生成的方法。汽车提供多能量系统的混合整数线性编程模型。为了准确地模拟整体多能量系统，AutomoG将余额平衡每个组件引起的错误。模型精度在运营成本方面测量。在一个案例研究中，AutomoG仍然提供了一种多能量系统模型，而不是单组分回归仍然存在较少的线性部分，汽车保留高精度。因此，AutomoG使能有效的数据驱动建模作为多能量系统优化的基础。

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  • 来源
    《Computers & Chemical Engineering》 |2021年第2期|107162.1-107162.12|共12页
  • 作者

    Andreas Kaemper; Ludger Leenders; Bjoern Bahl; Andre Bardow;

  • 作者单位

    Institute of Technical Thermodynamics RWTH Aachen University Aachen 52062 Germany;

    Institute of Technical Thermodynamics RWTH Aachen University Aachen 52062 Germany Energy & Process Engineering Department of Mechanical and Process Engineering ETH Zurich Zurich 8092 Switzerland;

    Institute of Technical Thermodynamics RWTH Aachen University Aachen 52062 Germany;

    Institute of Technical Thermodynamics RWTH Aachen University Aachen 52062 Germany Institute of Energy and Climate Research Energy Systems Engineering (IEK-10) Forschungszentrum Juelich GmbH Juelich 52425 Germany Energy & Process Engineering Department of Mechanical and Process Engineering ETH Zurich Zurich 8092 Switzerland;

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  • 正文语种 eng
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  • 关键词

    Regression analysis; Mixed-integer linear programming; Energy system optimization; Information criterion;

    机译：回归分析;混合整数线性规划;能量系统优化;信息标准;

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