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A novel approach for solving multi-objective unit commitment based on decompositioncoordination

机译:基于分解协调的多目标单元承诺求解新方法

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摘要

Multi-objective unit commitment (MOUC) considers simultaneously both economic and environmental objectives, then finds the best trade off with respect to these objectives. This paper proposes a novel model for MOUC, and a decomposition coordination approach is presented to solve the model. The MOUC model considers environmental objective by introducing a novel penalty term, and it's a quantized term for preference of environmental objective, which could be a basis for carbon tax makers. The model is solved by a decomposition coordination approach, which decomposes the whole system into subsystems and performs an iterative process. During each iteration step, the tie-line is updated based on the margin price in connected subsystems, then, each subsystem is solved by Lagrangian relaxation (LR), and the result is improved during iterations as shown in case studies. Besides, as LR does not require uploading units' parameters, it protects the privacy of generating companies. Numerical case studies considering different scenarios, conducted using the proposed multi-objective model, are applied to illustrate the robustness as well as the performance of the approach.
机译:多目标单位承诺(MOUC)同时考虑经济和环境目标,然后找到与这些目标相关的最佳权衡。本文提出了一种新的MOUC模型,并提出了一种分解协调的方法来求解该模型。 MOUC模型通过引入新的惩罚条款来考虑环境目标,它是对环境目标偏好的量化术语,这可能是碳税制定者的基础。该模型通过分解协调方法求解,该方法将整个系统分解为子系统并执行迭代过程。在每个迭代步骤中,根据连接子系统的保证金价格更新联系线,然后通过拉格朗日松弛(LR)解决每个子系统,并在迭代过程中改善结果,如案例研究所示。此外,由于LR不需要上传单位的参数,因此可以保护发电公司的隐私。使用提出的多目标模型进行的考虑不同场景的数值案例研究被用来说明该方法的鲁棒性和性能。

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