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Robust network data envelopment analysis approach to evaluate the efficiency of regional electricity power networks under uncertainty

机译:不确定条件下鲁棒网络数据包络分析方法评估区域电网效率

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摘要

In this paper, new Network Data Envelopment Analysis (NDEA) models are developed to evaluate the efficiency of regional electricity power networks. The primary objective of this paper is to consider perturbation in data and develop new NDEA models based on the adaptation of robust optimization methodology. Furthermore, in this paper, the efficiency of the entire networks of electricity power, involving generation, transmission and distribution stages is measured. While DEA has been widely used to evaluate the efficiency of the components of electricity power networks during the past two decades, there is no study to evaluate the efficiency of the electricity power networks as a whole. The proposed models are applied to evaluate the efficiency of 16 regional electricity power networks in Iran and the effect of data uncertainty is also investigated. The results are compared with the traditional network DEA and parametric SFA methods. Validity and verification of the proposed models are also investigated. The preliminary results indicate that the proposed models were more reliable than the traditional Network DEA model.
机译:本文中,开发了新的网络数据包络分析(NDEA)模型来评估区域电力网络的效率。本文的主要目的是考虑数据的扰动,并基于适应性强的优化方法开发新的NDEA模型。此外,在本文中,对涉及发电,输电和配电阶段的整个电力网络的效率进行了测量。尽管在过去的二十年中,DEA已被广泛用于评估电力网络各组件的效率,但尚无研究评估电力网络的整体效率。提出的模型用于评估伊朗16个区域电力网络的效率,并研究了数据不确定性的影响。将结果与传统的网络DEA和参数SFA方法进行了比较。还对所提出模型的有效性和验证性进行了研究。初步结果表明,所提出的模型比传统的网络DEA模型更可靠。

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