DOI:10.35833/MPCE.2020.000198 |
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Robust Optimal Operation of Active Distribution Network Based on Minimum Confidence Interval of Distributed Energy Beta Distribution |
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Page view: 114
Net amount: 599 |
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Author:
Yanhong Luo,Qiubo Nie,Dongsheng Yang,Bowen Zhou
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Author Affiliation:
Department of Electric Engineering, Northeastern University, Shenyang 110004, China
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Foundation: |
This work was supported in part by the National Natural Science Foundation of China (No. 61703081), the Liaoning Joint Fund of National Natural Science Foundation of China (No. U1908217), the Natural Science Foundation of Liaoning Province (No. 20170520113), and the Fundamental Research Funds for the Central Universities (No. N2004016). |
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Abstract: |
With the gradual increase of distributed energy penetration, the traditional optimization model of distribution network can no longer guarantee the stable and efficient operation of the distribution network. In order to deal with the inevitable uncertainty of distributed energy, a new robust optimal operation method is proposed for active distribution network (ADN) based on the minimum confidence interval of distributed energy Beta distribution in this paper. First, an ADN model is established with second-order cone to include the energy storage device, capacitor bank, static var compensator, on-load tap changer, wind turbine and photovoltaic. Then, the historical data of related distributed energy are analyzed and described by the probability density function, and the minimum confidence interval is obtained by interval searching. Furthermore, via taking this minimum confidence interval as the uncertain interval, a less conservative two-stage robust optimization model is established and solved for ADN. The simulation results for the IEEE 33-bus distribution network have verified that the proposed method can realize a more stable and efficient operation of the distribution network compared with the traditional robust optimization method. |
Keywords: |
Active distribution network ; robust optimization ; Beta distribution ; second-order cone |
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Received:March 30, 2020
Online Time:2021/03/22 |
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