Journal of Shanghai Jiaotong University >
Information Gap Decision Theory-Spectrum Clustering Typical Scenario Generation Considering Source Load Uncertainty
Received date: 2023-11-17
Revised date: 2024-02-01
Accepted date: 2024-03-18
Online published: 2024-04-01
The high proportion of new energy and dynamic load brings significant bidirectional uncertainty of source and load to power system. The strong uncertainty makes scheduling planning face high dimensional decision space and increases planning risk. Therefore, an information gap decision theory (IGDT)-spectral clustering typical scenario generation method considering the uncertainty of source load is proposed to provide a more accurate planning scenario for the determination of the operation mode of multi-source joint systems. First, the source load uncertainty can be quantified effectively by the IGDT theory without considering the uncertain quantitative probability distribution. The source load fluctuation range is described using the IGDT robust model and the IGDT chance model, and the original scenario representing each uncertainty situation is generated using the Latin hypercube sampling method to ensure the adequacy and accuracy of sample space. Then, to address the huge scale of the original scenario caused by the uncertainty of the source load, a spectral clustering method considering the adjustment ability of the system is introduced to mine the feature vectors of different source load fluctuations which have an important impact on the scheduling decision to reduce the complex original scenario set to a representative typical scenario of the source load. Finally, the simulation analysis of the actual system and operation data of a provincial power grid shows that compared with the traditional spectral clustering method, the proposed method generates four more typical scenarios after considering the bidirectional uncertainty of source load, the comprehensive average Pearson correlation coefficient is increased by 8.76%, the comprehensive average Euclidian distance is reduced by 43.48%, and the clustering scenario is more similar to the actual scenario.
ZHANG Jiamin , CAI Ye , TANG Xiafei , TAN Yudong , CAO Yijia , LI Junxiong . Information Gap Decision Theory-Spectrum Clustering Typical Scenario Generation Considering Source Load Uncertainty[J]. Journal of Shanghai Jiaotong University, 2025 , 59(11) : 1625 -1636 . DOI: 10.16183/j.cnki.jsjtu.2023.580
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