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所属单位：南京航空航天大学经济与管理学院

教研室：管理科学与工程

发表刊物：Grey Systems: Theory and Application

关键字：Electricity consumption; Seasonal grey prediction modeling; Grey buffer operator; Long timescale flexibility analysis

摘要：Purpose – Accurate prediction of seasonal power consumption trends with impact disturbances provides a scientific basis for the flexible balance of the long timescale power system. Consequently, it fosters reasonable scheduling plans, ensuring the safety of the system and improving the economic dispatching efficiency of the power system.
Design/methodology/approach – First, a new seasonal grey buffer operator in the longitudinal and transverse dimensional perspectives is designed. Then, a new seasonal grey modeling approach that integrates the new operator, full real domain fractional order accumulation generation technique, grey prediction modeling tool and fruit fly optimization algorithm is proposed. Moreover, the rationality, scientific and superiority of the new approach are verified by designing 24 seasonal electricity consumption forecasting approaches, incorporating case study and amalgamating qualitative and quantitative research.
Findings – Compared with other comparative models, the new approach has superior mean absolute percentage error and mean absolute error. Furthermore, the research results show that the new method provides a scientific and effective mathematical method for solving the seasonal trend power consumption forecasting modeling with impact disturbance.
Originality/value – Considering the development trend of longitudinal and transverse dimensions of seasonal data with impact disturbance and the differences in each stage, a new grey buffer operator is constructed, and a new seasonal grey modeling approach with multi-method fusion is proposed to solve the seasonal power consumption forecasting problem.

论文类型：期刊论文

学科门类：管理学

文献类型：J

卷号：14

期号：2

页面范围：414-428

是否译文：否

发表时间：2024-02-28

收录刊物：SCI

合写作者：Yatng Ren,Bo Zeng,Jamshed Khalid

通讯作者：Xiaoyi Gou