Power User Load Response Potential Assessment under Fuzzy-Rough Environment

doi:10.11930/j.issn.1004-9649.202212066

Abstract

Abstract:

In-depth exploration of user load adjustment potential is an urgent need for the refined development of the national power market. To effectively perceive the comprehensive load response potential of power users, a hybrid assessment model in fuzzy-rough environment is proposed. Firstly, a load response potential evaluation indicator system is constructed from the dimensions of economy, user load characteristics, and information characteristics. Secondly, the fuzzy-rough number is used to process and aggregate the individual linguistic evaluation information, which fully considers the ambiguity of individual judgment and the diversity of group preferences in the evaluation. On this basis, the fuzz-rough entropy weight method and step-wise weight assessment ratio analysis (SWARA) method are combined to determine the comprehensive weight of the indicators; and the improved multi-attributive border approximation area comparison (MABAC) based on rough-fuzzy numbers is adopted to calculate the comprehensive assessment value of the power user’s load response potential for the attribute function, thereby obtaining the potential ranking result. A case study of load response potential evaluation of power users in multiple industries in Nanjing is presented to illustrate the effectiveness of the proposed model.

Key words: power user response potential, fuzzy-rough number, step-wise weight assessment ratio analysis, multi-attributive border approximation area comparison

Chaobo GUO, Yibo ZHANG, Hongjiong ZHANG, Kai MA, Lu CHEN. Power User Load Response Potential Assessment under Fuzzy-Rough Environment[J]. Electric Power, 2023, 56(11): 134-142.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202212066

https://www.electricpower.com.cn/EN/Y2023/V56/I11/134

Figures/Tables 8

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语义变量		模糊标度
very low (VL)		(0, 0, 0.1)
low (L)		(0, 0.1, 0.3)
slightly low (SL)		(0.1, 0.3, 0.5)
medium (M)		(0.3, 0.5, 0.7)
slightly high (SH)		(0.5, 0.7, 0.9)
high (H)		(0.7, 0.9, 1)
very high (VH)		(0.9, 1, 1)

语义变量		模糊标度
very low (VL)		(0, 0, 0.1)
low (L)		(0, 0.1, 0.3)
slightly low (SL)		(0.1, 0.3, 0.5)
medium (M)		(0.3, 0.5, 0.7)
slightly high (SH)		(0.5, 0.7, 0.9)
high (H)		(0.7, 0.9, 1)
very high (VH)		(0.9, 1, 1)

语义变量		模糊标度
equally important (EI)		(1, 1, 1)
moderately less important (MI)		(0.67, 0.8, 1)
less important (LI)		(0.4, 0.5, 9.67)
very less important (VLI)		(0.29, 0.33, 0.4)
much less important (MLI)		(0.22, 0.25, 0.29)

语义变量		模糊标度
equally important (EI)		(1, 1, 1)
moderately less important (MI)		(0.67, 0.8, 1)
less important (LI)		(0.4, 0.5, 9.67)
very less important (VLI)		(0.29, 0.33, 0.4)
much less important (MLI)		(0.22, 0.25, 0.29)

方案	C₁₁	C₁₂	C₂₁	C₂₂	C₂₃	C₂₄	C₃₁	C₃₂	C₄₁	C₄₂	C₄₃
A₁	SL, H, VH, SL	M, M, H, M	SH, H, H, SH	H, H, H, H	M, VH, VH, M	L, M, M, L	H, M, M, H	SH, M, M, SH	VH, H, H, H	M, M, M, M	H, SH, H, H
A₂	L, SH, VL, VL	M, H, H, M	L, M, VH, L	H, M, H, H	M, H, H, H	M, L, L, M	M, H, H, M	H, M, M, H	M, M, SH, SH	VH, VH, VH, H	M, SL, SH, M
A₃	M, SH, SH, M	VH, M, M, VH	M, M, SL, M	H, M, M, SL	M, VH, VH, M	M, M, M, M	SH, H, H, SH	H, H, H, H	SL, SL, M, M	M, M, M, M	SL, M, SL, SL
A₄	M, H, H, M	M, M, H, H	M, H, H, M	H, H, H, H	H, H, H, H	M, M, M, L	SH, M, M, SH	H, M, M, H	VH, VH, H, VH	SL, M, SL, SL	H, VH, VH, VH
A₅	VH, VH, H, H	VH, VH, VH, VH	VL, VL, VL, VL	VL, VL, SL, VL	VL, L, L, VL	VL, VL, VL, VL	VH, VH, VH, VH	VL, H, H, VL	H, VH, M, M	SL, M, M, M	M, M, M, M
A₆	H, H, VH, VH	M, H, H, M	SL, H, H, H	VL, H, H, VL	M, H, VH, M	L, VH, SH, SL	VH, M, VH, VH	VL, VH, VH, VL	VH, VH, H, VH	H, H, VH, H	VH, H, VH, VH