中国电力 ›› 2023, Vol. 56 ›› Issue (11): 134-142.DOI: 10.11930/j.issn.1004-9649.202212066
郭朝波1(
), 张溢波1(), 张宏炯1(), 马凯2, 陈璐3
收稿日期:2022-12-19
出版日期:2023-11-28
发布日期:2023-11-28
作者简介:郭朝波（1989—），男，工程师，从事市场营销、综合能源服务研究，E-mail： 447801933@qq.com基金资助:
Chaobo GUO1(), Yibo ZHANG1(), Hongjiong ZHANG1(), Kai MA2, Lu CHEN3
Received:2022-12-19
Online:2023-11-28
Published:2023-11-28
Supported by:摘要：
深度探索用户负荷可调节潜力是国家电力市场精细化发展的迫切需求。为有效感知电力用户负荷综合响应潜力，提出一种模糊粗糙环境下的混合评估模型。首先，从经济性、用户特性、负荷特性、信息特性等4个维度构建负荷响应潜力指标体系；其次，充分考虑评估中个体判断的模糊性和群体偏好的多样性，采用模糊粗糙数对个体语义评估信息进行处理和集结；然后，将模糊粗糙熵权法和逐步加权评估比率分析法（step-wise weight assessment ratio analysis，SWARA）相结合确定指标综合权重，并采用基于模糊粗糙数的改进多属性边界逼近区域比较法（multi-attributive border approximation area comparison，MABAC）计算电力用户针对属性函数的负荷响应潜力综合评估值，从而获取潜力排序结果；最后，以多个行业的电力用户负荷综合响应潜力评估为例，验证所提模型的有效性。
郭朝波, 张溢波, 张宏炯, 马凯, 陈璐. 粗糙模糊环境下电力用户负荷响应潜力评估[J]. 中国电力, 2023, 56(11): 134-142.
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.
图 1 电力用户负荷响应潜力评估框架
Fig.1 Evaluation framework of load response potential of power users
| 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) |
表 1 评估方案的语义变量及对应模糊标度
Table 1 Semantic variables and corresponding fuzzy scales of evaluation schemes
| 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) |
表 2 评估指标重要性的语义变量及对应模糊标度
Table 2 Semantic variables and corresponding fuzzy scales for evaluating the importance of indicators
| 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 |
表 3 6个电力用户方案针对每个指标性能的语义评估信息
Table 3 Semantic evaluation information of six power users for each index performance
| 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 |
图 2 针对A2-C43的专家模糊偏好到模糊粗糙序列的转化
Fig.2 Transformation from expert fuzzy preference to fuzzy rough sequence for A2-C43
| 指标 | D1 | D2 | D3 | D4 | 模糊粗糙数 | 清晰值 | ||||||
| C11 | EI | MI | EI | EI | [{0.854, 0.979}, {0.913, 0.988}, {1, 1}] | 0.9367 | ||||||
| C12 | MI | EI | EI | EI | [{0.854, 0.979}, {0.913, 0.988}, {1, 1}] | 0.9367 | ||||||
| C21 | MI | LI | VLI | LI | [{0.362, 0.521}, {0.439, 0.633}, {0.560, 0.810}] | 0.4536 | ||||||
| C22 | LI | MI | MI | EI | [{0.560, 0.810}, {0.669, 0.877}, {0.840, 0.979}] | 0.7532 | ||||||
| C23 | LI | LI | VLI | VLI | [{0.314, 0.371}, {0.375, 0.458}, {0.467, 0.600}] | 0.3350 | ||||||
| C24 | VLI | MI | MLI | VLI | [{0.279, 0.464}, {0.335, 0.552}, {0.414, 0.680}] | 0.3243 | ||||||
| C31 | MI | MI | EI | EI | [{0.750, 0.917}, {0.850, 0.950}, {1, 1}] | 0.8848 | ||||||
| C32 | EI | MI | EI | MI | [{0.750, 0.917}, {0.850, 0.950}, {1, 1}] | 0.8848 | ||||||
| C41 | LI | VLI | MI | LI | [{0.362, 0.521}, {0.451, 0.633}, {0.591, 0.810}] | 0.4636 | ||||||
| C42 | LI | MLI | LI | VLI | [{0.283, 0.372}, {0.333, 0.460}, {0.410, 0.604}] | 0.2960 | ||||||
| C43 | VLI | MLI | VLI | LI | [{0.262, 0.337}, {0.304, 0.408}, {0.362, 0.521}] | 0.2624 |
表 4 指标重要性语义评估和集成的模糊粗糙信息
Table 4 Fuzzy rough information for semantic evaluation and integration of indicator importance
| 指标 | D1 | D2 | D3 | D4 | 模糊粗糙数 | 清晰值 | ||||||
| C11 | EI | MI | EI | EI | [{0.854, 0.979}, {0.913, 0.988}, {1, 1}] | 0.9367 | ||||||
| C12 | MI | EI | EI | EI | [{0.854, 0.979}, {0.913, 0.988}, {1, 1}] | 0.9367 | ||||||
| C21 | MI | LI | VLI | LI | [{0.362, 0.521}, {0.439, 0.633}, {0.560, 0.810}] | 0.4536 | ||||||
| C22 | LI | MI | MI | EI | [{0.560, 0.810}, {0.669, 0.877}, {0.840, 0.979}] | 0.7532 | ||||||
| C23 | LI | LI | VLI | VLI | [{0.314, 0.371}, {0.375, 0.458}, {0.467, 0.600}] | 0.3350 | ||||||
| C24 | VLI | MI | MLI | VLI | [{0.279, 0.464}, {0.335, 0.552}, {0.414, 0.680}] | 0.3243 | ||||||
| C31 | MI | MI | EI | EI | [{0.750, 0.917}, {0.850, 0.950}, {1, 1}] | 0.8848 | ||||||
| C32 | EI | MI | EI | MI | [{0.750, 0.917}, {0.850, 0.950}, {1, 1}] | 0.8848 | ||||||
| C41 | LI | VLI | MI | LI | [{0.362, 0.521}, {0.451, 0.633}, {0.591, 0.810}] | 0.4636 | ||||||
| C42 | LI | MLI | LI | VLI | [{0.283, 0.372}, {0.333, 0.460}, {0.410, 0.604}] | 0.2960 | ||||||
| C43 | VLI | MLI | VLI | LI | [{0.262, 0.337}, {0.304, 0.408}, {0.362, 0.521}] | 0.2624 |
图 3 指标综合权重
Fig.3 Comprehensive weight of indicators
| 方案 | | | 排序 | |||
| A1 | [{–0.3473, –0.0310}, {0.1789, 0.4892}, {0.5660, 0.8806}] | –0.0419 | 3 | |||
| A2 | [{–0.3856, 0.0125}, {0.1609, 0.5248}, {0.5461, 0.8949}] | –0.0185 | 1 | |||
| A3 | [{–0.4490, –0.1527}, {0.1021, 0.3712}, {0.4895, 0.7739}] | –0.2026 | 5 | |||
| A4 | [{–0.3355, –0.0328}, {0.2229, 0.4933}, {0.5992, 0.8757}] | –0.0246 | 2 | |||
| A5 | [{–0.6520, –0.4093}, {–0.2434, –0.0223}, {0.0823, 0.3324}] | –0.6520 | 6 | |||
| A6 | [{–0.4244, –0.0006}, {0.0580, 0.4626}, {0.3970, 0.7958}] | –0.1389 | 4 |
表 5 各电力用户针对指标函数的最终评估值和负荷响应潜力排序结果
Table 5 Ranking results of final evaluation value and load response potential of each power user for index function
| 方案 | | | 排序 | |||
| A1 | [{–0.3473, –0.0310}, {0.1789, 0.4892}, {0.5660, 0.8806}] | –0.0419 | 3 | |||
| A2 | [{–0.3856, 0.0125}, {0.1609, 0.5248}, {0.5461, 0.8949}] | –0.0185 | 1 | |||
| A3 | [{–0.4490, –0.1527}, {0.1021, 0.3712}, {0.4895, 0.7739}] | –0.2026 | 5 | |||
| A4 | [{–0.3355, –0.0328}, {0.2229, 0.4933}, {0.5992, 0.8757}] | –0.0246 | 2 | |||
| A5 | [{–0.6520, –0.4093}, {–0.2434, –0.0223}, {0.0823, 0.3324}] | –0.6520 | 6 | |||
| A6 | [{–0.4244, –0.0006}, {0.0580, 0.4626}, {0.3970, 0.7958}] | –0.1389 | 4 |
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