基于TOPSIS法的风速概率分布评价方法

蒋晨; 缪书唯

doi:10.19912/j.0254-0096.tynxb.2022-0651

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太阳能学报 ›› 2023, Vol. 44 ›› Issue (8) : 499-508. DOI: 10.19912/j.0254-0096.tynxb.2022-0651

基于TOPSIS法的风速概率分布评价方法

蒋晨, 缪书唯

作者信息 +

EVALUATION METHOD FOR WIND SPEED PROBABILITY DISTRIBUTION BASED ON TOPSIS METHOD

Jiang Chen, Miao Shuwei

Author information +

文章历史 +

摘要

将风速概率分布评价视为多属性决策问题,基于逼近理想解排序法（TOPSIS）评价各类候选概率分布拟合风速概率分布的优度。首先,将候选概率分布和拟合优度指标分别类比为方案和属性;其次,根据相对贴近度量化候选概率分布与正理想解的差距,进而在计及指标冲突的情况下评价风速概率分布;最后,收集美国某两处观测站实测风速数据验证所述方法的适用性和准确性,结果表明：该方法能有效整合多种拟合优度指标,进而在不同风况下为特定观测站评价风速概率分布。

Abstract

This paper considers the evaluation of WSPD as a multi-attribute decision making problem, the Technique for Order Preference by Similarity to Ideal Solution （TOPSIS） method is employed to assess the performance of all candidate probability distributions for fitting WSPD. Firstly, each candidate probability distribution and its fitting performance metrics are deemed as each scheme and its attributes, respectively. Secondly, the magnitude of difference between candidate probability distribution and positive ideal solution is quantified by the relative closeness, which enables the evaluation of WSPD considering the conflicts of multiple fitting performance metrics; Finally, the measured wind speed data from two observatories at U.S. are collected to verify the suitability and accuracy of the mentioned method. The results show that the mentioned method can integrate multiple fitting performance metrics and evaluate WSPD for specific observatory under different wind regimes.

导出引用

蒋晨, 缪书唯. 基于TOPSIS法的风速概率分布评价方法[J]. 太阳能学报. 2023, 44(8): 499-508 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0651

Jiang Chen, Miao Shuwei. EVALUATION METHOD FOR WIND SPEED PROBABILITY DISTRIBUTION BASED ON TOPSIS METHOD[J]. Acta Energiae Solaris Sinica. 2023, 44(8): 499-508 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0651

中图分类号： TK81

参考文献

[1] 国家能源局. 国家能源局2022年一季度网上新闻发布会文字实录[EB/OL]. [2022-06-18]. http://www.nea.gov.cn/2022-01/28/c_1310445390.htm.
[2] 国务院. 国务院关于印发2030年前碳达峰行动方案的通知[EB/OL]. [2022-06-18]. http://www.gov.cn/zhengce/content/2021-10/26/content_5644984.htm.
[3] 潘晓春. 风速概率分布参数估计的低阶概率权重矩法[J]. 中国电机工程学报, 2012, 32(5): 131-136.
PAN X C.Low-order probability-weighted moments method for wind speed probability distribution parameter estimation[J]. Proceedings of the CSEE, 2012, 32(5): 131-136.
[4] 周齐, 王海云, 王维庆. 基于峰型辨识的风速概率分布建模[J]. 太阳能学报, 2021, 42(8): 355-360.
ZHOU Q, WANG H Y, WANG W Q.Modeling of wind speed probability distribution based on peak pattern identification[J]. Acta energiae solaris sinica, 2021, 42(8): 355-360.
[5] 缪书唯, 蒋晨, 李丹, 等. 基于互转换Ornstein-Uhlenbeck过程的风速仿真模型及应用[J]. 电力系统自动化, 2022, 46(3): 75-84.
MIAO S W, JIANG C, LI D, et al.Wind speed simulation model and application based on mutual conversion based Ornstein-Uhlenbeck process[J]. Automation of electric power systems, 2022, 46(3): 75-84.
[6] 张雪寒, 余涛. 计及风速与负荷相关性的电-气互联系统概率可靠性评估方法[J]. 高电压技术, 2019, 45(10): 3263-3272.
ZHANG X H, YU T.Probabilistic reliability evaluation method of electricity-gas integrated energy system considering correlation of wind speeds and loads[J]. High voltage engineering, 2019, 45(10): 3263-3272.
[7] 杜刚, 赵冬梅, 刘鑫. 计及风电不确定性优化调度研究综述[J]. 中国电机工程学报, 2023, 43(7): 2608-2626.
DU G, ZHAO D M, LIU X.Research review on optimal scheduling considering wind power uncertainty[J]. Proceedings of the CSEE, 2023, 43(7): 2608-2626.
[8] 王文新, 陈可欣, 白杨, 等. 基于实测数据的呼和浩特近郊风速分布模型对比研究[J]. 太阳能学报, 2021, 42(9): 370-376.
WANG W X, CHEN K X, BAI Y, et al.Comparative study on wind speed distribution models of hohhot suburb based on measured data[J]. Acta energiae solaris sinica, 2021, 42(9): 370-376.
[9] JUNG C, SCHINDLER D.Wind speed distribution selection-a review of recent development and progress[J]. Renewable and sustainable energy reviews, 2019, 114: 109290.
[10] MASSERAN N.Integrated approach for the determination of an accurate wind-speed distribution model[J]. Energy conversion and management, 2018, 173: 56-64.
[11] JUNG C, SCHINDLER D, LAIBLE J, et al.Introducing a system of wind speed distributions for modeling properties of wind speed regimes around the world[J]. Energy conversion and management, 2017, 144: 181-192.
[12] MIAO S W, GU Y Z, LI D, et al.Determining suitable region wind speed probability distribution using optimal score-radar map[J]. Energy conversion and management, 2019, 183: 590-603.
[13] SUMAIR M, AIZED T, BHUTTA M M A, et al. Method of four moments mixture-a new approach for parametric estimation of weibull probability distribution for wind potential estimation applications[J]. Renewable energy, 2022, 191: 291-304.
[14] LUO H S, LI L J, ZHANG Y K, et al.Link prediction in multiplex networks using a novel multiple-attribute decision-making approach[J]. Knowledge-based systems, 2021, 219: 106904.
[15] 吕志鹏, 吴鸣, 宋振浩, 等. 电能质量CRITIC-TOPSIS综合评价方法[J]. 电机与控制学报, 2020, 24(1): 137-144.
LYU Z P, WU M, SONG Z H, et al.Comprehensive evaluation of power quality on CRITIC-TOPSIS method[J]. Electric machines and control, 2020, 24(1): 137-144.
[16] 刘国丹, 纪铱行, 滕润, 等. 基于熵权法的光热耦合综合能耗的百叶外遮阳控制策略[J]. 太阳能学报, 2022, 43(3): 236-241.
LIU G D, JI Y H, TENG R, et al.Control strategy of outer louver shading considering light-thermal coupling comprehensive energy consumption based on entropy weight method[J]. Acta energiae solaris sinica, 2022, 43(3): 236-241.
[17] 陈继明, 王元皓, 李其莹, 等. 基于低电压穿越能力评价的双馈风电机组风电场无功出力控制[J]. 太阳能学报, 2021, 42(4): 466-472.
CHEN J M, WANG Y H, LI Q Y, et al.Reactive power control strategy of dfig-based wind farm based on low voltage ride through ability evaluation[J]. Acta energiae solaris sinica, 2021, 42(4): 466-472.
[18] 肖白, 刘亚伟, 施永刚, 等. 基于主成分分析的中压配电网供电可靠性评估[J]. 电力自动化设备, 2018, 38(10): 7-12.
XIAO B, LIU Y W, SHI Y G, et al.Power supply reliability assessment of mid-voltage distribution network based on principal component analysis[J]. Electric power automation equipment, 2018, 38(10): 7-12.
[19] 门业堃, 钱梦迪, 于钊, 等. 基于博弈论组合赋权的电力设备供应商模糊综合评价[J] .电力系统保护与控制, 2020, 48(21): 179-186.
MEN Y K, QIAN M D, YU Z, et al.Fuzzy comprehensive evaluation of power equipment suppliers based on game theory and combination weighting[J]. Power system protection and control, 2020, 48(21): 179-186.
[20] 黄远明, 郑伟, 王宣定, 等. 基于马氏距离和密度聚类的电力现货报价模式分析[J]. 电力系统自动化, 2021, 45(13): 102-109.
HUANG Y M, ZHENG W, WANG X D, et al.Analysis of quotation mode for electricity spot market based on mahalanobis distance and density clustering[J]. Automation of electric power systems, 2021, 45(13): 102-109.
[21] MIAO S W, YANG H J, GU Y Z.A wind vector simulation model and its application to adequacy assessment[J]. Energy, 2018, 148: 324-340.