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山东大学学报 (工学版) ›› 2018, Vol. 48 ›› Issue (5): 124-130.doi: 10.6040/j.issn.1672-3961.0.2018.172

• 电气工程 • 上一篇    下一篇

基于连续小波变换的风光发电资源多尺度评估

王飞1(),宋士瞻2,曹永吉3,*(),谢红涛1,张新华1,张健2,肖天3,赵雅文3   

  1. 1. 国网山东省电力公司, 山东 济南 250001
    2. 国网山东省电力公司枣庄供电公司, 山东 枣庄 277100
    3. 电网智能化调度与控制教育部重点实验室(山东大学), 山东 济南 250061
  • 收稿日期:2018-05-04 出版日期:2018-10-01 发布日期:2018-05-04
  • 通讯作者: 曹永吉 E-mail:wf6102@163.com;caoyongji1991@163.com
  • 作者简介:王飞(1982—),男,山东济南人,高级工程师,主要研究方向为电网规划和新能源发电技术. E-mail: wf6102@163.com
  • 基金资助:
    国网山东省电力公司科技资助项目(2017A18)

Multi-scale assessment of wind-solar generation resources based on continuous wavelet transform

Fei WANG1(),Shizhan SONG2,Yongji CAO3,*(),Hongtao XIE1,Xinhua ZHANG1,Jian ZHANG2,Tian XIAO3,Yawen ZHAO3   

  1. 1. State Grid Shandong Electric Power Company, Jinan 250001, Shandong, China
    2. Zaozhuang Power Supply Company, State Grid Shandong Electric Power Company, Zaozhuang 277100, Shandong, China
    3. Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education (Shandong University), Jinan 250061, Shandong, China
  • Received:2018-05-04 Online:2018-10-01 Published:2018-05-04
  • Contact: Yongji CAO E-mail:wf6102@163.com;caoyongji1991@163.com
  • Supported by:
    国网山东省电力公司科技资助项目(2017A18)

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摘要：

针对区域风光发电资源评估问题,提出一种基于连续小波变换的多尺度评估方法。从美国国家航空航天局(National Aeronautics and Space Administration, NASA)中获取风速和光照强度再分析数据,并利用虚拟发电系统模型预处理为发电容量系数。综合考虑储量、波动性和互补性等资源属性,构建量化指标对区域风光发电资源进行分析,以时间和空间两个角度挖掘区域资源的分布特征。利用连续小波变换方法提取不同尺度上的风光波动性和互补性特征,评估风光互补发电对出力波动的平抑作用,并探究最佳的互补尺度。以枣庄市为例,对提出方法的有效性进行验证。算例分析表明:风光资源具有波动性和互补性,在最佳尺度上规划互补发电系统能够有效平抑功率波动。

关键词: 风光发电, 资源评估, NASA, 时空分布, 波动性, 互补性, 连续小波变换

Abstract:

Taken into account the assessment of areal wind and solar generation resources, a multi-scale assessment approach using the continuous wavelet transform was proposed. Based on the National Aeronautics and Space Administration (NASA), the wind speed and solar irradiation data were obtained and then preprocessed into capacity factors via virtual generation systems. From the viewpoint of time and space, the quantitative indices of energy potential, variability and complementarity were established to capture the attributes of areal wind and solar resources. The multi-scale variabilities and complementarities were extracted by the continuous wavelet transform to analyze the damping effect on output power and estimate the optimal scale. Zaozhuang City was taken as a case study to validate the effectiveness of proposed approach, of which the results indicated that there were inherent variability and complementary characteristics of wind and solar resources and the reasonable planning of hybrid generation systems in optimal scale could damp the power fluctuation.

Key words: wind and solar generation, resource assessment, NASA, space-time distribution, variability, complementarity, continuous wavelet transform

中图分类号: 

  • TM61

图1

研究地区虚拟观测点分布情况示意图"

表1

虚拟风力发电系统参数"

轮毂高度/
m		 额定功率/
kW		 切入风速/
(m·s-1)		 切出风速/
(m·s-1)		 额定风速/
(m·s-1)		 转换效率/
%
65 850 3.0 13.5 25.0 95.00

表2

虚拟光伏发电系统参数"

额定功率/W 开路电压/V 短路电流/A 模块尺寸/mm 转换效率/%
255 38.0 8.9 1650×992×35 12.48

表3

枣庄地区风电资源储量和波动性"

虚拟观测点序号 风电出力均值uw 风电非零出力概率Pro, w 风电变异系数Vw
S1 0.233 5 0.818 6 1.108 7
S2 0.228 0 0.819 9 1.106 7
S3 0.238 4 0.823 5 1.110 1
S4 0.245 3 0.818 8 1.114 4
S5 0.234 9 0.817 5 1.108 9
S6 0.243 6 0.824 2 1.121 0
S7 0.255 3 0.818 8 1.105 4
S8 0.244 6 0.812 1 1.094 5
S9 0.247 8 0.817 3 1.109 3

表4

枣庄地区光伏资源储量和波动性"

虚拟观测点序号 光伏出力均值uf 光伏非零出力概率Pro, f 光伏变异系数Vf
S1 0.127 0 0.543 2 0.712 6
S2 0.127 8 0.543 4 0.711 8
S3 0.127 2 0.543 4 0.706 8
S4 0.127 6 0.543 3 0.714 5
S5 0.129 2 0.543 4 0.711 8
S6 0.129 9 0.543 5 0.709 8
S7 0.126 8 0.543 4 0.715 2
S8 0.127 3 0.543 5 0.714 8
S9 0.127 9 0.543 5 0.714 0

表5

枣庄地区风光发电资源间的互补性"

虚拟观测点序号 变异平抑系数Cv
S1 0.323 1
S2 0.311 4
S3 0.306 5
S4 0.330 2
S5 0.315 0
S6 0.322 7
S7 0.326 0
S8 0.311 0
S9 0.322 8

图2

风电资源不同时间尺度的波动性示意图"

图3

光伏资源不同时间尺度的波动性示意图"

表6

风电资源不同时间尺度的波动性"

虚拟观测点序号 风电12 h尺度波动系数Gw 风电6 h尺度波动系数Gw 风电1 h尺度波动系数Gw
S1 805.435 4 267.618 2 0.073 8
S2 569.496 6 241.433 3 0.065 1
S3 616.634 4 232.294 6 0.077 4
S4 981.034 2 305.547 2 0.101 0
S5 701.500 3 278.767 0 0.065 9
S6 662.407 5 290.498 1 0.082 0
S7 1 337.753 7 339.686 1 0.093 1
S8 1 083.062 6 290.165 4 0.087 4
S9 915.765 0 292.197 3 0.078 0

表7

光伏资源不同时间尺度的波动性"

虚拟观测点序号 光伏12 h尺度波动系数Gf 光伏6 h尺度波动系数Gf 光伏1 h尺度波动系数Gf
S1 23 817.507 8 5 259.121 1 0.092 5
S2 24 130.025 4 5 350.986 3 0.091 6
S3 24 027.246 1 5 400.227 1 0.118 9
S4 24 014.234 4 5 255.398 4 0.100 0
S5 24 668.632 8 5 409.656 3 0.108 9
S6 24 944.914 1 5 522.150 9 0.084 2
S7 23 749.951 2 5 147.780 8 0.086 2
S8 23 901.509 8 5 188.373 0 0.073 2
S9 24 136.068 4 5 250.260 7 0.071 0

表8

枣庄地区风电与子区域S5光伏资源不同时间尺度的互补性"

虚拟观测点序号 12 h尺度波动平抑系数Cg 6 h尺度波动平抑系数Cg 1 h尺度波动平抑系数Cg
S1 0.119 3 0.501 4 0.421 2
S2 0.171 1 0.475 8 0.349 2
S3 0.245 7 0.458 3 0.355 0
S4 0.121 2 0.538 5 0.444 2
S5 0.160 6 0.509 9 0.413 4
S6 0.206 8 0.494 0 0.324 7
S7 0.110 1 0.553 6 0.403 3
S8 0.126 9 0.502 5 0.400 6
S9 0.155 2 0.472 3 0.422 1
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[1] 刘晓明,牛新生,张怡,曹本庆,施啸寒,张友泉,张杰,安鹏,汪湲. 基于NASA观测数据的风电出力时空分布及波动特性分析[J]. 山东大学学报(工学版), 2016, 46(4): 111-116.
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