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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
1 刘振亚. 全球能源互联网[M]. 北京: 中国电力出版社, 2015.
2 刘振亚. 中国电力与能源[M]. 北京: 中国电力出版社, 2012.
3 鲁宗相, 黄瀚, 单葆国, 等. 高比例可再生能源电力系统结构形态演化及电力预测展望[J]. 电力系统自动化, 2017, 41 (9): 12- 18.
LU Zongxiang , HUANG Han , SHAN Baoguo , et al. Morphological evolution model and power forecasting prospect of future electric power systems with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2017, 41 (9): 12- 18.
4 张恒旭, 施啸寒, 刘玉田, 等. 我国西北地区可再生能源基地对全球能源互联网构建的支撑作用[J]. 山东大学学报(工学版), 2016, 46 (4): 96- 102.
ZHANG Hengxu , SHI Xiaohan , LIU Yutian , et al. Support of the renewable energy base in northwest of China on the construction of global energy interconnection[J]. Journal of Shandong University (Engineering Science), 2016, 46 (4): 96- 102.
5 李璐, 郑亚先, 陈长升, 等. 风电的波动成本计算及应用研究[J]. 中国电机工程学报, 2016, 36 (19): 5155- 5163.
LI Lu , ZHENG Yaxian , CHEN Changsheng , et al. Calculation of wind power variation costs and its application research[J]. Proceedings of the CSEE, 2016, 36 (19): 5155- 5163.
6 丁明, 王伟胜, 王秀丽, 等. 大规模光伏发电对电力系统影响综述[J]. 中国电机工程学报, 2014, 34 (1): 2- 14.
DING Ming , WANG Weisheng , WANG Xiuli , et al. A review on the effect of large-scale PV generation on power systems[J]. Proceedings of the CSEE, 2014, 34 (1): 2- 14.
7 CAO Y J , ZHANG Y , ZHANG H X , et al. Probabilistic optimal PV capacity planning for wind farm expansion based on NASA data[J]. IEEE Transactions on Sustainable Energy, 2017, 8 (3): 1291- 1300.
doi: 10.1109/TSTE.2017.2677466
8 赵书强, 刘大正, 谢宇琪, 等. 基于相关机会目标规划的风光储联合发电系统储能调度策略[J]. 电力系统自动化, 2015, 39 (14): 30- 36.
doi: 10.7500/AEPS20140920009
ZHAO Shuqiang , LIU Dazheng , XIE Yuqi , et al. Scheduling strategy of energy storage in wind-solar-battery hybrid hybrid power system based on dependent-chance goal programming[J]. Automation of Electric Power Systems, 2015, 39 (14): 30- 36.
doi: 10.7500/AEPS20140920009
9 杨迎超, 刘宏昭, 原大宁, 等. 测风数据处理与风资源评估[J]. 太阳能学报, 2012, 33 (10): 1661- 1666.
doi: 10.3969/j.issn.0254-0096.2012.10.004
YANG Yingchao , LIU Hongzhao , YUAN Daning , et al. Data processing in anemometry and wind resource assessment[J]. Acta Energiae Solaris Sinica, 2012, 33 (10): 1661- 1666.
doi: 10.3969/j.issn.0254-0096.2012.10.004
10 肖创英, 汪宁渤, 陟晶, 等. 甘肃酒泉风电出力特性分析[J]. 电力系统自动化, 2010, 34 (17): 64- 67.
XIAO Chuangying , WANG Ningbo , ZHI Jing , et al. Power characteristics of Jiuquan wind power base[J]. Automation of Electric Power Systems, 2010, 34 (17): 64- 67.
11 李芬, 陈正洪, 成驰, 等. 武汉并网光伏电站性能与气象因子关系研究[J]. 太阳能学报, 2012, 33 (8): 1386- 1391.
doi: 10.3969/j.issn.0254-0096.2012.08.022
LI Fen , CHEN Zhenghong , CHENG Chi , et al. Relationship between performances of grid-connected PV power plant and meteorological factors in Wuhan[J]. Acta Energiae Solaris Sinica, 2012, 33 (8): 1386- 1391.
doi: 10.3969/j.issn.0254-0096.2012.08.022
12 解大, 康建洲. 崇明风力资源分析及风力机组的选择[J]. 电力系统保护与控制, 2009, 37 (24): 65- 70.
XIE Da , KANG Jianzhou . Analysis of Chongming Island wind power and selection of wind turbine unit[J]. Power System Protection and Control, 2009, 37 (24): 65- 70.
13 刘晓明, 牛新生, 张怡, 等. 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.
LIU Xiaoming , NIU Xinsheng , ZHANG Yi , et al. Analysis of spatial and temporal distribution of wind output and variation characteristics based on NASA observation data[J]. Journal of Shandong University (Engineering Science), 2016, 46 (4): 111- 116.
14 OKOYE C O , TAYLAN O , BAKER D K . Solar energy potentials in strategically located cities in Nigeria: review, resource assessment and PV system design[J]. Renewable & Sustainable Energy Reviews, 2016, 55 (3): 550- 566.
15 于大洋, 韩学山, 梁军, 等. 基于NASA地球观测数据库的区域风电功率波动特性分析[J]. 电力系统自动化, 2011, 35 (5): 77- 81.
YU Dayang , HAN Xueshan , LIANG Jun , et al. Study on the profiling of China's regional wind power fluctuation using GEOS-5 Data Assimilation System of National Aeronautics and Space Administration of America[J]. Automation of Electric Power Systems, 2011, 35 (5): 77- 81.
16 MARTINS F R , PEREIRA E B , SILVA S A B , et al. Solar energy scenarios in Brazil: Part one: resource assessment[J]. Energy Policy, 2008, 36 (8): 2853- 2864.
doi: 10.1016/j.enpol.2008.02.014
17 ZHANG H X , CAO Y J , ZHANG Y , et al. Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data[J]. Applied Energy, 2018, 216, 172- 182.
doi: 10.1016/j.apenergy.2018.02.094
18 姜文玲, 王勃, 汪宁渤, 等. 多时空尺度下大型风电基地出力特性研究[J]. 电网技术, 2017, 41 (2): 493- 499.
JIANG Wenling , WANG Bo , WANG Ningbo , et al. Research on power output characteristics of large-scale wind power base in multiple temporal and spatial scales[J]. Power System Technology, 2017, 41 (2): 493- 499.
19 李璐, 郑亚先, 陈长升, 等. 风电的波动成本计算及应用研究[J]. 中国电机工程学报, 2016, 36 (19): 5155- 5163.
LI Lu , ZHENG Yaxian , CHEN Changsheng , et al. Calculation of wind power variation costs and its application research[J]. Proceedings of the CSEE, 2016, 36 (19): 5155- 5163.
20 MONFORTI F , HULD T , BÓDIS K , et al. Assessing complementarity of wind and solar resources for energy production in Italy: a Monte Carlo approach[J]. Renewable Energy, 2014, 63 (1): 576- 586.
21 於益军, 雷为民, 单茂华, 等. 风光储联合发电监控系统功能设计与应用[J]. 电力系统自动化, 2012, 36 (20): 32- 38.
YU Yijun , LEI Weimin , SHAN Maohua , et al. Design and application of supervision and control system for wind-photovoltaic-battery power plants[J]. Automation of Electric Power Systems, 2012, 36 (20): 32- 38.
22 李剑楠, 乔颖, 鲁宗相, 等. 多时空尺度风电统计特性评价指标体系及其应用[J]. 中国电机工程学报, 2013, 33 (13): 53- 61.
LI Jiannan , QIAO Ying , LU Zongxiang , et al. An evaluation index system for wind power statistical characteristics in multiple spatial and temporal scales and its application[J]. Proceedings of the CSEE, 2013, 33 (13): 53- 61.
23 叶林, 屈晓旭, 么艳香, 等. 风光水多能互补发电系统日内时间尺度运行特性分析[J]. 电力系统自动化, 2018, 42 (4): 158- 164.
YE Lin , QU Xiaoxu , YAO Yanxiang , et al. Analysis on intraday operation characteristics of hybrid wind-solar-hydro power generation system[J]. Automation of Electric Power Systems, 2018, 42 (4): 158- 164.
24 ZHANG H , CAO Y , ZHANG Y , et al. Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data[J]. Applied Energy, 2018, 216, 172- 182.
25 HAN J , KAMBER M , PEI J . Data mining: concepts and techniques[M]. Boston, USA: Morgan Kaufmann, 2012.
[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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