Journal of Shandong University(Engineering Science) ›› 2018, Vol. 48 ›› Issue (5): 124-130.doi: 10.6040/j.issn.1672-3961.0.2018.172

• Electrical Engineering • Previous Articles     Next Articles

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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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

CLC Number: 

  • TM61

Fig.1

The schematic diagram of virtual measurement sites in study area"

Table 1

Parameters of the virtual wind generation system"

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

Table 2

Parameters of the virtual photovoltaic generation system"

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

Table 3

Wind resource reserve and variability of Zaozhuang region"

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

Table 4

Solar resource reserve and variability of Zaozhuang region"

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

Table 5

Wind-solar complementary features of Zaozhuang region"

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

Fig.2

The schematic diagram of wind generation resource variability in different time scales"

Fig.3

The schematic diagram of solar generation resource variability in different time scales"

Table 6

Wind generation resource variability in different time scales"

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

Table 7

Solar generation resources variability in different time scales"

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

Table 8

Complementary features of areal wind resources and solar resources of sub-area S5 in different time scales"

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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