内蒙古光伏开发空间适宜性及减排效益研究

doi:10.12118/j.issn.1000－6060.2023.234

Abstract

Abstract:

As an important photovoltaic (PV) power generation base, the Inner Mongolia Autonomous Region (IMAR), China has seen the problem of blindly constructing PV power stations become more prominent in recent years. It is of great significance to grasp the suitability of regional PV development, power generation potential, and emission reduction benefits for the healthy development of the PV industry. To explore the suitability of PV development in the IMAR and the benefits of emission reduction, this study makes comprehensive use of meteorological, natural geographic, economic, and social data, constructs a comprehensive evaluation index system of PV development suitability in the form of meteorology-terrain-location-vegetation, uses an analytic hierarchy process to determine the weights of the evaluation indexes, and performs a spatially explicit evaluation of the suitability of PV development in the IMAR with the aid of a geographic information system tool to quantitatively assess the potential of PV power generation and emission reduction benefits under different development intensities. The PV power generation potential of the leagues and cities and the demand for electric power are compared. The results are as follows: (1) The suitability of PV development in the western part of the IMAR is greater than that in the central and eastern parts, and the various suitable areas are mainly located in the western Alagxa League and Bayannur City, with particularly suitable areas for PV development accounting for 23.66% of the total area of the IMAR. (2) The IMAR PV power generation potential is enormous, especially for regional development, where 12.57% of it can meet the IMAR 2021 electricity consumption. (3) The distribution of PV power generation potential and electricity demand in the IMAR has strong spatial heterogeneity, and the spatial pattern is characterized by significant features. (4) The energy saving and emission reduction effect of PV power generation in the IMAR is remarkable. Compared with conventional coal-fired thermal power generation, the annual carbon emission reduction is approximately 2.947×10⁹ t if the development of a special suitable area is performed, which is 4.46 times the total carbon emission of the IMAR in 2021 and accounts for 21.20% of China’s total carbon emission in 2021. These results provide scientific references and guiding suggestions for the placement of PV power stations and the healthy development of the PV industry in the IMAR.

Key words: geographic information system, photovoltaic power generation, suitability evaluation, generation potential, emission reduction benefits, Inner Mongolia

XU Wei, LIU Zhenling. Spatial suitability and emission reduction benefits of photovoltaic development in Inner Mongolia[J].Arid Land Geography, 2024, 47(4): 684-694.

Figures/Tables 14

Fig. 1

Fig. 2

Fig. 3

Tab. 1

Tab. 2

Tab. 3

Tab. 4

Fig. 4

Fig. 5

Tab. 5

Tab. 6

Fig. 6

Fig. 7

Tab. 7

References 22

[1]	王利珍, 谭洪卫, 庄智, 等. 基于GIS平台的我国太阳能光伏发电潜力研究[J]. 上海理工大学学报, 2014, 36(5): 491-496.
	[Wang Lizhen, Tan Hongwei, Zhuang Zhi, et al. Evaluation of the photovoltaic solar energy potential in China based on GIS platform[J]. Journal of Shanghai University of Technology, 2014, 36(5): 491-496. ]
[2]	韩梦瑶, 熊焦, 刘卫东. 中国光伏发电的时空分布、竞争格局及减排效益[J]. 自然资源学报. 2022, 37(5): 1338-1351. doi: 10.31497/zrzyxb.20220516
	[Han Mengyao, Xiong Jiao, Liu Weidong. Spatio-temporal distribution, competitive development and emission reduction of China’s photovoltaic power generation[J]. Journal of Natural Resources, 2022, 37(5): 1338-1351. ] doi: 10.31497/zrzyxb.20220516
[3]	Alami Merrouni A, Elwali Elalaoui F, Ghennioui A, et al. A GIS-AHP combination for the sites assessment of large-scale CSP plants with dry and wet cooling systems. Case study: Eastern Morocco[J]. Solar Energy, 2018, 166: 2-12.
[4]	Vrinceanu A, Dumitrascu M, Kucsicsa G. Site suitability for photovoltaic farms and current investment in Romania[J]. Renewable Energy, 2022, 187: 320-330.
[5]	Ruiz H S, Sunarso A, Ibrahim-Bathis K, et al. GIS-AHP multi criteria decision analysis for the optimal location of solar energy plants at indonesia[J]. Energy Reports, 2020, 6: 3249-3263.
[6]	Noorollahi Y, Ghenaatpisheh Senani A, Fadaei A, et al. A framework for GIS-based site selection and technical potential evaluation of PV solar farm using Fuzzy-Boolean logic and AHP multi-criteria decision-making approach[J]. Renewable Energy, 2022, 186: 89-104.
[7]	Hassaan M A, Hassan A, Al-Dashti H. GIS-based suitability analysis for siting solar power plants in Kuwait[J]. The Egyptian Journal of Remote Sensing and Space Science, 2021, 24(3): 453-461.
[8]	Sun L, Jiang Y, Guo Q, et al. A GIS-based multi-criteria decision making method for the potential assessment and suitable sites selection of PV and CSP plants[J]. Resources, Conservation and Recycling, 2021, 168: 105306, doi: 10.1016/j.resconrec.2020.105306.
[9]	刘立程, 孙中孝, 吴锋, 等. 京津冀地区光伏开发空间适宜性及减排效益评估[J]. 地理学报, 2022, 77(3): 665-678. doi: 10.11821/dlxb202203012
	[Liu Licheng, Sun Zhongxiao, Wu Feng, et al. Evaluation of suitability and emission reduction benefits of photovoltaic development in Beijing-Tianjin-Hebei region[J]. Journal of Geography, 2022, 77(3): 665-678. ]
[10]	Yushchenko A, De Bono A, Chatenoux B, et al. GIS-based assessment of photovoltaic (PV) and concentrated solar power (CSP) generation potential in West Africa[J]. Renewale & Sustainable Energy Reviews, 2018, 81: 2088-2103.
[11]	江东, 王娣, 付晶莹, 等. 内蒙古自治区未利用土地可再生能源潜力评估[J]. 科技导报, 2020, 38(11): 60-69. doi: 10.3981/j.issn.1000-7857.2020.11.007
	[Jiang Dong, Wang Di, Fu Jingying, et al. Assessment of potential of renewable energy to be proclaced on unused land in Inner Mongolia Autonomous Region[J]. Science and Technology Herald, 2020, 38(11): 60-69. ]
[12]	Charabi Y, Gastli A. PV site suitability analysis using GIS-based spatial fuzzy multi-criteria evaluation[J]. Renewable Energy, 2011, 36(9): 2554-2561.
[13]	Villacreses G, Martínez-Gómez J, Jijón D, et al. Geolocation of photovoltaic farms using geographic information systems (GIS) with multiple-criteria decision-making (MCDM) methods: Case of the Ecuadorian energy regulation[J]. Energy Reports, 2022, 8: 3526-3548.
[14]	董秋霞, 董樊丽, 耿涌, 等. 碳达峰碳中和背景下内蒙古绿色低碳发展的路径和对策建议[J]. 科学管理研究, 2022, 40(6): 77-83.
	[Dong Qiuxia, Dong Fanli, Geng Yong, et al. The path and countermeasures of green and low-carbon development in Inner Mongolia under the background of carbon peak and neutrality[J]. Science Management Research, 2022, 40(6): 77-83. ]
[15]	Giamalaki M, Tsoutsos T. Sustainable siting of solar power installations in Mediterranean using a GIS/AHP approach[J]. Renewable Energy, 2019, 141: 64-75. doi: 10.1016/j.renene.2019.03.100
[16]	吕玉坤, 杨宇星, 赵伟萍. 低风速环境下光伏组件积灰特性模拟研究[J]. 电源技术, 2021, 45(6): 801-804, 827.
	[Lü Yukun, Yang Yuxing, Zhao Weiping. Ash deposition characteristics of photovoltaic modules under low wind speed numerical simulation[J]. Power Technology, 2021, 45(6): 801-804, 827. ]
[17]	Raza M A, Yousif M, Hassan M, et al. Site suitability for solar and wind energy in developing countries using combination of GIS-AHP: A case study of Pakistan[J]. Renewable Energy, 2023, 206: 180-191.
[18]	Huang T, Wang S, Yang Q, et al. A GIS-based assessment of large-scale PV potential in China[J]. Cleaner Energy for Cleaner Cities, 2018, 152: 1079-1084.
[19]	叶小伟, 乔建芳. 乌兹别克斯坦可再生能源现状及中乌合作建议[J]. 干旱区地理, 2022, 45(4): 1313-1319.
	[Ye Xiaowei, Qiao Jianfang. Current situation of renewable energy in Uzbekistan and suggestions on China-Uzbekistan cooperation[J]. Arid Land Geography, 2022, 45(4): 1313-1319. ]
[20]	Zhao L, Jia K, Liu X, et al. Assessment of land degradation in Inner Mongolia between 2000 and 2020 based on remote sensing data[J]. Geography and Sustainability, 2023, 4(2): 100-111.
[21]	Li X, Mauzerall D L, Bergin M H. Global reduction of solar power generation efficiency due to aerosols and panel soiling[J]. Nature Sustainability, 2020, 3(9): 720-727.
[22]	达成, 张富涛, 钱勇生, 等. 关中平原城市群“交通-产业-环境”耦合协调发展的动态演化特征分析[J]. 干旱区地理, 2022, 45(3): 955-965.
	[Da Cheng, Zhang Futao, Qian Yongsheng, et al. Dynamic evolution characteristics of coordinated development of transportation-industry-environment in Guanzhong Plain urban agglomeration[J]. Arid Land Geography, 2022, 45(3): 955-965. ]

数据名称	处理方法	数据来源
整体水平辐照	多年平均值	Global Solar Atl-as2.0
归一化植被指数	2012—2022年平均值	美国航空航天局发布的MODISMOD13A1产品
土地利用类型	按照用地类型把研究区域划分为限制区和非限制区2类，并剔除限制区	全球地表覆盖数据库Globeland30（2020版）
气温	采用Anusplin插值软件进行空间插值	中国气象科学数据共享服务网
降水量、风速、日照时数	借助ArcMap 10.8软件采用Kriging法进行空间插值	中国气象科学数据共享服务网
道路、居民点、保护区、河流	欧氏距离分析	全国基础地理数据库
数字高程模型	生成坡度和坡向数据	地理空间数据云平台

参数	设定依据	参数值
AF（接受太阳辐射的面积因子）	Zhao等^[20]	0.35
ASR（单位面积受到的年太阳辐射量）	平均太阳辐射量	1421.8575
PE（光伏板的发电效率）	多晶硅电池板发电转换效率	16.5%
LO（发电量损耗率）	Li等^[21]	7.5%
AP（弃光率）	国家可再生能源中心	4.0%

n	1	2	3	4	5	6
RI	0.00	0.00	0.58	0.90	1.12	1.24
n	7	8	9	10	11	12
RI	1.32	1.41	1.45	1.49	1.51	1.54

目标层	一级指标	权重	二级指标	权重
光伏开发	气象	0.55	太阳辐射量	0.51
			日照时数	0.26
			气温	0.10
			降水量	0.08
			风速	0.05
	地形	0.14	坡度	0.66
	地形	0.14	坡向	0.34
	位置	0.23	道路距离	0.28
			居民点距离	0.50
			河流距离	0.07
			保护区距离	0.15
	植被	0.08	NDVI	1.00

城市	特别适宜区面积	较适宜区面积	适宜区面积	较不适宜区面积	不适宜区面积
阿拉善盟	39438.75	155277.57	27985.94	192.90	0.00
巴彦淖尔市	9395.69	16386.60	283.85	57.91	0.00
包头市	0.00	377.99	631.88	0.00	0.00
赤峰市	1350.10	0.00	1924.86	884.82	82.40
鄂尔多斯市	0.00	7740.21	4484.42	0.00	0.00
呼和浩特市	0.00	0.00	102.25	0.00	0.00
呼伦贝尔市	0.00	0.00	312.45	2698.23	231.62
通辽市	0.00	0.00	173.91	926.48	220.17
乌海市	0.00	85.32	57.91	0.00	0.00
乌兰察布市	0.00	1493.56	3637.92	0.00	0.00
锡林郭勒盟	0.00	4648.07	4110.55	718.69	0.00
兴安盟	0.00	0.00	0.00	332.24	459.46
总面积	50184.54	186009.32	43705.94	5811.27	993.65

Spatial suitability and emission reduction benefits of photovoltaic development in Inner Mongolia

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 14

References 22

Related Articles 15

Metrics

Comments

Recommended 0

开发情景		情景解释	面积/km²	发电潜力/TWh
S1	S1-Q1	特别适宜区开发25%	12546.14	9148.11
	S1-Q2	特别适宜区开发50%	25092.27	18296.20
	S1-Q3	特别适宜区开发75%	37638.41	27444.31
	S1-Q4	特别适宜区开发100%	50184.54	36592.41
S2	S2-Q1	较适宜区开发 25%	46502.33	33907.50
	S2-Q2	较适宜区开发50%	93004.66	67815.00
	S2-Q3	较适宜区开发75%	139506.99	101722.50
	S2-Q4	较适宜区开发100%	186009.32	135630.00
S3	S3-Q1	适宜区开发25%	10926.49	7967.12
	S3-Q2	适宜区开发50%	21852.97	15934.25
	S3-Q3	适宜区开发75%	32779.46	23901.37
	S3-Q4	适宜区开发100%	43705.94	31868.50

开发情景	情景解释	减排效果/t
开发情景	情景解释	标准煤	CO₂	SO₂	NO_x	TSP
S1 S1-Q1	特别适宜区开发25%	2.767×10⁸	7.367×10⁸	6.088×10⁶	2.767×10⁶	4.704×10⁶
S1-Q2	特别适宜区开发50%	5.535×10⁸	1.473×10⁹	1.218×10⁷	5.535×10⁶	9.409×10⁶
S1-Q3	特别适宜区开发75%	8.302×10⁸	2.210×10⁹	1.826×10⁷	8.302×10⁶	1.411×10⁷
S1-Q4	特别适宜区开发100%	1.107×10⁹	2.947×10⁹	2.435×10⁷	1.107×10⁷	1.882×10⁷
S2 S2-Q1	较适宜区开发25%	1.026×10⁹	2.730×10⁹	2.257×10⁷	1.026×10⁷	1.744×10⁷
S2-Q2	较适宜区开发50%	2.051×10⁹	5.461×10⁹	4.513×10⁷	2.051×10⁷	3.487×10⁷
S2-Q3	较适宜区开发75%	3.077×10⁹	8.191×10⁹	6.770×10⁷	3.077×10⁷	5.231×10⁷
S2-Q4	较适宜区开发100%	4.103×10⁹	1.092×10¹⁰	9.026×10⁷	4.103×10⁷	6.975×10⁷
S3 S3-Q1	适宜区开发25%	2.410×10⁸	6.416×10⁸	5.302×10⁶	2.410×10⁶	4.097×10⁶
S3-Q2	适宜区开发50%	4.820×10⁸	1.283×10⁹	1.060×10⁷	4.820×10⁶	8.194×10⁶
S3-Q3	适宜区开发75%	7.230×10⁸	1.925×10⁹	1.591×10⁷	7.230×10⁶	1.229×10⁷
S3-Q4	适宜区开发100%	9.640×10⁸	2.566×10⁹	2.123×10⁷	9.640×10⁶	1.639×10⁷

[1]	NIU Yiying, LI Chunlan, WANG Jun, XU Hanqing, LIU Qing. Performance evaluation of ERA5 reanalysis precipitation data and spatiotemporal characteristics of extreme precipitation in Inner Mongolia [J]. Arid Land Geography, 2023, 46(9): 1418-1431.
[2]	NING Jing, ZHU Ran, ZHANG Xinyuan, CHEN Kai. Evaluation and analysis of urban resilience of districts and counties in Inner Mongolia [J]. Arid Land Geography, 2023, 46(7): 1217-1226.
[3]	SA Rigai, BAO Yuhai, DOU Yinyin, DONG Yulin, PAN Tao, KUANG Wenhui. Impacts of urban and rural construction on ecosystem productivity in Inner Mongolia Plateau from 2000 to 2020 [J]. Arid Land Geography, 2023, 46(6): 922-933.
[4]	PAN Xue, GUAN Yuqi, PAN Zhandong, LIU Jie, CAI Liqun, DONG Bo, DU Jian. Spatiotemporal variation and evaluation of cultivated land quality grade in arid areas: A case of Xining City [J]. Arid Land Geography, 2023, 46(5): 793-803.
[5]	ZHOU Haitao, MA Yusong, FAN Yayu, NING Xiaoli. Spatial distribution and accessibility analysis of red tourism resources in Inner Mongolia [J]. Arid Land Geography, 2023, 46(5): 814-822.
[6]	DONG Youming, QIAO Wenyi, LIU Zemiao, HUANG Xianjin. Characteristics of rural restructuring and problem areas identification in agro-pastoral area of northern China: A case of the Inner Mongolia section in the Yellow River Basin [J]. Arid Land Geography, 2023, 46(11): 1891-1902.
[7]	ZHANG Jianing, YAO Linjie, ZHANG Hengrui, ZHAO Yanyun, ZHANG Qing, LIU Pengtao. Ecological footprint and sustainable utilization of grassland resources in Inner Mongolia [J]. Arid Land Geography, 2022, 45(6): 1988-2003.
[8]	XIE Conghui,WU Shixin,LIN Juan,ZHUANG Qingwei,ZHANG Zihui,HOU Guanyu,LUO Geping. Analysis of cultivated land salinization in Kashgar Oasis based on PSO-PNN model [J]. Arid Land Geography, 2022, 45(5): 1547-1558.
[9]	JIN Ling,WANG Yongfang,GUO Enliang,LIU Guixiang,BAO Yulong. Evaluation of drought hazards in Inner Mongolia based on SPEIbase v.2.6 dataset [J]. Arid Land Geography, 2022, 45(3): 695-705.
[10]	ZHAI Yongguang,ZHANG Xin,JI Honglan,MOU Xianyou,ZHANG Baosen. Ice-water classification in Inner Mongolia reach of the Yellow River based on remote sensing images [J]. Arid Land Geography, 2022, 45(3): 763-773.
[11]	TANG Yuanhang,LI Mengqi,DENG Ling,WANG Xiaoli. Glacier change and its response to climate change in Pumqu Basin during 1990—2020 [J]. Arid Land Geography, 2022, 45(1): 27-36.
[12]	Baoleerqimuge . Variation characteristics of dry spell in desert steppe of Inner Mongolia during 1960—2020 [J]. Arid Land Geography, 2022, 45(1): 46-56.
[13]	XING Lizhu,ZHANG Fangmin,HUANG Jin,LI Yunpeng. Spatial and temporal changes of high wind days over category 6 and above in Inner Mongolia from 1961 to 2018 [J]. Arid Land Geography, 2021, 44(5): 1290-1298.
[14]	JIA Xin,LI Guoqing,WANG Gang,CAO Yu. Effects of wind farms on soil moisture in grassland [J]. Arid Land Geography, 2021, 44(4): 1125-1134.
[15]	LU Zhuoyu,CUI Jianxin,ZHANG Xiaohong,LI Peng. Historical changes reconstruction of Tonghalake Lake in the Mu Us Sandy Land from Qing Dynasty to Republic of China [J]. Arid Land Geography, 2021, 44(4): 1083-1092.