地理学报 ›› 2022, Vol. 77 ›› Issue (3): 665-678.doi: 10.11821/dlxb202203012
刘立程1(), 孙中孝1, 吴锋2,3, 张雪靓1, 张倩1(
)
收稿日期:
2021-04-19
修回日期:
2021-12-31
出版日期:
2022-03-25
发布日期:
2022-05-25
通讯作者:
张倩(1981-), 女, 山东兖州人, 副教授, 博士生导师, 研究方向为农业资源环境政策与管理。E-mail: qian. zhang@cau.edu.cn作者简介:
刘立程(1994-), 男, 甘肃民勤人, 博士生, 研究方向为资源与环境政策评估。E-mail: liulicheng@cau.edu.cn
基金资助:
LIU Licheng1(), SUN Zhongxiao1, WU Feng2,3, ZHANG Xueliang1, ZHANG Qian1(
)
Received:
2021-04-19
Revised:
2021-12-31
Published:
2022-03-25
Online:
2022-05-25
Supported by:
摘要:
京津冀地区作为中国重要的能源消费基地,近年在产业转型与发展中对清洁能源的需求不断增加。光伏发电是中国“十四五”期间加速能源结构转型,早日实现碳中和目标的关键举措与重要抓手。本文以京津冀为研究区,通过构建“地形—气象—成本”光伏开发适宜性综合评价指标体系,计算了光伏开发适宜性指数,刻画出京津冀地区2018年光伏开发适宜性的空间格局特征,进而定量评估不同开发适宜性情景下光伏发电潜力与减排效益。研究表明:① 京津冀地区光伏开发适宜区占到区域总面积的22%,一般适宜区面积最广,“燕山—太行山”一线是适宜区与不适宜区的主要分界线,各类适宜区主要分布在承德、张家口和保定市3个市。 ② 京津冀地区光伏发电发展潜力巨大,开发非常适宜区和较适宜区的年发电潜力是2018年京津冀地区电力消耗的3倍。③ 光伏发电节能减排效果显著。在将非常适宜区和较适宜区全部开发情景下碳减排量为京津冀2018年排放量的47%。④ 土地利用限制、大型输电网络和储能系统是制约光伏发展的主要因素。总体来看,虽然大规模光伏开发仍存在一定的限制条件与技术瓶颈,但在全球气候变化加剧和社会经济发展进入“低碳脱碳”新常态的背景下,京津冀地区的大规模光伏开发仍是助力区域早日实现碳中和目标、优化能源结构和提升人民福祉的重要途径。
刘立程, 孙中孝, 吴锋, 张雪靓, 张倩. 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.
LIU Licheng, SUN Zhongxiao, WU Feng, ZHANG Xueliang, ZHANG Qian. Evaluation of suitability and emission reduction benefits of photovoltaic development in Beijing-Tianjin-Hebei region[J]. Acta Geographica Sinica, 2022, 77(3): 665-678.
表1
评价指标数据及其预处理
指标名称 | 处理方法 | 数据来源 |
---|---|---|
年太阳总辐射 | 站点数据Anusplin插值为百米栅格数据 | 中国气象数据网 |
年日照时数 | 站点数据Anusplin插值为百米栅格数据 | 中国气象数据网 |
数字高程模型 | 拼接(Mosaic)后重采样(Resample)为百米栅格数据 | 地理空间数据云 |
坡度 | 采用坡度(Slope)工具计算得到百米栅格数据 | 根据DEM数据计算 |
土地利用类型 | LUCC 100×100 m栅格数据 | 中国科学院资源环境科学与数据中心 |
地貌类型 | 中国1:100万地貌类型重采样(Resample)为百米栅格数据 | 中国科学院资源环境科学与数据中心 |
距城镇距离 | 欧式距离(Euclidean distance)计算得到百米栅格数据 | 国家基础地理信息中心 |
距道路距离 | 欧式距离(Euclidean distance)计算得到百米栅格数据 | 国家基础地理信息中心 |
表4
主成分载荷矩阵
指标 | PC1 | PC2 | PC3 | PC4 | PC5 | PC6 | PC7 | PC8 | 权重(%) |
---|---|---|---|---|---|---|---|---|---|
DFR | 0.49 | 0.15 | 0.78 | -0.31 | -0.10 | -0.07 | -0.01 | 0.01 | 11.36 |
DFC | 0.65 | 0.30 | 0.25 | 0.63 | 0.08 | -0.08 | -0.03 | -0.01 | 12.52 |
DEM | 0.86 | 0.26 | -0.02 | -0.05 | 0.08 | 0.40 | -0.02 | 0.02 | 12.05 |
SLO | 0.82 | 0.46 | -0.03 | -0.05 | 0.25 | -0.07 | 0.03 | 0.18 | 12.73 |
GEO | 0.86 | 0.35 | -0.01 | -0.06 | 0.26 | -0.04 | 0.10 | -0.18 | 12.69 |
STY | 0.57 | 0.63 | 0.01 | 0.15 | -0.48 | 0.06 | -0.05 | -0.02 | 11.97 |
ASH | -0.76 | 0.43 | 0.27 | 0.06 | 0.28 | 0.09 | -0.23 | -0.03 | 13.44 |
ASR | -0.82 | 0.25 | 0.35 | 0.18 | 0.02 | 0.15 | 0.25 | 0.02 | 13.25 |
表6
京津冀不同光伏开发情景下的发电潜力
开发情景 | 情景释义 | 面积(km2) | 发电潜力(亿kWh) | |
---|---|---|---|---|
S1 | S1-Q1 | 非常适宜区开发25% | 1622.59 | 1337.09 |
S1-Q2 | 非常适宜区开发50% | 3245.10 | 2674.17 | |
S1-Q3 | 非常适宜区开发75% | 4867.64 | 4011.26 | |
S1-Q4 | 非常适宜区开发100% | 6490.19 | 5348.34 | |
S2 | S2-Q1 | 较适宜区开发25% | 4011.38 | 3305.64 |
S2-Q2 | 较适宜区开发50% | 8022.76 | 6611.28 | |
S2-Q3 | 较适宜区开发75% | 12034.13 | 9916.91 | |
S2-Q4 | 较适宜区开发100% | 16045.51 | 13222.55 |
表7
不同光伏开发强度下的减排效果
开发情景 | 情景释义 | 减排物(万t) | |||||
---|---|---|---|---|---|---|---|
氮氧化物 | 二氧化硫 | 粉尘 | 标准煤 | 二氧化碳 | |||
S1 | S1-Q1 | 非常适宜区开发25% | 200.56 | 401.12 | 3636.87 | 5348.34 | 13330.74 |
S1-Q2 | 非常适宜区开发50% | 401.12 | 802.25 | 7273.74 | 10696.68 | 26661.47 | |
S1-Q3 | 非常适宜区开发75% | 601.68 | 1203.37 | 10910.61 | 16045.02 | 39992.21 | |
S1-Q4 | 非常适宜区开发100% | 802.25 | 1604.50 | 14547.48 | 21393.36 | 53322.95 | |
S2 | S2-Q1 | 较适宜区开发25% | 495.84 | 991.69 | 8991.33 | 13222.55 | 32957.21 |
S2-Q2 | 较适宜区开发50% | 991.69 | 1983.38 | 17982.67 | 26445.1 | 65914.42 | |
S2-Q3 | 较适宜区开发75% | 1487.53 | 2975.07 | 26974.01 | 39667.66 | 98871.63 | |
S2-Q4 | 较适宜区开发100% | 1983.38 | 3966.76 | 35965.34 | 52890.21 | 131828.8 |
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