风能开发的土地资源需要区域化表征
Tao Dai1,2, Jeya Maria Jose Valanarasu3, Yifan Zhao4
1School of Advanced International Studies, Johns Hopkins University, Washington, District of Columbia 20036, United States.
Environmental science & technology
|March 4, 2024
概括
精确的风能土地利用估计是至关重要的. 这项研究使用机器学习和地理信息系统来量化土地转型和效率,揭示了风力项目中的人工修饰较少的地区产生更好的结果.
科学领域:
- 环境科学 环境科学
- 可再生能源技术可再生能源技术
- 地理信息系统 (GIS) 是一个地理信息系统.
背景情况:
- 风能占地面积的估计因数据限制和方法不一致而有很大差异.
- 精确量化土地利用对于高效的风能项目开发和与其他能源进行比较至关重要.
研究的目的:
- 开发和应用一种新方法,以一致量化风能项目的土地面积和影响.
- 评估先前的土地利用和人类修改对风能土地利用效率和土地转型的影响.
主要方法:
- 结合基于机器学习的图像分析与地理信息系统 (GIS).
- 在美国西部互联网中分析了318个风力发电场 (15,871台轮机).
- 使用缓冲几何作为外围轮冲击评估的代理.
主要成果:
- 在人类修改较少的地区的风力项目显示了更高的土地利用效率 (63.8 ± 8.9 W/m2) 和较低的土地转型 (0.24 ± 0.07 m2/MWh).
- 在高度改造的地区的项目表现出显著更高的土地利用效率 (447 ± 49.4 W/m2),但较低的土地转型 (0.05 ± 0.01 m2/MWh).
- 与传统方法相比,开发的方法可以减少99%以上的工作量.
结论:
- 建立了一种可复制的方法,用于在风能中一致量化土地资源.
- 以前的土地使用是影响土地利用效率和风电项目的转型的关键因素.
- 这些发现支持区域化影响评估和改进可再生能源替代品的比较.
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