Sterl Sebastian, Hussain Bilal, Miketa Asami, Li Yunshu, Merven Bruno, Ben Ticha Mohammed Bassam, Elabbas Mohamed A Eltahir, Thiery Wim, Russo Daniel
International Renewable Energy Agency (IRENA), Bonn, Germany.
Faculty of Engineering, BClimate group, Department HYDR, Vrije Universiteit Brussel, Brussels, Belgium.
Sci Data. 2022 Oct 31;9(1):664. doi: 10.1038/s41597-022-01786-5.
With solar and wind power generation reaching unprecedented growth rates globally, much research effort has recently gone into a comprehensive mapping of the worldwide potential of these variable renewable electricity (VRE) sources. From a perspective of energy systems analysis, the locations with the strongest resources may not necessarily be the best candidates for investment in new power plants, since the distance from existing grid and road infrastructures and the temporal variability of power generation also matter. To inform energy planning and policymaking, cost-optimisation models for energy systems must be fed with adequate data on potential sites for VRE plants, including costs reflective of resource strength, grid expansion needs and full hourly generation profiles. Such data, tailored to energy system models, has been lacking up to now. In this study, we present a new open-source and open-access all-Africa dataset of "supply regions" for solar photovoltaic and onshore wind power to feed energy models and inform capacity expansion planning.
随着太阳能和风能发电在全球范围内达到前所未有的增长率，最近许多研究工作都致力于全面绘制这些可变可再生电力（VRE）资源在全球的潜力。从能源系统分析的角度来看，资源最丰富的地区不一定是投资新建发电厂的最佳选择，因为与现有电网和道路基础设施的距离以及发电的时间变化性也很重要。为了为能源规划和政策制定提供信息，能源系统的成本优化模型必须输入有关VRE发电厂潜在选址的充分数据，包括反映资源强度、电网扩展需求和完整每小时发电概况的成本。到目前为止，一直缺乏针对能源系统模型量身定制的此类数据。在本研究中，我们展示了一个新的开源且开放获取的全非洲太阳能光伏和陆上风能“供应区域”数据集，以输入能源模型并为容量扩展规划提供信息。
