A factor analysis and self-organizing map based evaluation approach for the renewable energy heating potentials at county level: A case study in China

可再生能源 环境经济学 资源(消歧) 比例(比率) 地热能 可再生资源 工程类 计算机科学 地温梯度 地热能 经济 地理 计算机网络 地图学 地球物理学 地质学 电气工程
作者
Xuejing Zheng,Xueqing Yang,Hongfei Miao,Huzhen Liu,Yanzhe Yu,Yaran Wang,Huan Zhang,Shijun You
出处
期刊:Renewable & Sustainable Energy Reviews [Elsevier BV]
卷期号:165: 112597-112597 被引量:5
标识
DOI:10.1016/j.rser.2022.112597
摘要

Reflecting on the sharp contradictions between energy and environmental concerns, nowadays, a critical theme is to strengthen the role of renewables for heating. The majority of current renewable energy (RE) studies are for power generation, research at the macro level, with subjective evaluation methods. Aimed at filling the niche, this paper proposes an integrated approach involving the investigation of renewable energy (solar, geothermal and biomass) heating potentials, the evaluation of suitability at the county level, and the guidance of targeted policies. Accordingly, the factor analysis, an objective statistical analysis method, is employed to concentrate information and score appropriateness based on the county development level, population quality, government support and renewable resource potentials. Subsequently, the comprehensive scores for counties are categorized into four classes by self-organizing maps. In this study, a novel approach for evaluating the RE heating potentials and identifying the constraints of RE development is proposed. The heating demand and the potentials of renewables are determined on a detailed and precise scale at the county level, and the heating supply-demand is mapped with symbol sizes. Finally, specific recommendations for renewables energy development are put forward from a local planning perspective. The application of this systematic approach, which can be broadly exported and applied to other regions, will promote a strong commitment to renewable energy and significantly accelerate the transition to a clean energy supply.
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