Data basis of economic-environmental analysis for renewables
The decreasing cost of renewable energy devices, technology maturity and increasing efficiency in renewable energy generation improve the competitiveness of renewable systems in replacement of traditional fossil fuel power generation units, while the scalability and market acceptance of renewable sy...
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Format: | Dataset |
Sprache: | eng |
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Zusammenfassung: | The decreasing cost of renewable energy devices, technology maturity and increasing efficiency in renewable energy generation improve the competitiveness of renewable systems in replacement of traditional fossil fuel power generation units, while the scalability and market acceptance of renewable systems are still questionable, especially due to spatiotemporal intermittence, high levelized cost of energy, unwillingness for spontaneous renewable installation for stakeholders, and etc. We attempt to answer this question by evaluating the economic and ecological performance of both centralized and distributed renewable energy systems. We argue the general conclusion that renewable energy has been more affordable than traditional energy supply while neglecting the renewable type, climate condition, device degradation, life cycle assessment, currency depreciation, and application scenarios.
By comparing the energy costs and energy carbon emissions for centralized and distributed renewable energy systems in diverse Chinese cities with varying climates, we find that in most cases, renewable energy is not economically viable but demonstrates absolute superiority in low carbon emission over traditional energy supply. To incentivize renewable energy adoption and achieve dual-carbon goals in China, we propose the implementation of the levelized carbon mitigation subsidy (LCMS). However, determining values for the LCMS impose significant policy challenges, as it is quite higher than the existing carbon price.
The dataset contains the instantaneous power generation of different renewables under different application scenarios, and the electricity demand of buildings across different climates of China, which serves as the data basis of this research. |
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DOI: | 10.5281/zenodo.10697086 |