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Abstract A convenient and effective method based on vector analysis was proposed in this paper to quantitatively describe the pattern of the wind speed distribution curve. This method can accurately describe the steepness of the single‐peak curve by using two parameters of concentration degree (CD) and concentration period (CP). Through the analysis of wind speed data in China over the past 40 years, this paper found that regional wind resources with larger CD were poorer, while regional wind resources with larger CP were richer. In addition, there were obvious cubic relationships between the CP and the average wind power density. These two parameters could reflect the richness of wind energy and realize the comparisons of wind resources across time and scales. In comparison with conventional approaches, this method is simpler and avoids fitting process, which has broad promotion prospects in the field of power grids.

A convenient and effective method based on vector analysis was proposed in this paper to quantitatively describe the pattern of the wind speed distribution curve. This method can accurately describe the steepness of the single‐peak curve by using two parameters of concentration degree (CD) and concentration period (CP). Through the analysis of wind speed data in China over the past 40 years, this paper found that regional wind resources with larger CD were poorer, while regional wind resources with larger CP were richer. In addition, there were obvious cubic relationships between the CP and the average wind power density. These two parameters could reflect the richness of wind energy and realize the comparisons of wind resources across time and scales. In comparison with conventional approaches, this method is simpler and avoids fitting process, which has broad promotion prospects in the field of power grids. [ABSTRACT FROM AUTHOR]

Space heating is the single greatest source of building-related greenhouse gas emissions in the industrialized world, giving urgency to the development of strategies for carbon-free heating. Recent advances have shown that the direct capture, storage, and deployment of solar energy, without conversion to electricity, has considerable potential to address space-heating needs even in cold and cloudy climates. However, the solar energy available for direct heating at climatic and metropolitan scales is both unquantified and widely assumed to be negligible, impeding further investigation, development, and policy responses. To estimate the magnitude and distribution of solar resources concurrent with space-heating needs, we spatially integrate datasets characterizing solar radiation, outdoor temperature, and heating energy use across U.S. climates. Results show that the median resource incident upon collectors of residential scale (10 m2) and distribution is much greater than previously realized, equaling 7 MWh per household annually; by comparison, the median household heating need is currently 10.3 MWh. Unexpectedly, cloud-diffused solar radiation accounts for over one-quarter of this resource in all but semi-arid climates. Metropolitan residential resources exceed 5 TWh in areas including Detroit and Boston (cold continental), Washington D.C. (humid subtropical), Seattle and San Francisco (Mediterranean), and Denver (semi-arid), and national resources exceed 750 TWh annually, compared to approximately 1200 TWh of annual heating need. Current technology is able to capture and retain over half of a direct solar heating resource, revealing that the untapped U.S. solar heating potential is comparable to one-third of the national residential space-heating need and implying that analogous resources exist in analogous climates worldwide. • Solar energy resources for direct space heating are estimated for the first time. • Resources are extensive in cool, cold, and cloudy climates. • Diffuse radiation is often a sizable resource component, requiring tilted collectors. • The median U.S. household direct solar heating resource exceeds 7 MWh annually. • The untapped U.S. solar heating potential equals one-third of residential needs. [ABSTRACT FROM AUTHOR]