比较低资源太阳能临近预报的碳成本和效益
Comparing the carbon costs and benefits of low-resource solar nowcasting
摘要：
太阳能光伏发电产量临近预报用于帮助预测需求的高峰和低谷，以支持电网整合。本文比较了多种低资源方法来临近预报太阳能光伏发电量，使用英国卫星图像和太阳能光伏能量读数在1至4小时的时间范围内的数据集。该论文还估计了通过部署模型产生和避免的碳排放量，并发现即使是可以在低资源环境中部署的小型模型也可能比其碳成本大几个数量级。本文还研究了预测误差和CNN中的激活。
英文摘要：
Solar PV yield nowcasting is used to help anticipate peaks and troughs in demand to support grid integration. This paper compares multiple low-resource approaches to nowcasting solar PV yield, using a dataset of UK satellite imagery and solar PV energy readings over a 1 to 4-hour time range. The paper also estimates the carbon emissions generated and averted by deploying models, and finds that even small models that could be deployable in low-resource settings may have a benefit several orders of magnitude greater than its carbon cost. The paper also examines prediction errors and the activations in a CNN.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
