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Guest Editorial for the Special Section on Advances in Renewable Energy Forecasting: Predictability, Business Models and Applications in the Power Industry
IEEE Transactions on Sustainable Energy ( IF 8.6 ) Pub Date : 2022-03-21 , DOI: 10.1109/tste.2022.3157009
Ricardo J. Bessa 1 , Pierre Pinson 2 , George Kariniotakis 3 , Dipti Srinivasan 4 , Charlie Smith 5 , Nima Amjady 6 , Hamidreza Zareipour 7
Affiliation  

The papers in this special section focus on advances in renewable energy forecasting, predictability, business models, and applications in the power industry. During the last 25 years, research has been conducted for developing renewable energy source (RES) forecasting algorithms, especially for wind and solar energy, seeking an improvement of predictability and uncertainty forecasting products. Research on wave energy forecasting is also being conducted, although this technology is not at the same maturity levels of wind and solar energy technologies. Furthermore, the number of companies selling forecasting services has proliferated and the reliability and availability of the services have improved. Currently, power system operators and electrical energy traders use weather and power forecasts embedded in their decision-making processes. Despite all this research and adoption by the energy industry, deterministic forecasts are still predominant in utility practice mainly due to: i) lack of understanding and standardization of uncertainty forecast products; and ii) high computational time associated with stochastic and robust optimization approaches. Moreover, proven business cases are also needed to demonstrate the benefits of uncertainty forecasts to end-users.

中文翻译:


可再生能源预测进展特别部分的客座社论:电力行业的可预测性、商业模式和应用



本专题部分的论文重点关注可再生能源预测、可预测性、商业模式和电力行业应用方面的进展。在过去的 25 年里,人们一直在研究开发可再生能源 (RES) 预测算法,特别是风能和太阳能,以寻求改进可预测性和不确定性预测产品。波浪能预测的研究也在进行中,尽管这项技术的成熟度与风能和太阳能技术并不相同。此外,销售预测服务的公司数量激增,服务的可靠性和可用性也得到了提高。目前,电力系统运营商和电能交易商在决策过程中嵌入了天气和电力预测。尽管能源行业进行了所有这些研究和采用,但确定性预测在公用事业实践中仍然占主导地位,这主要是由于:i)缺乏对不确定性预测产品的理解和标准化; ii) 与随机和鲁棒优化方法相关的高计算时间。此外,还需要经过验证的业务案例来向最终用户展示不确定性预测的好处。
更新日期:2022-03-21
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