IEC TR 63043:2020（E）是一份技术报告，描述了可再生能源功率预测技术的常见实践和最新技术，包括一般数据需求、可再生能源功率预测方法和预测误差评估。就本文件而言，可再生能源是指可变可再生能源，主要包括风力发电和光伏发电（PV），这些是本文件的重点。其他可变的可再生能源，如聚光太阳能、波浪能和潮汐能等。，没有在本文件中介绍，因为它们的容量很小，而水力发电预测是一个明显不同的领域，因此这里不包括。 可再生能源功率预测的对象可以是风力涡轮机，也可以是风电场，也可以是风电场较多的地区（分别是光伏系统、光伏电站和光伏渗透率较高的地区）。本文件重点为风电和光伏发电的多时空尺度预测技术、概率预测和斜坡事件预测提供技术指导。 本文件概述了可再生能源功率预测技术的基本方面。这是IEC第一份与可再生能源功率预测相关的文件。本文件的内容将在以下潜在领域中得到应用: ？通过展示当前的技术水平，支持可再生能源功率预测技术的发展和未来研究； ？可再生能源功率预测系统设计和运行过程中预测性能的评估； ？提供可再生能源预测技术基准的信息，包括使用的方法、所需数据和评估技术

IEC TR 63043:2020(E), which is a technical report, describes common practices and state of the art for renewable energy power forecasting technology, including general data demands, renewable energy power forecasting methods and forecasting error evaluation. For the purposes of this document, renewable energy refers to variable renewable energy, which mainly comprises wind power and photovoltaic (PV) power – these are the focus of the document. Other variable renewable energies, like concentrating solar power, wave power and tidal power, etc., are not presented in this document, since their capacity is small, while hydro power forecasting is a significantly different field, and so not covered here.
The objects of renewable energy power forecasting can be wind turbines, or a wind farm, or a region with lots of wind farms (respectively PV systems, PV power stations and regions with high PV penetration). This document focuses on providing technical guidance concerning forecasting technologies of multiple spatial and temporal scales, probabilistic forecasting, and ramp event forecasting for wind power and PV power.
This document outlines the basic aspects of renewable energy power forecasting technology. This is the first IEC document related to renewable energy power forecasting. The contents of this document will find an application in the following potential areas:
？ support the development and future research for renewable energy power forecasting technology, by showing current state of the art;
？ evaluation of the forecasting performance during the design and operation of renewable energy power forecasting system;
？ provide information for benchmarking renewable forecasting technologies, including methods used, data required and evaluation techniques