可再生能源电力预测技术

[中文适用范围]： 本技术规范报告，性质为信息性文件，描述了可再生能源电力预测技术的通用实践和最新技术水平，包括一般数据需求、可再生能源电力预测方法和预测误差评估。在本文档的目的范围内，可再生能源指的是可变可再生能源，主要包括风能和光伏（PV）电力——这是本文档的重点。其他可变可再生能源，如聚光太阳能、波浪能和潮汐能等，由于容量较小，未在本文档中介绍；而水电预测是一个显著不同的领域，因此也不涵盖在此。可再生能源电力预测的对象可以是风力涡轮机、风电场，或拥有许多风电场的区域（相应地，对于光伏系统、光伏电站和拥有高光伏渗透率的区域）。本文档侧重于提供关于多时空尺度、概率预测以及风能和光伏功率坡道事件预测的技术指南。本文档概述了可再生能源电力预测技术的基本方面。这是IEC发布的关于可再生能源电力预测的第一份文件。本文档的内容将应用于以下潜在领域：展示当前技术水平，支持可再生能源电力预测技术的发展和未来研究；在可再生能源电力预测系统的设计和操作期间评估预测性能；提供基准测试可再生能源预测技术（包括所用方法、所需数据和评估技术）的信息。 [外文原描述]： 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