基于统计方法的风电光伏功率预测研究
Statistical Methods-based Power Prediction of Wind and Photovoltaic Generations
宋赫 1宁宾 2李恒3
作者信息
- 1. 国网江苏省电力有限公司淮安供电分公司,江苏淮安 223001
- 2. 江苏能投沿海发电有限公司,江苏盐城 224300
- 3. 国网银川供电公司,宁夏银川 750004
- 折叠
摘要
可再生能源发电具有随机性和波动性等特点,导致大规模并网运行稳定性差、调峰能力不足、消纳困难等问题.针对风电光伏的功率预测,基于时间序列和灰色理论研究模型的优化与改进,全面量化评估持续TP模型、传统和改进的新陈代谢GM模型、ARMA模型等在短期和中长期时间尺度下预测性能的差异.
Abstract
The renewable energy generations have the characteristics of randomness and fluctuation.With respect to power prediction of wind and photovoltaic generations,this work studied the optimization and improvement of predictive models based on time sequence and grey theory.It comprehensively evaluated the prediction performance of different prediction models including continuous TP model,conventional and modified metabolic GM models,and ARMA model at both short-and medium-term and long-term time scales.
关键词
风电光伏/功率预测/可再生能源/ARMA模型/统计学方法/灰色模型Key words
wind and photovoltaic generations/power prediction/renewable energy source/ARMA/statistical method/grey predictor model引用本文复制引用
出版年
2024
NETL
NSTL
万方数据