新能源风光场站发电量预测与交易策略
Power Generation Prediction and Trading Strategy for New Energy Wind and Solar Power Plants
李伟 1高益坚 1付常德1
作者信息
- 1. 河北华电冀北新能源有限公司,河北张家口 075000
- 折叠
摘要
随着新能源技术的发展,其在全球能源结构中的份额逐年上升,带来了发电量预测和交易策略的新挑战和机遇.文章探讨了新能源风光发电技术的特点及其发电量的波动性.利用深度学习与神经网络模型,对新能源发电量进行高精度预测,同时结合交易市场的实际情况,构建了基于风险和收益的交易策略.通过机器学习的方法进一步优化交易策略,为新能源发电量的市场化交易提供科学依据.
Abstract
With the development of new energy technologies,their share in the global energy structure has been increasing year by year,bringing new challenges and opportunities for power generation forecasting and trading strategies.This article delves into the classification,characteristics,and volatility of new energy technologies and their power generation.Using deep learning and neural network models,high-precision prediction of new energy generation was carried out,and a trading strategy based on risk and return was constructed in combination with the actual situation of the trading market.Further optimize trading strategies through machine learning methods to provide scientific basis for market-oriented trading of new energy generation.
关键词
新能源风光场站/深度学习/发电量预测/交易策略Key words
new energy wind and solar power station/deep learning/power generation forecast/trading strategy引用本文复制引用
出版年
2024
NETL
NSTL
万方数据