摘要
电力系统由发电、输电等多环节构成。清洁能源发电具间歇性与波动性,其大规模接入为电力系统带来挑战与机遇。人工智能核心技术适配电力系统数据特点,在运行分析与决策中发挥重要作用。基于人工智能的清洁能源发电预测先进行数据采集与预处理,再对预测结果不确定性进行分析与修正,利用机器学习、深度学习算法提升预测精度。在电力系统清洁能源调度策略优化方面,通过人工智能负荷预测,构建多目标调度模型,将强化学习应用于调度决策,且人工智能与传统调度算法融合,提升调度策略优化效果。
The power system consists of multiple links such as generation and transmission.Clean energy generation has intermittency and volatility,and its large-scale integration brings challenges and opportunities to the power system.The core technology of artificial intelligence adapts to the characteristics of power system data and plays an important role in operation analysis and decision-making.The prediction of clean energy generation based on artificial intelligence first collects and preprocesses the data,then analyzes and corrects the uncertainty of the prediction results,and uses machine learning and deep learning algorithms to improve the prediction accuracy.In terms of optimizing clean energy dispatch strategies in the power system,a multi-objective dispatch model is constructed through artificial intelligence load forecasting,and reinforcement learning is applied to dispatch decision-making.The integration of artificial intelligence and traditional dispatch algorithms improves the optimization effect of dispatch strategies.
作者
战鹰
ZHAN Ying(Changji Vocational and Technical College,Changji 831100,China)
出处
《通信电源技术》
2025年第10期103-105,共3页
Telecom Power Technology
关键词
电力系统
清洁能源发电
人工智能
发电预测
调度策略
power system
clean energy generation
artificial intelligence
power generation forecast
scheduling strategy
