光伏电站电量预测中的系统运行参数优化与预测精度提升

Optimization of System Operating Parameters and Improvement of Prediction Accuracy in Photovoltaic Power Station Electricity Prediction

文章探讨了在光伏电站电量预测中优化系统运行参数的重要性,并研究了通过优化参数提升预测精度的方法。介绍了光伏电站电量预测的背景和意义,分析了当前存在的主要问题及其原因,包括天气条件、系统复杂性、组件老化和传统预测方法的局限性。提出了具体的系统运行参数优化方法,重点介绍了粒子群算法在优化中的应用,并通过试验证明了该方法的有效性。总结了系统运行参数优化在提升光伏电站电量预测精度方面的重要性和实用性,为未来的研究和应用提供了参考。

This paper explores the importance of optimizing system operating parameters in photovoltaic power plant electricity prediction and investigates methods to enhance prediction accuracy through parameter optimization.First,it introduces the background and significance of electricity prediction in photovoltaic power plants and analyzes the main existing problems and their causes,including weather conditions,system complexity,component aging,and the limitations of traditional prediction methods.Then,it presents specific methods for optimizing system operating parameters,with a focus on the application of the particle swarm algorithm in optimization.The effectiveness of this method is demonstrated through experiments.Finally,the paper summarizes the importance and practicality of optimizing system operating parameters in improving the accuracy of electricity prediction in photovoltaic power plants,providing a reference for future research and applications.