Optimization of Wind and Light Power Generation Prediction Model Based on RNA-CS Hybrid Algorithm

GUAN Da; LING Yun

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Optimization of Wind and Light Power Generation Prediction Model Based on RNA-CS Hybrid Algorithm

更新时间：2025-11-18

- Optimization of Wind and Light Power Generation Prediction Model Based on RNA-CS Hybrid Algorithm
- Vol. 40, Issue 1, Pages: 20-23(2020)
- 作者机构：
  
  湖南工业大学
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM61;TP18
- Published：2020
- 稿件说明：
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[1]官达,凌云.基于RNA-CS混合算法优化的风光发电预测模型研究[J].湖南电力,2020,40(01):20-23.

GUAN Da, LING Yun. Optimization of Wind and Light Power Generation Prediction Model Based on RNA-CS Hybrid Algorithm[J]. 2020, 40(1): 20-23.
[1]官达,凌云.基于RNA-CS混合算法优化的风光发电预测模型研究[J].湖南电力,2020,40(01):20-23. DOI：

GUAN Da, LING Yun. Optimization of Wind and Light Power Generation Prediction Model Based on RNA-CS Hybrid Algorithm[J]. 2020, 40(1): 20-23. DOI：

摘要

提出一种基于RNA-CS混合算法优化的预测模型

优化布谷鸟算法

权衡全局搜索和局部搜索。结合某地区风力和光伏发电实际

对一天中的风速和辐射进行测量。采用基础遗传算法、基础布谷鸟算法与RNA-CS混合算法进行仿真对比研究。结果表明

RNA-CS混合优化算法对比其他两种算法模型

对风电、光伏发电具有更精确的预测结果

能够有效的保障电力系统稳定运行。

Abstract

A prediction model based on RNA-CS hybrid algorithm is proposed to optimize the cuckoo algorithm and balance the global search and local search. Combined with the actual wind and photovoltaic power generation in a certain area

the wind speed and radiation in a day are measured. The basic genetic algorithm

the basic cuckoo algorithm and the RNA-CS hybrid algorithm are used for simulation and comparison. The results show that the RNA-CS hybrid optimization algorithm has more accurate prediction results for wind power and photovoltaic power generation compared with the other two algorithms

and can effectively guarantee the stable operation of the power system.

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