[1]梁 伟,马兴海,陈海宏,等.基于物联网的光伏电站远程监测及功率预测研究[J].工业仪表与自动化装置,2025,(05):117-123.[doi:10.19950/j.cnki.CN61-1121/TH.2025.05.022]
　LIANG Wei,MA Xinghai,CHEN Haihong,et al.Research on remote monitoring and power prediction of photovoltaic power stations based on the Internet of Things[J].Industrial Instrumentation & Automation,2025,(05):117-123.[doi:10.19950/j.cnki.CN61-1121/TH.2025.05.022]
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基于物联网的光伏电站远程监测及功率预测研究()

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2025年05期
页码:
117-123
栏目:
出版日期:
2025-10-15

文章信息/Info

Title:
Research on remote monitoring and power prediction of photovoltaic power stations based on the Internet of Things
文章编号:
1000-0682（2025）05-0117-07
作者:
梁 伟; 马兴海; 陈海宏; 马映江; 王志强
甘肃龙源新能源有限公司，甘肃 兰州 730050
Author(s):
LIANG Wei;  MA Xinghai;  CHEN Haihong;  MA Yingjiang;  WANG Zhiqiang
Gansu Longyuan New Energy Co., Ltd.,Gansu Lanzhou 730050, China
关键词:
光伏电站; 远程监测; 功率预测; SCSSA-CNN-BiLSTM预测模型
Keywords:
photovoltaic power station;  remote monitoring;  power prediction;  SCSSA-CNN BiLSTM prediction model
分类号:
TM615
DOI:
10.19950/j.cnki.CN61-1121/TH.2025.05.022
文献标志码:
A
摘要:
针对沙漠光伏电站规模大、工作环境恶劣，不利于工作人员掌握电站实时运行状态，存在故障处理不及时、易发生安全事故等问题，基于物联网技术和神经网络算法，设计了光伏电站远程监测及功率预测系统，实现电站运行状态数据的实时采集，通过无线通信技术进行远程传输，最终实现光伏电站的远程监测和智能管理。提出了SCSSA-CNN-BiLSTM预测模型，实现对光伏输出功率的精准预测。系统运行稳定可靠，数据采集误差小于1%，光伏输出功率预测平均绝对误差小于0.3，对于指导工作人员优化电网调配、提高电站运营效率具有实际应用价值。
Abstract:
In response to the large scale and harsh working environment of desert photovoltaic power stations, which are not conducive to the real-time operation status of the power station for staff, and have problems such as untimely fault handling and easy occurrence of safety accidents, a remote monitoring and power prediction system for photovoltaic power stations is designed based on Internet of Things technology and neural network algorithms to achieve real-time collection of power station operation status data, remote transmission through wireless communication technology, and ultimately achieve remote monitoring and intelligent management of photovoltaic power stations. Propose the SCSA-CNN BiLSTM prediction model to achieve accurate prediction of photovoltaic output power. The system runs stably and reliably, with a data collection error of less than 1% and an average absolute error of less than 0.3 for predicting photovoltaic output power. It guides staff to optimize power grid allocation, improve power station operation efficiency, and has practical application value.

参考文献/References:

[1]武文江,郭俊卿.光伏电站运维中人工智能技术的应用研究[J].电力设备管理,2025(02):156-158.

[2]刘淑娟,袁宏波,刘虎俊,等.沙漠地区光伏电场的风沙危害及光伏治沙模式[J].防护林科技,2025(02):76-81.
[3]尚小伟,刘建国,卫建军,等.沙漠地区光伏电站风沙问题治理措施及策略[J].能源与环保,2024,46(11):159-167.
[4]杨文,倪志强.光伏电站设备状态监测与故障诊断技术研究与应用[J].电力与能源,2025,46(01):16-19+48.
[5]刘山麒,朱武,王光东.基于LoRa和NB-IoT的分布式光伏电站监测系统设计[J].集成电路与嵌入式系统,2024,24(12):59-65.
[6]孙路,丁振华,丁宏,等.基于物联网和云平台的光伏电站标准化模块检测系统设计[J].电气技术,2025,26(03):75-80.
[7]纪泽飞,吴思宇.集中式光伏电站中的智能监控技术分析[J].电子技术,2025,54(01):389-391.
[8]杜虎,阚斌,高武山,等.基于气象特征的分布式光伏发电监测方法[J].微型电脑应用,2024,40(10):72-75.
[9]李承皓,杨永标,宋嘉启,等.基于IMVMD和BiLSTM-SARIMA组合模型的台区光伏短期发电功率预测[J].太阳能学报,2025,46(02):433-440.
[10]姚阳,杨朝翔,张皓天,等.基于CNN的太阳能热泵—壁挂炉供暖系统约束控制方法[J].建筑节能(中英文),2023,51(02):64-69.
[11]王玲芝,李晨阳,刘婧,等.基于GRO-SSA-LSTM的短期光伏发电功率预测[J].太阳能学报,2025,46(02):401-409.

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备注/Memo

备注/Memo:
收稿日期：2025-02-19第一作者：梁伟（1989—），男，甘肃陇西人，高级工程师，主要研究方向为电气工程及其自动化。E-mail：hmcdy123456@163.com
更新日期/Last Update: 1900-01-01