一种基于分类模型的间歇发电功率预测方法

2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing Pub Date : 2014-11-08 DOI:10.1109/3PGCIC.2014.33

Hang Yang, Fuzheng Zhang, Aidong Xu, Cai Yuan, Chuanlin Chen

{"title":"一种基于分类模型的间歇发电功率预测方法","authors":"Hang Yang, Fuzheng Zhang, Aidong Xu, Cai Yuan, Chuanlin Chen","doi":"10.1109/3PGCIC.2014.33","DOIUrl":null,"url":null,"abstract":"More and more power plants have been constructed and generated by intermittent energy. As a clean and renewable energy, such sources as wind and solar are favored in the new generation of power grid system. However, influenced by factors of geography, circumstance and climates, the renewable energy has the characteristics of intermittency, volatility and uncontrollability, which reduce the efficient utilization of intermittent energy. This paper uses data mining methods to predict the level of power generation from solar energy, by analyzing the information collected from distributed power plants. Investigating the real-world power grid dataset, the experimental result verifies the feasibility of the proposed method for improving the utilization of intermittent energy.","PeriodicalId":395610,"journal":{"name":"2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Method to Predict the Intermittent Power by Classification Model\",\"authors\":\"Hang Yang, Fuzheng Zhang, Aidong Xu, Cai Yuan, Chuanlin Chen\",\"doi\":\"10.1109/3PGCIC.2014.33\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"More and more power plants have been constructed and generated by intermittent energy. As a clean and renewable energy, such sources as wind and solar are favored in the new generation of power grid system. However, influenced by factors of geography, circumstance and climates, the renewable energy has the characteristics of intermittency, volatility and uncontrollability, which reduce the efficient utilization of intermittent energy. This paper uses data mining methods to predict the level of power generation from solar energy, by analyzing the information collected from distributed power plants. Investigating the real-world power grid dataset, the experimental result verifies the feasibility of the proposed method for improving the utilization of intermittent energy.\",\"PeriodicalId\":395610,\"journal\":{\"name\":\"2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/3PGCIC.2014.33\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/3PGCIC.2014.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

越来越多的发电厂已经建成，并利用间歇性能源发电。风能、太阳能作为清洁可再生能源，在新一代电网系统中备受青睐。然而，受地理、环境和气候等因素的影响，可再生能源具有间歇性、波动性和不可控性等特点，降低了间歇性能源的高效利用。本文利用数据挖掘的方法，通过对分布式电站收集的信息进行分析，对太阳能发电水平进行预测。通过对实际电网数据集的研究，实验结果验证了该方法提高间歇性能源利用率的可行性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A Method to Predict the Intermittent Power by Classification Model

More and more power plants have been constructed and generated by intermittent energy. As a clean and renewable energy, such sources as wind and solar are favored in the new generation of power grid system. However, influenced by factors of geography, circumstance and climates, the renewable energy has the characteristics of intermittency, volatility and uncontrollability, which reduce the efficient utilization of intermittent energy. This paper uses data mining methods to predict the level of power generation from solar energy, by analyzing the information collected from distributed power plants. Investigating the real-world power grid dataset, the experimental result verifies the feasibility of the proposed method for improving the utilization of intermittent energy.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing

自引率

0.00%

发文量