Model Predictive Control for Hydroelectric Power Plant Reservoirs

S. Zanoli, C. Pepe, G. Astolfi, F. Luzi
{"title":"Model Predictive Control for Hydroelectric Power Plant Reservoirs","authors":"S. Zanoli, C. Pepe, G. Astolfi, F. Luzi","doi":"10.1109/iccc54292.2022.9805881","DOIUrl":null,"url":null,"abstract":"The present work describes a project aimed to the optimization of the water management within the reservoirs of a hydroelectric plant located in Italy. The considered reservoirs feed a set of turbines for energy production. The nature of the process and the availability of forecasts on water requests by the hydroelectric plant motivated the choice of a Model Predictive Control strategy. A first principle linear model with time delays has been adopted for the process modellization; the relationship between the sensor level information and reservoir water volume has been suitably identified from data. A tailored strategy for taking into account unknown water flows has been developed. The MPC strategy has been designed based on the obtained linear model and on assigned control specifications. In particular, special attention has been given not to waste water and at the same time to guarantee a prompt reaction to possible variation of the electric energy production plan. The reliability of the proposed approach has been tested through tailored simulation experiments, taking into account different significant scenarios. The developed proprietary framework has been installed on the real plant, confirming the validity of the designed control strategies.","PeriodicalId":167963,"journal":{"name":"2022 23rd International Carpathian Control Conference (ICCC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 23rd International Carpathian Control Conference (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iccc54292.2022.9805881","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The present work describes a project aimed to the optimization of the water management within the reservoirs of a hydroelectric plant located in Italy. The considered reservoirs feed a set of turbines for energy production. The nature of the process and the availability of forecasts on water requests by the hydroelectric plant motivated the choice of a Model Predictive Control strategy. A first principle linear model with time delays has been adopted for the process modellization; the relationship between the sensor level information and reservoir water volume has been suitably identified from data. A tailored strategy for taking into account unknown water flows has been developed. The MPC strategy has been designed based on the obtained linear model and on assigned control specifications. In particular, special attention has been given not to waste water and at the same time to guarantee a prompt reaction to possible variation of the electric energy production plan. The reliability of the proposed approach has been tested through tailored simulation experiments, taking into account different significant scenarios. The developed proprietary framework has been installed on the real plant, confirming the validity of the designed control strategies.
水电站水库模型预测控制
目前的工作描述了一个项目,旨在优化位于意大利的水力发电厂水库内的水管理。所考虑的水库为一组涡轮机提供能源生产。该过程的性质和水力发电厂用水需求预测的可用性促使选择模型预测控制策略。过程建模采用了带时滞的第一性原理线性模型;从数据中适当地识别了传感器液位信息与水库水量之间的关系。已经制定了一项考虑到未知水流的专门战略。基于得到的线性模型和指定的控制规范,设计了MPC策略。尤其要特别注意不浪费水,同时保证对电力生产计划可能发生的变化作出迅速反应。考虑到不同的重要场景,通过量身定制的仿真实验测试了所提出方法的可靠性。开发的专有框架已安装在实际工厂上,证实了所设计的控制策略的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信