{"title":"基于递归最小二乘估计的智能建筑需求响应能力评估方法","authors":"Chen Li, Mingze Tong, Zhibin Ma, Shiwei Xia, Peng Wang, Qing Ge, Yukai Li","doi":"10.1049/rpg2.13060","DOIUrl":null,"url":null,"abstract":"<p>Fully tapping adjustable load demand response capabilities is necessary to guide massive and dispersed demand-side resources to participate in power dispatching operations. This study considers intelligent buildings (IBS) as the research object and proposes an adjustable load demand response capability assessment method. First, response capability assessment indicators, including adjustment power, adjustment response time, and adjustment sustainable time, are established based on the technical characteristics of adjustable loads. Second, the heating, ventilation, and air conditioning system model is established for IBS. Based on this, an intelligent building is used as an adjustable load unit for parameter identification using the recursive least squares estimation method. Finally, the response capability of the intelligent building is assessed based on the identified data and established response capability assessment indicators that can provide support for power dispatch.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13060","citationCount":"0","resultStr":"{\"title\":\"Demand response capability assessment method for intelligent buildings based on recursive least squares estimation\",\"authors\":\"Chen Li, Mingze Tong, Zhibin Ma, Shiwei Xia, Peng Wang, Qing Ge, Yukai Li\",\"doi\":\"10.1049/rpg2.13060\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Fully tapping adjustable load demand response capabilities is necessary to guide massive and dispersed demand-side resources to participate in power dispatching operations. This study considers intelligent buildings (IBS) as the research object and proposes an adjustable load demand response capability assessment method. First, response capability assessment indicators, including adjustment power, adjustment response time, and adjustment sustainable time, are established based on the technical characteristics of adjustable loads. Second, the heating, ventilation, and air conditioning system model is established for IBS. Based on this, an intelligent building is used as an adjustable load unit for parameter identification using the recursive least squares estimation method. Finally, the response capability of the intelligent building is assessed based on the identified data and established response capability assessment indicators that can provide support for power dispatch.</p>\",\"PeriodicalId\":55000,\"journal\":{\"name\":\"IET Renewable Power Generation\",\"volume\":\"19 1\",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13060\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Renewable Power Generation\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/rpg2.13060\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Renewable Power Generation","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/rpg2.13060","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Demand response capability assessment method for intelligent buildings based on recursive least squares estimation
Fully tapping adjustable load demand response capabilities is necessary to guide massive and dispersed demand-side resources to participate in power dispatching operations. This study considers intelligent buildings (IBS) as the research object and proposes an adjustable load demand response capability assessment method. First, response capability assessment indicators, including adjustment power, adjustment response time, and adjustment sustainable time, are established based on the technical characteristics of adjustable loads. Second, the heating, ventilation, and air conditioning system model is established for IBS. Based on this, an intelligent building is used as an adjustable load unit for parameter identification using the recursive least squares estimation method. Finally, the response capability of the intelligent building is assessed based on the identified data and established response capability assessment indicators that can provide support for power dispatch.
期刊介绍：
IET Renewable Power Generation (RPG) brings together the topics of renewable energy technology, power generation and systems integration, with techno-economic issues. All renewable energy generation technologies are within the scope of the journal.
Specific technology areas covered by the journal include:
Wind power technology and systems
Photovoltaics
Solar thermal power generation
Geothermal energy
Fuel cells
Wave power
Marine current energy
Biomass conversion and power generation
What differentiates RPG from technology specific journals is a concern with power generation and how the characteristics of the different renewable sources affect electrical power conversion, including power electronic design, integration in to power systems, and techno-economic issues. Other technologies that have a direct role in sustainable power generation such as fuel cells and energy storage are also covered, as are system control approaches such as demand side management, which facilitate the integration of renewable sources into power systems, both large and small.
The journal provides a forum for the presentation of new research, development and applications of renewable power generation. Demonstrations and experimentally based research are particularly valued, and modelling studies should as far as possible be validated so as to give confidence that the models are representative of real-world behavior. Research that explores issues where the characteristics of the renewable energy source and their control impact on the power conversion is welcome. Papers covering the wider areas of power system control and operation, including scheduling and protection that are central to the challenge of renewable power integration are particularly encouraged.
The journal is technology focused covering design, demonstration, modelling and analysis, but papers covering techno-economic issues are also of interest. Papers presenting new modelling and theory are welcome but this must be relevant to real power systems and power generation. Most papers are expected to include significant novelty of approach or application that has general applicability, and where appropriate include experimental results. Critical reviews of relevant topics are also invited and these would be expected to be comprehensive and fully referenced.
Current Special Issue. Call for papers:
Power Quality and Protection in Renewable Energy Systems and Microgrids - https://digital-library.theiet.org/files/IET_RPG_CFP_PQPRESM.pdf
Energy and Rail/Road Transportation Integrated Development - https://digital-library.theiet.org/files/IET_RPG_CFP_ERTID.pdf
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