{"title":"为电力系统集成建立热泵负荷曲线模型","authors":"","doi":"10.1016/j.epsr.2024.111059","DOIUrl":null,"url":null,"abstract":"<div><p>Heat pumps (HPs) are one of the most efficient heating technologies; their mass adoption will be required to decarbonize energy systems. However, to do so will require a better understanding of how they will impact electric grid load. Methods are needed to estimate not just their peak demand but also their impact on hourly load profiles. In this paper, we propose two methods, using easily accessible data, for estimating future hourly load profiles following the adoption of large populations of residential HPs. The first method uses feeder load data disaggregation while the second method uses annual space heating end-use energy consumption, both taking into account the temperature dependencies on coefficient of performance and output heat capacity. A case study based on data from Summerside, PE, Canada, is used to demonstrate and evaluate the two methods.</p></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378779624009441/pdfft?md5=2aff90de186793075c1ac6fe81c2ecf4&pid=1-s2.0-S0378779624009441-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Modeling of heat pumps load profiles for power systems integration\",\"authors\":\"\",\"doi\":\"10.1016/j.epsr.2024.111059\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Heat pumps (HPs) are one of the most efficient heating technologies; their mass adoption will be required to decarbonize energy systems. However, to do so will require a better understanding of how they will impact electric grid load. Methods are needed to estimate not just their peak demand but also their impact on hourly load profiles. In this paper, we propose two methods, using easily accessible data, for estimating future hourly load profiles following the adoption of large populations of residential HPs. The first method uses feeder load data disaggregation while the second method uses annual space heating end-use energy consumption, both taking into account the temperature dependencies on coefficient of performance and output heat capacity. A case study based on data from Summerside, PE, Canada, is used to demonstrate and evaluate the two methods.</p></div>\",\"PeriodicalId\":50547,\"journal\":{\"name\":\"Electric Power Systems Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0378779624009441/pdfft?md5=2aff90de186793075c1ac6fe81c2ecf4&pid=1-s2.0-S0378779624009441-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electric Power Systems Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0378779624009441\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electric Power Systems Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378779624009441","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
摘要
热泵(HPs)是最高效的供热技术之一;要实现能源系统的去碳化,就必须大规模采用热泵。然而,要做到这一点,需要更好地了解它们将如何影响电网负荷。不仅需要估算其峰值需求的方法,还需要估算其对每小时负荷曲线的影响的方法。在本文中,我们提出了两种方法,利用易于获取的数据,估算未来大量采用住宅 HPs 后的每小时负荷曲线。第一种方法使用馈线负荷数据分解,第二种方法使用年度空间供热终端能源消耗,两种方法都考虑了性能系数和输出热容量的温度依赖性。基于加拿大 PE 省 Summerside 市数据的案例研究用于演示和评估这两种方法。
Modeling of heat pumps load profiles for power systems integration
Heat pumps (HPs) are one of the most efficient heating technologies; their mass adoption will be required to decarbonize energy systems. However, to do so will require a better understanding of how they will impact electric grid load. Methods are needed to estimate not just their peak demand but also their impact on hourly load profiles. In this paper, we propose two methods, using easily accessible data, for estimating future hourly load profiles following the adoption of large populations of residential HPs. The first method uses feeder load data disaggregation while the second method uses annual space heating end-use energy consumption, both taking into account the temperature dependencies on coefficient of performance and output heat capacity. A case study based on data from Summerside, PE, Canada, is used to demonstrate and evaluate the two methods.
期刊介绍:
Electric Power Systems Research is an international medium for the publication of original papers concerned with the generation, transmission, distribution and utilization of electrical energy. The journal aims at presenting important results of work in this field, whether in the form of applied research, development of new procedures or components, orginal application of existing knowledge or new designapproaches. The scope of Electric Power Systems Research is broad, encompassing all aspects of electric power systems. The following list of topics is not intended to be exhaustive, but rather to indicate topics that fall within the journal purview.
• Generation techniques ranging from advances in conventional electromechanical methods, through nuclear power generation, to renewable energy generation.
• Transmission, spanning the broad area from UHV (ac and dc) to network operation and protection, line routing and design.
• Substation work: equipment design, protection and control systems.
• Distribution techniques, equipment development, and smart grids.
• The utilization area from energy efficiency to distributed load levelling techniques.
• Systems studies including control techniques, planning, optimization methods, stability, security assessment and insulation coordination.