Sumin Jeon , Hyungsu Kang , Suwon Song , Sumin Kim
{"title":"为能源共享社区规划建立基于频率的时序建筑能源数据清单的方法","authors":"Sumin Jeon , Hyungsu Kang , Suwon Song , Sumin Kim","doi":"10.1016/j.solener.2024.112693","DOIUrl":null,"url":null,"abstract":"<div><p>This study aims to establish a foundation for estimating energy demand according to building types by proposing a method to establish a time-series energy data inventory solely based on energy consumption in countries where typical models or benchmarking data by building types have not been developed. First, we presented the characteristics of energy consumption patterns that can be defined from the energy consumption itself based on frequency characteristics. Then, we defined a method to normalize and classify types of daily energy consumption patterns using this method and validated it with measured data. Finally, based on the results, a generalized method for establishing building time series energy data inventory was proposed. This method has a simple procedure and its result can be interpreted intuitively. It does not require data to be converted into stationary time-series data, unlike statistical methods, and it can avoid data distortion due to building operational errors. Moreover, it is easy to find the reasons for the results because the processes are easy to understand, unlike artificial intelligence methods. This study proposes a method to establish a time-series building energy data inventory by classifying types based solely on energy consumption. Furthermore, it suggests the possibility of its application in the early stages of planning an energy-sharing community.</p></div>","PeriodicalId":428,"journal":{"name":"Solar Energy","volume":null,"pages":null},"PeriodicalIF":6.0000,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Method to establish time-series building energy data inventory based on frequency for energy-sharing community planning\",\"authors\":\"Sumin Jeon , Hyungsu Kang , Suwon Song , Sumin Kim\",\"doi\":\"10.1016/j.solener.2024.112693\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study aims to establish a foundation for estimating energy demand according to building types by proposing a method to establish a time-series energy data inventory solely based on energy consumption in countries where typical models or benchmarking data by building types have not been developed. First, we presented the characteristics of energy consumption patterns that can be defined from the energy consumption itself based on frequency characteristics. Then, we defined a method to normalize and classify types of daily energy consumption patterns using this method and validated it with measured data. Finally, based on the results, a generalized method for establishing building time series energy data inventory was proposed. This method has a simple procedure and its result can be interpreted intuitively. It does not require data to be converted into stationary time-series data, unlike statistical methods, and it can avoid data distortion due to building operational errors. Moreover, it is easy to find the reasons for the results because the processes are easy to understand, unlike artificial intelligence methods. This study proposes a method to establish a time-series building energy data inventory by classifying types based solely on energy consumption. Furthermore, it suggests the possibility of its application in the early stages of planning an energy-sharing community.</p></div>\",\"PeriodicalId\":428,\"journal\":{\"name\":\"Solar Energy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2024-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Solar Energy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0038092X24003888\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Solar Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0038092X24003888","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Method to establish time-series building energy data inventory based on frequency for energy-sharing community planning
This study aims to establish a foundation for estimating energy demand according to building types by proposing a method to establish a time-series energy data inventory solely based on energy consumption in countries where typical models or benchmarking data by building types have not been developed. First, we presented the characteristics of energy consumption patterns that can be defined from the energy consumption itself based on frequency characteristics. Then, we defined a method to normalize and classify types of daily energy consumption patterns using this method and validated it with measured data. Finally, based on the results, a generalized method for establishing building time series energy data inventory was proposed. This method has a simple procedure and its result can be interpreted intuitively. It does not require data to be converted into stationary time-series data, unlike statistical methods, and it can avoid data distortion due to building operational errors. Moreover, it is easy to find the reasons for the results because the processes are easy to understand, unlike artificial intelligence methods. This study proposes a method to establish a time-series building energy data inventory by classifying types based solely on energy consumption. Furthermore, it suggests the possibility of its application in the early stages of planning an energy-sharing community.
期刊介绍:
Solar Energy welcomes manuscripts presenting information not previously published in journals on any aspect of solar energy research, development, application, measurement or policy. The term "solar energy" in this context includes the indirect uses such as wind energy and biomass