{"title":"基于agent决策支持的透析诊所能耗模型","authors":"Stefan Wandler, S. Bai, W. Raskob","doi":"10.1504/ijspm.2020.10028741","DOIUrl":null,"url":null,"abstract":"This paper describes an approach to predict the consumptions of water and power in dialysis clinics by simulating the internal processes. Better understanding is essential to prevent and mitigate adverse health impact on patients. Our methods are based on literature about dialysis processes and dialysis clinics, which are first-hand technical reports. The nonlinear model comprises the energy consumption of the technical systems together with their working schedules and the time schedule of the number of patients to be treated. Our model will be used as sub-model in an agent-based simulation system aiming to optimise the use of resources in an emergency with power outages or brownouts. The results presented in this study can be treated as a benchmark for decision makers to estimate the performance of a dialysis clinic or centre based on the amount of electricity and water needed and available.","PeriodicalId":266151,"journal":{"name":"Int. J. Simul. Process. Model.","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Energy consumption models in dialysis clinics for agent-based decision support\",\"authors\":\"Stefan Wandler, S. Bai, W. Raskob\",\"doi\":\"10.1504/ijspm.2020.10028741\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes an approach to predict the consumptions of water and power in dialysis clinics by simulating the internal processes. Better understanding is essential to prevent and mitigate adverse health impact on patients. Our methods are based on literature about dialysis processes and dialysis clinics, which are first-hand technical reports. The nonlinear model comprises the energy consumption of the technical systems together with their working schedules and the time schedule of the number of patients to be treated. Our model will be used as sub-model in an agent-based simulation system aiming to optimise the use of resources in an emergency with power outages or brownouts. The results presented in this study can be treated as a benchmark for decision makers to estimate the performance of a dialysis clinic or centre based on the amount of electricity and water needed and available.\",\"PeriodicalId\":266151,\"journal\":{\"name\":\"Int. J. Simul. Process. Model.\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Simul. Process. Model.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijspm.2020.10028741\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Simul. Process. Model.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijspm.2020.10028741","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Energy consumption models in dialysis clinics for agent-based decision support
This paper describes an approach to predict the consumptions of water and power in dialysis clinics by simulating the internal processes. Better understanding is essential to prevent and mitigate adverse health impact on patients. Our methods are based on literature about dialysis processes and dialysis clinics, which are first-hand technical reports. The nonlinear model comprises the energy consumption of the technical systems together with their working schedules and the time schedule of the number of patients to be treated. Our model will be used as sub-model in an agent-based simulation system aiming to optimise the use of resources in an emergency with power outages or brownouts. The results presented in this study can be treated as a benchmark for decision makers to estimate the performance of a dialysis clinic or centre based on the amount of electricity and water needed and available.