{"title":"基于Flownex®仿真环境和人工智能的燃煤锅炉控制性能优化","authors":"L. V. D. Westhuizen, I. Gorlach","doi":"10.17159/2309-8988/2019/V37A2","DOIUrl":null,"url":null,"abstract":"ABSTRACT The inherent variability of renewable energy sources, pump storage plants and combined cycle gas turbines implies that coal-fired plants designed for continuous base load generation in South Africa must now be used for variable load. This has a negative effect on the overall efficiency and life expectancy of these plants. The challenge is, therefore, to balance the network demands with the power station operation, its thermal efficiency, availability and extended plant life expectancy. The focus of the current research is to monitor and optimise the efficiency of the boiler operation and control through modelling of the boiler subsystems during transient states. Flownex® Simulation Environment was used to model a generic boiler and a boiler control system in order to simulate thermo-fluid processes and critical boiler controllers. The developed model was evaluated based on plant data and optimised afterwards by means of PID controllers and Machine Learning algorithms. The process parameters obtained from the Machine Learning algorithms outperform that of the PID controllers for the selected controllers, such as: boiler load control and steam pressure control. Additional keywords: Power generation, boiler control, boiler modelling.","PeriodicalId":299970,"journal":{"name":"R&D Journal","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance Optimisation of Coal-fired Boiler Control using Flownex® Simulation Environment and AI\",\"authors\":\"L. V. D. Westhuizen, I. Gorlach\",\"doi\":\"10.17159/2309-8988/2019/V37A2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT The inherent variability of renewable energy sources, pump storage plants and combined cycle gas turbines implies that coal-fired plants designed for continuous base load generation in South Africa must now be used for variable load. This has a negative effect on the overall efficiency and life expectancy of these plants. The challenge is, therefore, to balance the network demands with the power station operation, its thermal efficiency, availability and extended plant life expectancy. The focus of the current research is to monitor and optimise the efficiency of the boiler operation and control through modelling of the boiler subsystems during transient states. Flownex® Simulation Environment was used to model a generic boiler and a boiler control system in order to simulate thermo-fluid processes and critical boiler controllers. The developed model was evaluated based on plant data and optimised afterwards by means of PID controllers and Machine Learning algorithms. The process parameters obtained from the Machine Learning algorithms outperform that of the PID controllers for the selected controllers, such as: boiler load control and steam pressure control. Additional keywords: Power generation, boiler control, boiler modelling.\",\"PeriodicalId\":299970,\"journal\":{\"name\":\"R&D Journal\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"R&D Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17159/2309-8988/2019/V37A2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"R&D Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17159/2309-8988/2019/V37A2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance Optimisation of Coal-fired Boiler Control using Flownex® Simulation Environment and AI
ABSTRACT The inherent variability of renewable energy sources, pump storage plants and combined cycle gas turbines implies that coal-fired plants designed for continuous base load generation in South Africa must now be used for variable load. This has a negative effect on the overall efficiency and life expectancy of these plants. The challenge is, therefore, to balance the network demands with the power station operation, its thermal efficiency, availability and extended plant life expectancy. The focus of the current research is to monitor and optimise the efficiency of the boiler operation and control through modelling of the boiler subsystems during transient states. Flownex® Simulation Environment was used to model a generic boiler and a boiler control system in order to simulate thermo-fluid processes and critical boiler controllers. The developed model was evaluated based on plant data and optimised afterwards by means of PID controllers and Machine Learning algorithms. The process parameters obtained from the Machine Learning algorithms outperform that of the PID controllers for the selected controllers, such as: boiler load control and steam pressure control. Additional keywords: Power generation, boiler control, boiler modelling.