A dynamic mathematical model of an ultra-supercritical coal fired once-through boiler-turbine unit. (1st March 2017)
- Record Type:
- Journal Article
- Title:
- A dynamic mathematical model of an ultra-supercritical coal fired once-through boiler-turbine unit. (1st March 2017)
- Main Title:
- A dynamic mathematical model of an ultra-supercritical coal fired once-through boiler-turbine unit
- Authors:
- Fan, He
Zhang, Yu-fei
Su, Zhi-gang
Wang, Ben - Abstract:
- Graphical abstract: Highlights: A mathematical model of an ultra-supercritical unit is developed. The analysis of open-loop experiments is described. Parameter identification based on immune genetic algorithm is presented. The closed-loop validation is performed and compared with the previous study. Abstract: It is challenging and interesting to establish a precise dynamic model of an OTB (once-through boiler) power plant unit in order to meet large scale load demands from the power grid. This study proposes to establish such a dynamic mathematical model of an ultra-supercritical OTB unit under dry operating conditions. More precisely, the dynamic model structure was derived from mass and energy conservation laws as well as thermodynamic principles under some reasonable simplifications and assumptions. Then an IGA (immune genetic algorithm) was improved to identify the parameters, combined with running data. After this, to further enhance model performance, the dynamic mathematical model was extended to be the one with different sets of parameters and functions under different monotonous load ranges. Additionally, open- and closed-loop experiments were conducted in order to further validate the developed model. The experimental results show that the model outputs can approach the actual running data over a wide operating range with appropriate accuracy. More importantly, the dynamic model captures the essential dynamic characteristics of the unit. Therefore, the model can beGraphical abstract: Highlights: A mathematical model of an ultra-supercritical unit is developed. The analysis of open-loop experiments is described. Parameter identification based on immune genetic algorithm is presented. The closed-loop validation is performed and compared with the previous study. Abstract: It is challenging and interesting to establish a precise dynamic model of an OTB (once-through boiler) power plant unit in order to meet large scale load demands from the power grid. This study proposes to establish such a dynamic mathematical model of an ultra-supercritical OTB unit under dry operating conditions. More precisely, the dynamic model structure was derived from mass and energy conservation laws as well as thermodynamic principles under some reasonable simplifications and assumptions. Then an IGA (immune genetic algorithm) was improved to identify the parameters, combined with running data. After this, to further enhance model performance, the dynamic mathematical model was extended to be the one with different sets of parameters and functions under different monotonous load ranges. Additionally, open- and closed-loop experiments were conducted in order to further validate the developed model. The experimental results show that the model outputs can approach the actual running data over a wide operating range with appropriate accuracy. More importantly, the dynamic model captures the essential dynamic characteristics of the unit. Therefore, the model can be feasible and applicable for simulation analysis and testing control algorithms. … (more)
- Is Part Of:
- Applied energy. Volume 189(2017)
- Journal:
- Applied energy
- Issue:
- Volume 189(2017)
- Issue Display:
- Volume 189, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 189
- Issue:
- 2017
- Issue Sort Value:
- 2017-0189-2017-0000
- Page Start:
- 654
- Page End:
- 666
- Publication Date:
- 2017-03-01
- Subjects:
- Once-through boiler -- IGA -- Mathematical model -- Dynamic -- Power plant
Power (Mechanics) -- Periodicals
Energy conservation -- Periodicals
Energy conversion -- Periodicals
621.042 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03062619 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.apenergy.2016.11.074 ↗
- Languages:
- English
- ISSNs:
- 0306-2619
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1572.300000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 1806.xml