The Experts below are selected from a list of 729 Experts worldwide ranked by ideXlab platform
Jingcheng Wang - One of the best experts on this subject based on the ideXlab platform.
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Soot Blowing Optimization for Frequency in Economizers to Improve Boiler Performance in Coal-Fired Power Plant
Energies, 2019Co-Authors: Yuanhao Shi, Jie Wen, Pang Xiaoqiong, Jianfang Jia, Jianchao Zeng, Cui Fangshu, Jingcheng WangAbstract:Because of the present ineffective method of Soot Blowing on a boiler’s heating surface in a coal-fired power plant, and to improve the economic benefit of the boiler in the power plant, weigh the improvement of boiler efficiency and steam loss brought by Soot Blowing, and ensure the safe operation of the unit, an optimization model of Soot Blowing on the boiler’s heating surface is established. Taking the economizer of the 300 MW coal-fired power plant unit as the research object, the measurement data and basic thermodynamic calculation data of the Distributed Control System (DCS) of the thermal power plant are used to calculate the fouling rate of the heated surface in real time. By analyzing the multi-group fouling rate under the same working conditions, the incremental distribution of the same measuring point at different times is obtained, and the expectation is obtained according to the distribution curve. The state of heating of the heated surface at a time in the future is predicted by the known initial cleaning state. By analyzing the trend of the fouling rate and combining the Soot Blowing optimization model, a set of Soot Blowing optimization strategies are proposed. The method proposed in this manuscript can be applied to the guidance of boiler Soot Blowing operation.
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Optimization of Soot Blowing of Coal-fired Boilers Based on UKF Predicted Health Status
2019 3rd International Symposium on Autonomous Systems (ISAS), 2019Co-Authors: Yanting Wang, Jingcheng WangAbstract:Aiming at the problems of boiler heating surface from clean to produce ash and slag, the heat transfer efficiency of boiler is reduced. With the cleanliness factor as the monitoring index, a real-time Soot Blowing prediction method based on unscented Kalman filter algorithm is proposed. The cleanliness factor degradation data was analyzed by double exponential function fitting, and the model parameters were updated by the unscented Kalman filter algorithm, and the future trend of the cleanliness factor was predicted. At the same time, a Soot-Blowing optimization model with the largest heat transfer per unit time is proposed to further optimize the Soot Blowing time. Taking the cleanliness factor data of a economizer as an example, by comparing with the extended Kalman filter algorithm, it is found that the proposed method can predict the Soot Blowing time more accurately, and the calculation of the Soot-Blowing optimization example is carried out to verify the feasibility of the proposed optimization model.
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An Optimization Study on Soot-Blowing of Air Preheaters in Coal-Fired Power Plant Boilers
Energies, 2019Co-Authors: Yuanhao Shi, Jie Wen, Cui Fangshu, Jingcheng WangAbstract:This paper presents a comprehensive approach for optimization of Soot-Blowing of air preheaters in a coal-fired power plant boiler. In the method, modeling of the cleanliness factor is firstly proposed to monitor the ash deposition status of the air preheaters. Then, the statistical fitting of the ash fouling status is subsequently obtained to analyze the ash fouling dynamics and assessment of optimized Soot-Blowing strategies. Soot-Blowing strategies are finally developed to optimize the steam consumption and heat transfer efficiency. Our methods can achieve the fouling monitoring and Soot-Blowing optimization of air preheater (APH) by using the existing monitoring data, not requiring additional special instruments and complex computing systems. The methodology is validated with the actual operating data of a 300 MW coal-fired power plant boiler. The results show the effectiveness of the proposed method. It can be used for the Soot-Blowing optimization in most coal-fired power plant boiler with air preheaters.
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Preventive Soot Blowing Strategy Based on State of Health Prediction for Coal-fired Power Plant Boiler
2018 37th Chinese Control Conference (CCC), 2018Co-Authors: Xiaoqiong Pang, Jianchao Zeng, Jingcheng WangAbstract:This paper seeks the optimization of Soot-Blowing operations for heat transfer surfaces in coal- fired power plant boiler. A preventive Soot Blowing strategy based on state of health prediction for heat transfer surface was proposed. The average state of health of heat transfer surface was forecasted as the threshold to draft preventive Soot Blowing strategy. According to the theory of renewal process, an optimization model with the system prediction interval and the threshold of preventive Soot Blowing operation as the optimization variables and minimize average energy losses as the target function was established. By using Particle Swarm Optimization (PSO), the optimal preventive cycle and Soot-Blowing threshold were obtained, and the long-run average cost rate was the lowest. The model is validated with experiment data of a 300MW coal-fired power plant boiler and the parameters of prediction model are obtained. The results can verify the feasibility of proposed strategy. It can be used as the guide for the optimization of Soot Blowing in coal-fired power plant to improve the energy conservation level.
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On-line monitoring of ash fouling and Soot-Blowing optimization for convective heat exchanger in coal-fired power plant boiler
Applied Thermal Engineering, 2015Co-Authors: Yuanhao Shi, Jingcheng Wang, Liu ZhengfengAbstract:Abstract This paper presented a comprehensive approach of on-line monitoring and optimization for the Soot-Blowing system in coal-fired power plant boilers. Due to ash fouling monitoring of heat transfer surfaces of the boiler based on dynamic mass and energy balance method, on-line calculation of boiler thermal efficiency and soft measurements for gas flow rate at the double breezing tail and steam flow rate of reheaters, the performance of boiler's Soot-Blowing system can be evaluated on-line. And then, the suitable Soot-Blowing strategies are developed for Soot-Blowing frequencies and duration optimization. Monitoring results and analysis of an experimental application are given to illustrate the proposed methodologies. The methods proposed in this paper can be applied to state assessment and guidance of Soot-Blowing operation of boiler's Soot-Blowing system in order to achieve the purpose of energy conservation, without demanding special instruments or complex computing systems.
Luis I Diez - One of the best experts on this subject based on the ideXlab platform.
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towards Soot Blowing optimization in superheaters
Applied Thermal Engineering, 2013Co-Authors: Enrique Teruel, Luis I DiezAbstract:Abstract This paper seeks the optimization of steam consumptions dedicated to ash removal in large-sized superheaters operating at coal-fired utility boilers. The methodology consists of the design of a thermal model aiming at the real-time calculation of the fouling rates, the statistical fitting of the computed rates to obtain their time evolution and the assessment of optimized Soot-Blowing manoeuvres. Fouling rates are estimated by means of global thermal resistances, since local deposition is not feasible from available, standard measurements. The methodology is applied to the upper superheaters of a selected 350 MWe utility boiler, where significant steam rates are actually consumed. The results from the comparison of the heat transfer gains in this case-study show that energy savings can be attained by adopting new Soot-Blowing schedules in the plant. The methodology can be easily implemented in other coal-fired utility boilers, without demanding special instrumentation or computation requirements.
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Soft-computing models for Soot-Blowing optimization in coal-fired utility boilers
Applied Soft Computing, 2011Co-Authors: B. Peña, Enrique Teruel, Luis I DiezAbstract:Fouling and slagging are classical difficulties in pulverized fuel utility boilers, which cause important degradation and dramatic reduction of efficiency. Current cleaning devices, traditionally based on prefixed Soot-Blowing manoeuvres, mitigate the problem only partially and offers clear optimization possibilities. But the development of predictive control is far from easy: Soot-Blowing represents a significant fraction of efficiency, the effectiveness has an intrinsic level of randomness and the fouling dynamics involves nonlinear feedback loops. The complexity of the phenomenon makes not applicable theoretical models or statistical analysis. The problem requires the application of alternative methodologies as expert systems or soft-computing based techniques. The present paper aims to develop a probabilistic model to predict the effectiveness of Soot-Blowing based in Artificial Neural Networks and Adaptive Neuro-Fuzzy Inference Systems. The validity of the model has been illustrated in a real case-study boiler, a 350MW"e Spanish power station. Training and test data for these models are provided by a monitoring system based on heat-flux measurements in the furnace water-walls. For evaluation and comparison purposes, the quality of prediction obtained for the mentioned algorithms is analyzed in terms of performance indices. The connection weight approach reveals the relative importance of input variables in each soft-computing model. Finally, the integration of these models into an advisory tool is discussed.
Yuanhao Shi - One of the best experts on this subject based on the ideXlab platform.
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Soot Blowing Optimization for Frequency in Economizers to Improve Boiler Performance in Coal-Fired Power Plant
Energies, 2019Co-Authors: Yuanhao Shi, Jie Wen, Pang Xiaoqiong, Jianfang Jia, Jianchao Zeng, Cui Fangshu, Jingcheng WangAbstract:Because of the present ineffective method of Soot Blowing on a boiler’s heating surface in a coal-fired power plant, and to improve the economic benefit of the boiler in the power plant, weigh the improvement of boiler efficiency and steam loss brought by Soot Blowing, and ensure the safe operation of the unit, an optimization model of Soot Blowing on the boiler’s heating surface is established. Taking the economizer of the 300 MW coal-fired power plant unit as the research object, the measurement data and basic thermodynamic calculation data of the Distributed Control System (DCS) of the thermal power plant are used to calculate the fouling rate of the heated surface in real time. By analyzing the multi-group fouling rate under the same working conditions, the incremental distribution of the same measuring point at different times is obtained, and the expectation is obtained according to the distribution curve. The state of heating of the heated surface at a time in the future is predicted by the known initial cleaning state. By analyzing the trend of the fouling rate and combining the Soot Blowing optimization model, a set of Soot Blowing optimization strategies are proposed. The method proposed in this manuscript can be applied to the guidance of boiler Soot Blowing operation.
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An Optimization Study on Soot-Blowing of Air Preheaters in Coal-Fired Power Plant Boilers
Energies, 2019Co-Authors: Yuanhao Shi, Jie Wen, Cui Fangshu, Jingcheng WangAbstract:This paper presents a comprehensive approach for optimization of Soot-Blowing of air preheaters in a coal-fired power plant boiler. In the method, modeling of the cleanliness factor is firstly proposed to monitor the ash deposition status of the air preheaters. Then, the statistical fitting of the ash fouling status is subsequently obtained to analyze the ash fouling dynamics and assessment of optimized Soot-Blowing strategies. Soot-Blowing strategies are finally developed to optimize the steam consumption and heat transfer efficiency. Our methods can achieve the fouling monitoring and Soot-Blowing optimization of air preheater (APH) by using the existing monitoring data, not requiring additional special instruments and complex computing systems. The methodology is validated with the actual operating data of a 300 MW coal-fired power plant boiler. The results show the effectiveness of the proposed method. It can be used for the Soot-Blowing optimization in most coal-fired power plant boiler with air preheaters.
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Optimization of Boiler Soot Blowing Based on Hamilton-Jacobi-Bellman Equation
IEEE Access, 2019Co-Authors: Jie Wen, Yuanhao Shi, Pang Xiaoqiong, Jianfang Jia, Jianchao ZengAbstract:In this paper, the optimization of the boiler Soot Blowing is investigated based on the Hamilton-Jacobi-Bellman (HJB) equation and from the standpoint of the equipment health management. The mathematical model of the boiler Soot Blowing is built by a Markov process with two modes: Soot deposition mode and Soot Blowing mode. In order to obtain the optimal Soot Blowing strategies via the HJB method, a cost function is constructed according to the proposed boiler Soot Blowing model. Considering the solution's existence of the HJB equation, the elementary properties of the value function are described and proved. It is difficult to solve the HJB equation analytically, so Kushner's method is applied to get the numerical solution of the HJB equation. Moreover, the sensitivity analyses for the effects of different parameters are shown via a set of numerical simulations.
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Optimal Soot Blowing Strategies in Boiler Systems with Variable Steam Flow
2018 37th Chinese Control Conference (CCC), 2018Co-Authors: Jie Wen, Yuanhao Shi, Pang Xiaoqiong, Jianfang Jia, Jianchao ZengAbstract:The optimal Soot Blowing strategies of boiler systems with variable steam flow is investigated based on Hamilton-Jacobi-Bellman (HJB) equation in this paper. A continuous time Markov process with Soot deposition mode and Soot Blowing mode is constructed as the mathematical model of boiler systems. In order to obtain the optimal Soot Blowing strategies, we propose a cost function based on the constructed boiler model, and derive the corresponding value function, which is the solution of HJB equation. In particular, the elementary properties of value function are described and proved strictly. Considering the difficulty of solving the HJB equation analytically, Kushner's method is applied to get the numerical solution of HJB equation, and the experiment results are analyzed.
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On-line monitoring of ash fouling and Soot-Blowing optimization for convective heat exchanger in coal-fired power plant boiler
Applied Thermal Engineering, 2015Co-Authors: Yuanhao Shi, Jingcheng Wang, Liu ZhengfengAbstract:Abstract This paper presented a comprehensive approach of on-line monitoring and optimization for the Soot-Blowing system in coal-fired power plant boilers. Due to ash fouling monitoring of heat transfer surfaces of the boiler based on dynamic mass and energy balance method, on-line calculation of boiler thermal efficiency and soft measurements for gas flow rate at the double breezing tail and steam flow rate of reheaters, the performance of boiler's Soot-Blowing system can be evaluated on-line. And then, the suitable Soot-Blowing strategies are developed for Soot-Blowing frequencies and duration optimization. Monitoring results and analysis of an experimental application are given to illustrate the proposed methodologies. The methods proposed in this paper can be applied to state assessment and guidance of Soot-Blowing operation of boiler's Soot-Blowing system in order to achieve the purpose of energy conservation, without demanding special instruments or complex computing systems.
Jianchao Zeng - One of the best experts on this subject based on the ideXlab platform.
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Soot Blowing Optimization for Frequency in Economizers to Improve Boiler Performance in Coal-Fired Power Plant
Energies, 2019Co-Authors: Yuanhao Shi, Jie Wen, Pang Xiaoqiong, Jianfang Jia, Jianchao Zeng, Cui Fangshu, Jingcheng WangAbstract:Because of the present ineffective method of Soot Blowing on a boiler’s heating surface in a coal-fired power plant, and to improve the economic benefit of the boiler in the power plant, weigh the improvement of boiler efficiency and steam loss brought by Soot Blowing, and ensure the safe operation of the unit, an optimization model of Soot Blowing on the boiler’s heating surface is established. Taking the economizer of the 300 MW coal-fired power plant unit as the research object, the measurement data and basic thermodynamic calculation data of the Distributed Control System (DCS) of the thermal power plant are used to calculate the fouling rate of the heated surface in real time. By analyzing the multi-group fouling rate under the same working conditions, the incremental distribution of the same measuring point at different times is obtained, and the expectation is obtained according to the distribution curve. The state of heating of the heated surface at a time in the future is predicted by the known initial cleaning state. By analyzing the trend of the fouling rate and combining the Soot Blowing optimization model, a set of Soot Blowing optimization strategies are proposed. The method proposed in this manuscript can be applied to the guidance of boiler Soot Blowing operation.
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Optimization of Boiler Soot Blowing Based on Hamilton-Jacobi-Bellman Equation
IEEE Access, 2019Co-Authors: Jie Wen, Yuanhao Shi, Pang Xiaoqiong, Jianfang Jia, Jianchao ZengAbstract:In this paper, the optimization of the boiler Soot Blowing is investigated based on the Hamilton-Jacobi-Bellman (HJB) equation and from the standpoint of the equipment health management. The mathematical model of the boiler Soot Blowing is built by a Markov process with two modes: Soot deposition mode and Soot Blowing mode. In order to obtain the optimal Soot Blowing strategies via the HJB method, a cost function is constructed according to the proposed boiler Soot Blowing model. Considering the solution's existence of the HJB equation, the elementary properties of the value function are described and proved. It is difficult to solve the HJB equation analytically, so Kushner's method is applied to get the numerical solution of the HJB equation. Moreover, the sensitivity analyses for the effects of different parameters are shown via a set of numerical simulations.
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Preventive Soot Blowing Strategy Based on State of Health Prediction for Coal-fired Power Plant Boiler
2018 37th Chinese Control Conference (CCC), 2018Co-Authors: Xiaoqiong Pang, Jianchao Zeng, Jingcheng WangAbstract:This paper seeks the optimization of Soot-Blowing operations for heat transfer surfaces in coal- fired power plant boiler. A preventive Soot Blowing strategy based on state of health prediction for heat transfer surface was proposed. The average state of health of heat transfer surface was forecasted as the threshold to draft preventive Soot Blowing strategy. According to the theory of renewal process, an optimization model with the system prediction interval and the threshold of preventive Soot Blowing operation as the optimization variables and minimize average energy losses as the target function was established. By using Particle Swarm Optimization (PSO), the optimal preventive cycle and Soot-Blowing threshold were obtained, and the long-run average cost rate was the lowest. The model is validated with experiment data of a 300MW coal-fired power plant boiler and the parameters of prediction model are obtained. The results can verify the feasibility of proposed strategy. It can be used as the guide for the optimization of Soot Blowing in coal-fired power plant to improve the energy conservation level.
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Optimal Soot Blowing Strategies in Boiler Systems with Variable Steam Flow
2018 37th Chinese Control Conference (CCC), 2018Co-Authors: Jie Wen, Yuanhao Shi, Pang Xiaoqiong, Jianfang Jia, Jianchao ZengAbstract:The optimal Soot Blowing strategies of boiler systems with variable steam flow is investigated based on Hamilton-Jacobi-Bellman (HJB) equation in this paper. A continuous time Markov process with Soot deposition mode and Soot Blowing mode is constructed as the mathematical model of boiler systems. In order to obtain the optimal Soot Blowing strategies, we propose a cost function based on the constructed boiler model, and derive the corresponding value function, which is the solution of HJB equation. In particular, the elementary properties of value function are described and proved strictly. Considering the difficulty of solving the HJB equation analytically, Kushner's method is applied to get the numerical solution of HJB equation, and the experiment results are analyzed.
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Study on optimization of Soot Blowing based on monitoring model of coal-fired power station Soot accumulation
2018 Chinese Automation Congress (CAC), 2018Co-Authors: Qiang Li, Xiaolong Chen, Jianchao ZengAbstract:In view of the present unreasonable situation about the Blowing way of boiler heating surface, an optimized model of Soot Blowing was established to improve the economic benefit of the unit, after weighing the improvement of boiler efficiency and steam loss caused by ash Blowing and ensuring the safe operation of the unit. The measured data of thermal power plant DCS system and the basic thermodynamic calculation data was adopted, and the contamination rate of heating surface was calculated in real time. The fitted curve was taken by taking the expected data from multiple data sets at the same measuring point from the statistical point of view, combining the optimization model of the heating surface to solve the optimal Soot Blowing cycle in the boiler economizer of 300 MW coal-fired power plant, which was taken as the research object.
Enrique Teruel - One of the best experts on this subject based on the ideXlab platform.
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towards Soot Blowing optimization in superheaters
Applied Thermal Engineering, 2013Co-Authors: Enrique Teruel, Luis I DiezAbstract:Abstract This paper seeks the optimization of steam consumptions dedicated to ash removal in large-sized superheaters operating at coal-fired utility boilers. The methodology consists of the design of a thermal model aiming at the real-time calculation of the fouling rates, the statistical fitting of the computed rates to obtain their time evolution and the assessment of optimized Soot-Blowing manoeuvres. Fouling rates are estimated by means of global thermal resistances, since local deposition is not feasible from available, standard measurements. The methodology is applied to the upper superheaters of a selected 350 MWe utility boiler, where significant steam rates are actually consumed. The results from the comparison of the heat transfer gains in this case-study show that energy savings can be attained by adopting new Soot-Blowing schedules in the plant. The methodology can be easily implemented in other coal-fired utility boilers, without demanding special instrumentation or computation requirements.
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Soft-computing models for Soot-Blowing optimization in coal-fired utility boilers
Applied Soft Computing, 2011Co-Authors: B. Peña, Enrique Teruel, Luis I DiezAbstract:Fouling and slagging are classical difficulties in pulverized fuel utility boilers, which cause important degradation and dramatic reduction of efficiency. Current cleaning devices, traditionally based on prefixed Soot-Blowing manoeuvres, mitigate the problem only partially and offers clear optimization possibilities. But the development of predictive control is far from easy: Soot-Blowing represents a significant fraction of efficiency, the effectiveness has an intrinsic level of randomness and the fouling dynamics involves nonlinear feedback loops. The complexity of the phenomenon makes not applicable theoretical models or statistical analysis. The problem requires the application of alternative methodologies as expert systems or soft-computing based techniques. The present paper aims to develop a probabilistic model to predict the effectiveness of Soot-Blowing based in Artificial Neural Networks and Adaptive Neuro-Fuzzy Inference Systems. The validity of the model has been illustrated in a real case-study boiler, a 350MW"e Spanish power station. Training and test data for these models are provided by a monitoring system based on heat-flux measurements in the furnace water-walls. For evaluation and comparison purposes, the quality of prediction obtained for the mentioned algorithms is analyzed in terms of performance indices. The connection weight approach reveals the relative importance of input variables in each soft-computing model. Finally, the integration of these models into an advisory tool is discussed.