The Energy-Saving and Emission Reduction Generation Dispatching Based on Particle Swarm Optimization

2012 ◽  
Vol 459 ◽  
pp. 99-102 ◽  
Author(s):  
Yong Hua Li ◽  
Jun Wang ◽  
Wei Ping Yan
Keyword(s):  
Particle Swarm Optimization ◽  
Energy Saving ◽  
Power Supply ◽  
Coal Combustion ◽  
Emission Reduction ◽  
Consumption Rate ◽  
Particle Swarm ◽  
Optimization Method ◽  
Coal Consumption ◽  
Swarm Optimization

Energy-saving and emission reduction is the based policy of China. Energy-saving dispatching is a new generation optimized method combined with the aim of energy-saving and emission reduction. At present, the trial energy-saving dispatching in some area evaluate energy-saving and emission reduction of coal combustion power generation according to power supply coal consumption rate only. But the power supply coal consumption rate can’t overall reflect the energy-saving and emission reduction effect of coal combustion power plant. This paper selects the power supply coal consumption rate, auxiliary power ratio, SO2 and NOx emission, EAF, net loss and water consumption as the energy-saving dispatching index, adopts particle swarm optimization method, carries the order integrate index, provides the reference for energy-saving dispatching.

The Integrated Evaluation Index of Energy-Saving and Emission Reduction Generation Dispatching

2011 ◽  
Vol 382 ◽  
pp. 56-59
Author(s):  
Yong Hua Li ◽  
Jun Wang ◽  
Wei Ping Yan
Keyword(s):  
Power Generation ◽  
Energy Saving ◽  
Power Supply ◽  
Coal Combustion ◽  
Emission Reduction ◽  
Evaluation System ◽  
Power Plants ◽  
Consumption Rate ◽  
Coal Consumption ◽  
Reduction Effect

In China, coal combustion to generate electric power is the primary method, the energy-saving and emission reduction is the urgent task. At present, the energy-saving dispatching trial method in some area evaluates energy-saving and emission reduction of coal combustion power generation according to power supply coal consumption rate only. But the power supply coal consumption rate can’t reflect the energy-saving and emission reduction effect of coal combustion power plant overall. For example, the same coal combustion unit, the coal consumption rate is difference when desulfuration system is operating or not; the coal consumption rate of the unit with SCR will be increased; the coal consumption rate of the air-cooled unit is higher than water-cooled unit; etc.. This paper considers synthetically coal consumption rate, pollution emission, water resource wastage, etc., establishes a integrated evaluation system, adopts factor analysis method, gets the integrated evaluation system and index of energy-saving and emission reduction of coal combustion power generation, evaluates energy-saving and emission reduction effect of 5 power plants reasonable. The results show that the index can reflect the energy-saving and emission reduction level of coal combustion power generation.

Emergy Analysis of Energy-Saving and Emission Reduction of Coal-Fired Generation

2012 ◽  
Vol 459 ◽  
pp. 110-113 ◽  
Author(s):  
Yong Hua Li ◽  
Jun Wang ◽  
Wei Ping Yan
Keyword(s):  
Energy Saving ◽  
Power Supply ◽  
Coal Combustion ◽  
Emission Reduction ◽  
Power Plants ◽  
Consumption Rate ◽  
Emergy Analysis ◽  
Analysis Method ◽  
Coal Consumption ◽  
Integrate Index

Coal-fired to generate electric power is the primary method in China and it occupies about 80% generation portions. Therefore, it is necessary to increase power generation efficiency and reduce related pollution in order to conserve energy and resources. In certain regions of China, energy saving oriented dispatch is under test, which only uses coal consumption rate for power supply as the indicator of energy saving. But coal consumption rate for power supply itself doesn’t show the whole picture of energy saving and emission reduction of coal combustion power plants. This paper selects the coal consumption for power supply, SO2 and NOx emission, EAF, net loss and water consumption as the energy-saving dispatching index, adopts emergy analysis method, carries the order integrate index, provides the reference for energy-saving dispatching.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

A novel sensor array and classifier optimization method of electronic nose based on enhanced quantum-behaved particle swarm optimization

Sensor Review ◽  
2014 ◽  
Vol 34 (3) ◽  
pp. 304-311 ◽  
Author(s):  
Pengfei Jia ◽  
Fengchun Tian ◽  
Shu Fan ◽  
Qinghua He ◽  
Jingwei Feng ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Wound Infection ◽  
Electronic Nose ◽  
Classification Accuracy ◽  
Sensor Array ◽  
Particle Swarm ◽  
Optimization Method ◽  
Support Vector ◽  
Swarm Optimization ◽  
Content Type

Purpose – The purpose of the paper is to propose a new optimization algorithm to realize a synchronous optimization of sensor array and classifier, to improve the performance of E-nose in the detection of wound infection. When an electronic nose (E-nose) is used to detect the wound infection, sensor array’s optimization and parameters’ setting of classifier have a strong impact on the classification accuracy. Design/methodology/approach – An enhanced quantum-behaved particle swarm optimization based on genetic algorithm, genetic quantum-behaved particle swarm optimization (G-QPSO), is proposed to realize a synchronous optimization of sensor array and classifier. The importance-factor (I-F) method is used to weight the sensors of E-nose by its degree of importance in classification. Both radical basis function network and support vector machine are used for classification. Findings – The classification accuracy of E-nose is the highest when the weighting coefficients of the I-F method and classifier’s parameters are optimized by G-QPSO. All results make it clear that the proposed method is an ideal optimization method of E-nose in the detection of wound infection. Research limitations/implications – To make the proposed optimization method more effective, the key point of further research is to enhance the classifier of E-nose. Practical implications – In this paper, E-nose is used to distinguish the class of wound infection; meanwhile, G-QPSO is used to realize a synchronous optimization of sensor array and classifier of E-nose. These are all important for E-nose to realize its clinical application in wound monitoring. Originality/value – The innovative concept improves the performance of E-nose in wound monitoring and paves the way for the clinical detection of E-nose.

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