Equilibrium optimization for high efficiency and low pollution combustion of power-generation boilers using game differential evolution algorithm

ZHAO Minhua; HU Yi; LI Jin; WANG Yusheng; WU Rui; SONG Le

doi:10.11949/j.issn.0438-1157.20161480

您当前的位置：

首页 >

文章列表页 >

Equilibrium optimization for high efficiency and low pollution combustion of power-generation boilers using game differential evolution algorithm

更新时间：2025-12-10

- Equilibrium optimization for high efficiency and low pollution combustion of power-generation boilers using game differential evolution algorithm
- CIESC Journal Issue 6, Pages: 2455-2464(2017)
- 作者机构：
  
  1. 西安建筑科技大学信息与控制工程学院,陕西,西安,710055
  2. 西安艾贝尔科技发展有限公司,陕西,西安,710065
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20161480
  CLC： P273TK227.1
- Online First：05 June 2017，
  
  Published：05 June 2017
- 稿件说明：
移动端阅览
ZHAO Minhua, HU Yi, LI Jin, et al. Equilibrium optimization for high efficiency and low pollution combustion of power-generation boilers using game differential evolution algorithm[J]. CIESC Journal, 2017, (6): 2455-2464.
DOI：

ZHAO Minhua, HU Yi, LI Jin, et al. Equilibrium optimization for high efficiency and low pollution combustion of power-generation boilers using game differential evolution algorithm[J]. CIESC Journal, 2017, (6): 2455-2464. DOI： 10.11949/j.issn.0438-1157.20161480.

摘要

提高电站锅炉热效率，降低NOx等污染物的排放量是电站节能减排必须解决的问题。经过采用经量子遗传算法）QGA）优化参数后的最小二乘支持向量机（LSSVM-QGA）建立燃烧优化模型，预测的锅炉热效率和NOx排放量的平均相对误差分别达到了0.054%和1.229%，其预测精度及泛化能力均较优，有更强的适用性能。在此模型基础上，提出一种采用自适应缩放因子与交叉因子和共享函数机制的差分进化算法（DE），通过其演化博弈论中的NASH均衡，实现锅炉燃烧的多目标优化，结果表明，基于NASH均衡的优化方法可以得到操作变量的最优解集，能够更好地改善运行工况，最终可以实现削峰填谷，使电站锅炉保持一个稳定均衡的燃烧状态。

Abstract

Improving thermal efficiency and reducing pollutant emissions such as NOx is a critical problem to be solved for conservation and emission reduction in power plant energy. A combustion optimization model was established by quantum genetic algorithm (QGA) optimized least squares support vector machine (LSSVM-QGA). The model predicted boiler thermal efficiency and NOx emissions at average relative error of 0.054% and 1.229%

respectively

which demonstrated high prediction accuracy

generalization ability and applicability. Based on the model

a method of differential evolution algorithm (DE) of self-adaptive scaling/crossover factors and sharing function followed by evolutionary Nash equilibrium was proposed for multi-objective optimization of boiler's combustion. Results show that optimization method based on NASH equilibrium can get optimal set of solutions to operational variables

which improve operating conditions and keep power generation boiler at a stable equilibrium state of combustion.

关键词

Keywords

references

Views

216

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Multiple kernel least square support vector machine model for prediction of cement clinker lime content

New universal corresponding state equation for correlation and extrapolation of saturated vapor-liquid density

Optimization method of coal-based cooling, heating and power co-generation

Water quality prediction in wastewater treatment based on data decomposition and dung beetle optimized TCN-BiGRU/BiLSTM

Prediction of COD concentration in wastewater treatment plant effluent based on secondary decomposition and BiLSTM

Related Author

ZHAO Pengcheng

LIU Bin

GAO Wei

ZHAO Zhibiao

WANG Meiqi

QING Kang

WANG Erqi

YANG Zhen

Related Institution

Institute of Information Science and Engineering, Yanshan University

Key Laboratory for Special Fiber and Fiber Sensor of Hebei Province

Institute of Electrical Engineering, Yanshan University

Key Laboratory for Thermal Science and Power Engineering of Ministry of Education,Beijing Key Laboratory of CO2 Utilization and Reduction Technology, Tsinghua University

Southwest United Graduate School

⁰