煤气与热力2026，Vol.46Issue(3)：50-55,6.
改进灰狼优化算法天然气余压发电参数优化
Parameter Optimization for Natural Gas Residual Pressure Power Generation Based on Improved Grey Wolf Optimization Algorithm
蒋林 1王弘涛 1丁辉 2朱静东 2张艺馨2
作者信息
- 1. 西南石油大学电气信息学院,四川成都 610500
- 2. 长庆油田(榆林)油气有限公司,陕西榆林 719000
- 折叠
摘要
Abstract
For natural gas residual pressure power gen-eration systems under high pressure differential ratio conditions,the multi-stage expansion power generation mode is generally adopted.However,improper selec-tion of intermediate pressure and fluctuations in the nature gas inlet pressure can reduce the efficiency of residual pressure power generation,and even compro-mise the stability of the power generation system.To address this,a parameter optimization method for natu-ral gas residual pressure power generation under high pressure differential ratio conditions based on a.multi-strategy improved Grey Wolf Optimizer(GWO)algorithm is proposed.Based on actual cases,under steady-state operating conditions,the optimization errors for two-stage and three-stage expansion are only 0.041 W and 30 W,respectively,verifying the method's effectiveness.Furthermore,simulation experiments were conducted under variable operating conditions using the proposed algorithm;the errors of two-stage expansion under the original process and the changed operating conditions are only 0.053 W and 0.000 55 W respectively,and those of three-stage expansion are only 3.7 W and 7.8 W respectively,which confirms that the proposed algorithm has strong adaptability to operating conditions.Overall,the proposed multi-strategy improved GWO-based parameter optimi-zation method yields small optimization errors under both steady-state and variable operating conditions,demonstrating excellent effectiveness and robust adapt-ability.关键词
多策略改进灰狼优化算法/天然气余压发电/高压差比/多级膨胀/中间压力Key words
multi-strategy improved Grey Wolf Optimi-zation algorithm/natural gas residual pressure power generation/high pressure difference ratio/multi-stage expansion/intermediate pressure分类
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蒋林,王弘涛,丁辉,朱静东,张艺馨..改进灰狼优化算法天然气余压发电参数优化[J].煤气与热力,2026,46(3):50-55,6.
