Optimal Identification of Variable Resistance Coefficient of Heat Supply Network Based on Flow Measurement Points

doi:10.19596/j.cnki.1001-246x.8280

Abstract

Abstract:

With popularity of heating metering system, system can be adjusted according to the change of load, and the resistance coefficient of pipe network change. Optimal identification of variable resistance coefficient is an effective means to understand the real-time operation of heating network. We present an optimal identification method for variable resistance coefficient of heat supply network based on flow observation data. Genetic algorithm is used to solve the problem. Relative error of the identification results is less than 5% in practical verification example. It shows that the method can obtain variable resistance coefficient of heating network with high accuracy when only flow observation data is available. It can provide guidance for the operation and regulation of heating systems.

Key words: heating pipe network, no pressure measuring point, variable resistance coefficient, optimization identification, genetic algorithm

CLC Number:

TK323

Lijuan TU, Enze ZHOU, Xuefei WU, Qi YANG, Xuefeng DING. Optimal Identification of Variable Resistance Coefficient of Heat Supply Network Based on Flow Measurement Points[J]. Chinese Journal of Computational Physics, 2021, 38(4): 498-504.

Figures/Tables 11

References 13

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	参数类型	参数确定值
种群Population	种群类型Population type	双精度向量Double vector
	种群规模Population size	100
	初始种群生成函数Creation function	可行随机种群Feasible population
适应度比例Fitness scaling	适应尺度变换函数Scaling function	排序变换Rank
选择Selection	选择函数Selection function	随机均匀Stochastic uniform
复制Reproduction	精英个数Elite count	2
复制Reproduction	交叉比例Crossover fraction	0.8
变异Mutation	变异函数Mutation function	自适应Adaptive feasible
交叉Crossover	交叉函数Crossover function	分散交叉Scattered
停止准则Stop criteria	进化代数Generations	200
	停滞代数Stalls generations	50
	函数容差Function tolerance	10^-6

	参数类型	参数确定值
种群Population	种群类型Population type	双精度向量Double vector
	种群规模Population size	100
	初始种群生成函数Creation function	可行随机种群Feasible population
适应度比例Fitness scaling	适应尺度变换函数Scaling function	排序变换Rank
选择Selection	选择函数Selection function	随机均匀Stochastic uniform
复制Reproduction	精英个数Elite count	2
复制Reproduction	交叉比例Crossover fraction	0.8
变异Mutation	变异函数Mutation function	自适应Adaptive feasible
交叉Crossover	交叉函数Crossover function	分散交叉Scattered
停止准则Stop criteria	进化代数Generations	200
	停滞代数Stalls generations	50
	函数容差Function tolerance	10^-6

热力入口	设计阻力系数	搜索上限	搜索下限
1	49.36	39.98	62.19
2	49.36	39.98	62.19
3	49.36	39.98	62.19
4	24.68	21.22	29.86
5	43.55	35.28	54.87
6	43.55	35.28	54.87
7	43.55	35.28	54.87
8	43.55	35.28	54.87
9	24.68	21.22	29.86
供回水干管	0.42	0.38	0.48

热力入口	设计阻力系数	搜索上限	搜索下限
1	49.36	39.98	62.19
2	49.36	39.98	62.19
3	49.36	39.98	62.19
4	24.68	21.22	29.86
5	43.55	35.28	54.87
6	43.55	35.28	54.87
7	43.55	35.28	54.87
8	43.55	35.28	54.87
9	24.68	21.22	29.86
供回水干管	0.42	0.38	0.48

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