Influence of constraints on optimal price of blending coal: by particle swarm optimization algorithm
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Influence of constraints on optimal price of blending coal: by particle swarm optimization algorithm
Thermal Power GenerationVol. 46, Issue 12, Pages: 99-104(2017)
作者机构:
西安热工研究院有限公司
作者简介:
基金信息:
DOI:
CLC:F426.21;F764.1
Published:2017
稿件说明:
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ZHAO Yue, MENG Yi, LI Renyi. Influence of constraints on optimal price of blending coal: by particle swarm optimization algorithm[J]. Thermal power generation, 2017, 46(12): 99-104.
DOI:
ZHAO Yue, MENG Yi, LI Renyi. Influence of constraints on optimal price of blending coal: by particle swarm optimization algorithm[J]. Thermal power generation, 2017, 46(12): 99-104.DOI:
Influence of constraints on optimal price of blending coal: by particle swarm optimization algorithm
Coal blending is a process of optimization under all constraints.The influences of different constraints on the objective function are different.To analyze the effects of several constraints including coal calorific value
volatile
moisture
ash and sulfur content on the optimal price of coal blending
an optimizing model was established by using particle swarm optimization algorithm in this paper.Moreover
the effects of adjusting the constraint range of calorific value and volatile content of the coal on coal blending economy were analyzed in detail.The results show that
the influence of each constraint on the blending coal's price meets the piecewise linear function
the economy of range constraint is determined by the slope of the function
the smaller absolute value of the slope has the higher economy.Setting reasonable constraints for coal blending can further improve the economy of blending coal and satisfy the requirement of coal property.The research methods in this paper can provide reference for constraints design of coal blending
it is helpful for thermal power plants to obtain more economical solution of coal blending.