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Short-term Scheduling of Steam Power System in Iron and Steel Industry under Time-of-use Power Price 被引量:7

Short-term Scheduling of Steam Power System in Iron and Steel Industry under Time-of-use Power Price
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摘要 A generalized formulation for short-term scheduling of steam power system in iron and steel industry under the time-of-use(TOU)power price was presented,with minimization of total operational cost including fuel cost,equipment maintenance cost and the charge of exchange power with main grid.The model took into account the varying nature of surplus byproduct gas flows,several practical technical constraints and the impact of TOU power price.All major types of utility equipments,involving boilers,steam turbines,combined heat and power(CHP)units,and waste heat and energy recovery generators(WHERG),were separately modeled using thermodynamic balance equations and regression method.In order to solve this complex nonlinear optimization model,a new improved particle swarm optimization(IPSO)algorithm was proposed by incorporating time-variant parameters,a selfadaptive mutation scheme and efficient constraint handling strategies.Finally,a case study for a real industrial example was used for illustrating the model and validating the effectiveness of the proposed approach. A generalized formulation for short-term scheduling of steam power system in iron and steel industry under the time-of-use(TOU)power price was presented,with minimization of total operational cost including fuel cost,equipment maintenance cost and the charge of exchange power with main grid.The model took into account the varying nature of surplus byproduct gas flows,several practical technical constraints and the impact of TOU power price.All major types of utility equipments,involving boilers,steam turbines,combined heat and power(CHP)units,and waste heat and energy recovery generators(WHERG),were separately modeled using thermodynamic balance equations and regression method.In order to solve this complex nonlinear optimization model,a new improved particle swarm optimization(IPSO)algorithm was proposed by incorporating time-variant parameters,a selfadaptive mutation scheme and efficient constraint handling strategies.Finally,a case study for a real industrial example was used for illustrating the model and validating the effectiveness of the proposed approach.
出处 《Journal of Iron and Steel Research(International)》 SCIE EI CAS CSCD 2015年第9期795-803,共9页 钢铁研究学报(英文版)
基金 Sponsored by National Natural Science Foundation of China(51304053) International Science and Technology Cooperation Program of China(2013DFA10810)
关键词 short-term optimization byproduct gas distribution steam and power dispatch CHP iron and steel industry time-of-use power price short-term optimization byproduct gas distribution steam and power dispatch CHP iron and steel industry time-of-use power price
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