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IPSO-TS算法在矿井通风网络风量优化中的应用研究

Application of IPSO-TS algorithm in air volume optimization of mine ventilation network

  • 摘要: 为了解决矿井通风网络中用风需求多变及通风能耗高等问题,以通风网络总功耗最低为目标函数,以矿井通风网络基础定律等为约束条件,建立通风网络非线性无约束优化模型,应用罚函数对模型进行改进。采用改进粒子群算法与禁忌搜索算法相结合的方法,以提高算法收敛速度与精度,能够避免陷入局部最优。应用该方法对改进模型进行求解,并以荣华一矿为研究对象进行仿真模拟,结果表明:该方法使通风网络总功耗降低43.27%,矿井各巷道风量能够满足需求,从而验证所采用方法的可行性及有效性。

     

    Abstract: In order to solve the problems of variable wind demand and high ventilation energy consumption in ventilation network of mine, by taking the minimum total power consumption of ventilation network as the objective function and the basic law of mine ventilation network as the constraint conditions, the nonlinear unconstrained optimization model of ventilation network was established. The improved particle swarm optimization algorithm combined with tabu search algorithm was proposed to improve the convergence speed and accuracy of the algorithm, which can avoid falling into local optimal. The improved model was solved by using the method, and Ronghua No.1 Coal Mine was taken as the research object for simulation. The results show that: this method can reduce the total power consumption of ventilation network by 43.27%, and the air volume of each roadway can meet the demand, so as to verify the feasibility and effectiveness of the adopted method.

     

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