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

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.