Mine ventilation network optimization to reduce power consumption with an improved pso algorithm

Underground mines are becoming deeper due to the depletion of shallower mineral resources. An effective mine ventilation network can save tremendous of electricity cost used by fans. This requires the ventilation system to be regulated so that the required airflow to the mine key areas are met with minimum power consumption. But mine ventilation networks are internal coupled strongly. The air-flow of all the other branches may be changed if only one of the branches air-flow is regulated. Such a problem becomes more complicated if multiple main fans are installed. The Hardy Cross method can determine the flow in pipe network systems where the inputs and outputs are known with iterative method. But it is difficult to find the optimum regulating scheme with iterative method such as Hardy Cross, because the inputs of the network systems are the regulating variables. They are not known or constant. This paper established a mine ventilation optimization model, and proposed a λ-PSO optimization algorithm to solve the model. By applying it to a typical mine ventilation network case, it is demonstrated that the proposed algorithm can reach the global optimal solution in shorter computational time. It is recommended to incorporate the algorithm to commercial ventilation network analysis software to assist with cost effective ventilation planning.