A stable ventilation system is an essential guarantee for the efficient production and safety of underground workers. In order to solve the big changes in underground air quantity, gas accumulation, and other problems...
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A stable ventilation system is an essential guarantee for the efficient production and safety of underground workers. In order to solve the big changes in underground air quantity, gas accumulation, and other problems caused by mine main fans switchover. This paper proposes a non-stop switchover system of the mine main fans based on intelligent control and establishes a dynamic optimization model for the switchover process of the mine main fans. The equilibrium optimizer algorithm is improved by chaos mapping and opposition learning machine based on refraction principle to solve the model, and the simulation experiment is carried out with MATLAB. The results show that the proposed method can effectively mitigate the change of underground air quantity during the switchover process of mine main fans. In the 120 s of system operation, the change rate of underground air quantity is consistently within 0.4%, and the two mine main fans always work in the stable interval, which proves the system's high efficiency, stability and safety.
Taking advantage of the favorable operating efficiencies, photovoltaic (PV) with Battery Energy Storage (BES) technology becomes a viable option for improving the reliability of distribution networks;however, achievin...
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Taking advantage of the favorable operating efficiencies, photovoltaic (PV) with Battery Energy Storage (BES) technology becomes a viable option for improving the reliability of distribution networks;however, achieving substantial economic benefits involves an optimization of allocation in terms of location and capacity for the incorporation of PV units and BES into distribution networks. This article suggests a methodology based on the equilibrium Optimization (EO) algorithm for optimal integration of PV with BES in radial distribution networks. Multifarious objectives are comprised to minimize the cost of energy not supplied (CENS), the investment cost of PV and BES installations, their operational costs, the power losses through the distribution lines, the produced CO2 emissions relative to the grid and PV systems. Added to that, the power losses through the voltage source converter (VSC) interface between integrated PV and BES with the grid are assessed. The proposed methodology is applied on two radial distribution systems of 30-bus and 69-bus. The optimal integration of PV systems with BES have been obtained by considering various case studies by imposing several limits on the number of PV-BES and the state of charge (SoC) for BES. Subsequently, comparative performance analysis is performed using genetic algorithm (GA), EO algorithm, particle swarm optimization (PSO), differential evolution (DE), and grey wolf optimization (GWO).
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