电气化公路煤炭运输调度模型研究OA

Under the"dual-carbon"goals,traditional highway transport of coal is confronted with issues such as high energy consumption,heavy emissions,and uncertain costs.Electrified highway technology provides a clean and efficient alternative.However,most existing scheduling models overlook issues regarding dynamic electricity pricing fluctuations and resource coordination for multimodal transport.This paper offers a coal transport optimization model that integrates a response mechanism for dynamic electricity pricing with collaborative scheduling for multimodal transport in the coal transport scenario of Group C.Within a mixed-integer programming framework,the model incorporates transport costs,life-cycle carbon emissions,intermodal transfer efficiency,and resource constraints,and establishes a multi-objective collaborative optimization mechanism to achieve high economic efficiency and low carbon emissions.Simulation experiments based on data of Group C show that the model significantly reduces transport costs(by 9.51%)and carbon emissions,validating its effectiveness in responding to dynamic electricity pricing and collaborative optimization for multimodal transport.