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Research On Charging Scheduling Strategy Of Electric Vehicles Based On Imperialist Competitive Algorithm

Posted on:2024-04-01Degree:MasterType:Thesis
Country:ChinaCandidate:Q B HuangFull Text:PDF
GTID:2542307121488414Subject:Traffic and Transportation Engineering
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With the promotion and popularization of transportation electrification,the modern transportation system has adopted cleaner,greener and more efficient electric vehicles to replace the previous fuel ones on a large scale,and the rapid adjustment of the energy structure has greatly promoted the realization of the "double carbon" goal.However,the charging requirements of electric vehicles bring new challenges to vehicle scheduling,especially for production transport fleets with unified operators and unified tasks.Therefore,formulating a reasonable charging scheduling strategy for it can not only improve the economic benefits of relevant operators,but also effectively promote energy saving and consumption reduction in the production and transportation links.Aiming at the electric vehicle fleet with unified operation scheduling,this paper proposes a resource-constrained charging scheduling strategy.This strategy includes a modeling idea and a solving algorithm.Based on the derived model of the resource-constrained project scheduling problem,a resource-constrained charging scheduling model is built.This model takes the tasks to be solved in the operation process as the scheduling objects,and takes the number of electric vehicles as the resource constraints.A two-stage evolutionary imperialist competitive algorithm is used to solve the model to obtain the charging scheduling scheme and the corresponding work scheduling scheme.In this paper,electric buses and AGVs are used as experimental objects for research.The specific research contents are as follows:(1)The models of resource-constrained project scheduling problem and its derivative problems are studied,and it is found that the multi-skills resource-constrained multi-project scheduling problem considering is very suitable for simulating the operation scheduling process of electric buses,while the resource-constrained project scheduling problem considering resource transfer time adapt to the scheduling optimization problem of AGV.Moreover,a large number of experts and scholars currently prefer to use meta-heuristic methods to solve such problems.Therefore,this paper improves the imperialist competitive algorithm from three aspects: selection of individual feature,improvement of search operator,and enhanced sub-population interaction,and proposes a two-stage evolutionary imperialist competitive algorithm that can effectively solve resource-constrained project scheduling problems and its derivatives.(2)Aiming at the plug-in charging scenario of the whole vehicle,a resource-constrained charging scheduling model for electric buses considering shallow charging and shallow discharging,interleaved charging and on-demand charging is constructed.The charging scheduling scheme with the best economic benefits and its matching driving plan are output.The model first uses 4 examples of bus terminals containing 5,10,20 and 36 lines to verify its validity,and compares the experimental numerical value with the disordered charging scheduling strategy and the conventional ordered charging scheduling strategy to prove that the proposed strategy can better reduce electricity costs,equipment purchase costs and battery charge and discharge times.(3)Aiming at the automatic port that adopts the dual-cycle strategy,the overall layout of "spatial isolation + yard parallel + side interaction" and the plug-in offline charging mode,a resource-constrained charging scheduling model oriented to AGVs considering shallow charging and shallow discharging,interleaved charging and on-demand charging is constructed.The model outputs the charging scheduling scheme and job scheduling scheme of AGVs with the shortest construction period.The relevant model is verified by using 5 examples of automated docks with scheduling cycles of 1 day,7 days,10 days,15 days and 30 days,and three charging decisionmaking methods are designed to compare with the method proposed in this paper.Experimental results prove that the proposed strategy has a good effect in compressing makespans and total charging capacity and balancing no-load mileage and charging and discharging depth.
Keywords/Search Tags:electric buses, AGV, charging scheduling strategy, resource-constrained project scheduling problem, imperialist competitive algorithm
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