Rapid electromobile charge scheme optimization method

Abstract

The invention discloses a rapid electromobile charge scheme optimization method, for optimizing a charge scheme of electromobiles within a whole scheduling period on the basis of machine set combination and economic scheduling by taking margin power generation cost as decision basis, so as to ensure the lowest total charge cost of the electromobiles. The rapid electromobile charge scheme optimization method comprises the following steps: firstly, dividing the whole scheduling period into a plurality of charge zones according to the technical characteristics and the charge modes of the electromobiles, subsequently calculating the average margin power generation cost of different available charge zones; preferentially charging charge zones with the lowest average margin power generation cost of the electromobiles; implementing the steps in an iteration manner until all electromobiles are completely charged. In the iteration process, if all charge zones are not available because of the limit of the startup capacity of a conventional machine set combination scheme, a novel machine set is started up to continue the whole charge scheme optimization process on the basis of the principle of the lowest extra startup cost.

Description

[0001] This application is a divisional application with application number: 201310365531.6, application date: 2013-08-20, and title "A Method for Optimizing Electric Vehicle Charging Scheme Based on System Marginal Power Generation Cost". technical field [0002] The invention relates to electric vehicle technology, in particular to an electric vehicle charging scheme optimization method for the marginal power generation cost of a unit system. Background technique [0003] Fuel vehicles emit a large amount of greenhouse gases and polluting gases while consuming most of the oil resources, which poses a huge challenge to environmental protection and sustainable development. Compared with traditional vehicles, electric vehicles have incomparable advantages in alleviating the energy crisis and promoting the harmonious development of human beings and the environment. At present, electric vehicles have become the focus of attention of governments, energy manufacturers and automobi...

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Problems solved by technology

Obviously, the extended unit combination model extended from the unit model considering the charging optimization of electric vehicles will be more difficult to solve. The references given in the previous paragraph respectively use the particle swarm algorithm and the mixed integer linear programming method to solve the model, and the solution process is relatively complicated. , there are certain difficulties when the algorithm is applied to the actual scale power system

[0007] Secondly, the modeling process completely ignores the charging characteristics of electric vehicles, and does not consider that the charging process of electric vehicles is a continuous process, assuming that it completes the charging process within a single scheduling period (1h or 0.5h)

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