Intelligent power grid deep learning scheduling method considering schedulable electric vehicle fast/slow charging and discharging forms

Abstract

The invention discloses an intelligent power grid deep learning scheduling method considering schedulable electric vehicle fast / slow charging and discharging forms, belongs to the field of regional intelligent power grid operation, and aims to perform power supply power optimal distribution by taking total operation cost as an objective function in a day-ahead scheduling stage. In the intra-day pre-scheduling stage, load fluctuation and a day-ahead scheduling plan are simulated to serve as input samples of the deep learning network, prediction data generated through simulation are input into aregional intelligent power grid model in the intra-day pre-scheduling stage, and controllable unit scheduling data in the scheduling plan in the model training stage serve as output samples of the deep learning network. An intra-day scheduling model of the regional smart grid is trained based on the deep learning network through the input sample and the output sample to acquire a predicted valueof the load at the next scheduling moment through ultra-short-term prediction. The predicted value and the day-ahead scheduling plan are inputted into an intra-day scheduling model of the regional smart power grid to obtain an intra-day scheduling value of the controllable unit. The method solves the problems that errors exist in prediction of distributed power supplies, electric vehicles and loads of a regional smart power grid, and intra-day economic dispatching of the regional smart power grid is difficult to achieve.

Description

technical field [0001] The invention relates to the field of regional smart grid scheduling, in particular to a smart grid deep learning scheduling method that takes into account the fast / slow charging and discharging forms of schedulable electric vehicles. Background technique [0002] Power dispatching is an important task in modern energy management systems. Under the constraints of power generation, transmission and operation, system operation economy becomes an important goal of power dispatching. In traditional power dispatching, only thermal power generation units are involved, and the dispatching center formulates the unit start-up plan with the goal of the lowest coal consumption according to the unit combination status and system parameters of the previous dispatching day. With the global energy crisis and environmental problems becoming more and more serious, it has become the consensus of all countries in the world to vigorously develop renewable energy. Modern ...

AI Technical Summary

Problems solved by technology

[0003] The existing research of the present invention does not take into account the use of adjusting the charging and discharging power of electric vehicles to suppress the adverse effects caused by wind power output and load fluctuations and uncertainties. The scheduling strategy Relying on the accuracy of day-ahead dispatching, it is easy to affect the power grid dispatching plan. A smart grid deep learning dispatching method that takes into account the fast / slow charging and discharging forms of dispatchable electric vehicles is provided.

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