MATEC Web Conf.
Volume 363, 20225th International Conference on Advances in Materials, Machinery, Electronics (AMME 2022)
|Number of page(s)||4|
|Published online||29 August 2022|
Research on differentiated scheduling method of electric vehicle considering random probability
Dongying Power Supply Company of State Grid Corporation of China, China
On the basis of the charging load of a single electric vehicle, in order to reduce the variance of the equivalent load curve and alleviate the peak plus peak caused by electric vehicles, a local electric vehicle charging cooperative scheduling model with the distribution network node as the optimization unit is set up. The model is composed of node agent and electric vehicle agent. The electric vehicle agent is based on the node load obtained. Rate information, combining with its own state, using random probability charging algorithm to make the decision to start charging or stop charging, and use IEEE-33 node system as an example to use MATLAB software for the designed electricity. The algorithm is verified by dynamic vehicle charging cooperative scheduling strategy. The results show that the proposed algorithm can effectively load the load curve and reduce the variance of load curve.
Key words: Electric vehicle / collective motion / ordered charging / synegistic dispatch / random probability charging algorithm
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.