Abstract: In order to better mine the spatial-temporal dynamic characteristics of electric vehicle charging load under the situation of strong grid-transportation network coupling and improve the accuracy of charging load forecasting,a framework of graph Wave Net based charging load forecasting for electric vehicles is proposed.First,the charging stations in the coupled grid-transportation network are regarded as charging load nodes.Then,by regarding the charging load data of the charging stations as the characteristic information of the nodes,all the nodes are constructed into a graph,and the graph containing the spatial-dimension information of charging loads and the time-dimension information of charging loads are input into the adaptive graph Wave Net framework for forecasting.Finally,taking the charging station load data in an urban area of a city in China as an example,the forecasting results based on the adaptive graph Wave Net framework are compared with the forecasting results of the existing methods,and the correctness and effectiveness of the proposed method are verified.