Currently power series with single time scale and large sampling intervals are generally used in modeling photovoltaic generation forecast.Simple as the model is，its simulation accuracy of the time-series characteristics of photovoltaic（PV）power series is not high.In order to solve this problem，this paper proposes a local forecasting method for multidimensional time-series based on PV power series with small sampling interval.By constructing the main value series of PV power with different time-scales，the multidimensional time-series with hourly average PV power series as the main series is obtained.The correlation analysis，C-C method and minimum prediction error method of embedding dimension are used to compute the time-delay and embedding dimensions of the reconstructed phase space of the multidimensional time-series.The1-hour ahead local forecasting model for PV power is developed by using support vector regression after phase space reconstruction.To demonstrate the effectiveness，the model is applied and tested in a microgrid.Simulation results show that the proposed local forecasting model based on multidimensional time-series outperforms the local forecasting model based on one-dimensional series，hence it has a better application value.