Research on Data-Driven Distributed Resource Dynamic Aggregation Technology

With the increasingly widespread application of distributed resources in the power distribution network, the traditional power grid dispatching methods are difficult to adapt to the diversity and uncertainty of distributed resources. Therefore, new technologies and methods need to be introduced to improve the efficiency of distributed resource dispatching and the stability of the power grid. To effectively integrate these scattered and diversified resources, this paper puts forward a distributed resources based on quantile regression forest dynamic aggregation method, the method using quantile regression forest algorithm, the real-time state of distributed resources, forecast trend and user demand for accurate analysis, according to the prediction results, dynamically aggregate DER output into a generalized energy storage model, and realize the intelligent scheduling and optimal configuration of resources. Through simulation experiment and actual case analysis, this paper proves that this method can effectively improve the accuracy of power grid dispatching, ensure the security and enhance the stability.