Stochastic Day-Ahead Scheduling of Distributed Energy Resources: A Meta Modeling Approach

Integration of distributed energy resources (DERs) presents several challenges for grid operators, including managing the intermittent output of renewable energy sources, balancing the grid's supply and demand, and ensuring grid stability and reliability. To this end, this article presents a novel approach for (SDS) of DERs, with the aim of minimizing network losses, maximizing solar PV generations, efficiently balancing the system, and mitigating the risks of line congestion and voltage limit violations under uncertain conditions. A meta-model of SDS is developed using the so-called lite polynomial chaos expansion, which can handle a large number of uncertain and nonparametric sources and provide a fast and scalable solution. The proposed framework is evaluated using the modified IEEE 33-bus, 69-bus, and 141-bus distribution networks with forecasted values of load and solar generation on a rolling-time horizon. The results demonstrate that the proposed method achieves the same level of accuracy as Monte Carlo simulation-based SDS, while having low computational complexity. Further, we have demonstrated the impact of battery energy storage systems on the SDS of DERs.