Stochastic Optimization of Integrated Transmission and Distribution Network Considering Distributed Generation With Uncertainties

Renewable energy resources (RERs) are currently integrated at different layers of the grid network (either transmission or distribution); the location in the network can depend on the size or policy-related aspects of the resources. The current approach to the optimal power flow methods requires individual solutions for both transmission and distribution networks, and this is often done with no exchange of information between the networks. Moreover, RERs are stochastic in nature, and their uncertainty is a major concern for utilities, even though such integration is economic and sustainable. In this article, a stochastic integrated linear optimization (SILP) framework is modeled to solve the optimal power flow for integrated transmission and distribution networks. The approach is utilized to demonstrate the capability of the framework to handle uncertainty caused by RERs and can help utilities achieve optimum operation based on some key objectives: the cost of operation, the minimization of network loss, and voltage deviation. The simulation analysis is performed on two different integrated T&D networks, IEEE 57-bus & 34-bus and IEEE 118-bus & 123-bus. The simulation results proved that the proposed architecture finds the global optimal solution and has a significant advantage when compared to the state-of-the-art in terms of voltage violations, cost and loss improvement, and increased RER penetration.