Hybrid uncertainty approach for management of energy storage-embedded soft open points in distribution grids

Abstract

Energy storage-embedded soft open point (ESOP) is an innovative electronic device that incorporates energy storage capabilities and is designed to interconnect two or three neighboring distribution feeders. Its primary functions include active power control, reactive power compensation, and grid voltage regulation. On the other hand, distribution grids have been equipped with other distributed energy resources (DERs) such as smart PV inverters, renewable energy sources (solar and wind), and so on. Therefore, this article proposes a novel management scheme for the mentioned devices in distribution grids based on a convex formulation to take powerful solvers like CPLEX into account. Since there are a set of uncertainties associated with the model, including renewable resources, loads, and market price, a hybrid framework is developed based on the unscented transformation (UT) method and information gap decision theory (IGDT). In other words, the uncertainties of renewable resources and loads are captured by the UT method which could provide a correlation among uncertain parameters, while the IGDT method is employed to model the uncertainty associated with the market price. The hybridization of these methods assists in reducing the discrepancy between the actual and predicted values of uncertain parameters. The model is applied to a 33-bus grid, considering various case studies. The proposed method results in a substantial operational cost reduction of approximately 26.82 %. Additionally, it ensures a flatter voltage profile across the network, with the minimum voltage reaching 0.985 p.u.