Coordination of Neighboring Active Distribution Networks under Electricity Price Uncertainty using Distributed Robust Bi-level Programming

• Published in: IEEE transactions on sustainable energy Vol. 14; no. 1; pp. 1 - 14
• Main Authors: Homaee, Omid, Najafi, Arsalan, Jasinski, Michal, Tsaousoglou, Georgios, Leonowicz, Zbigniew
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Active Distribution Network; bi-level optimization; Coordination; Costs; Distributed generation; Distribution networks; DSO-DSO coordination; Electric power distribution; Electricity; Electricity pricing; Energy management; Energy resources; Energy sources; Energy storage; Indexes; Kuhn-Tucker method; Market prices; Networks; Optimization; Reactive power; Renewable energy sources; robust optimization; Robustness; Storage systems; Uncertainty
• ISSN: 1949-3029; 1949-3037
• DOI: 10.1109/TSTE.2022.3212004

Distributed energy resources transform the passive distribution networks into active distribution networks (ADNs). Coordinating the dispatch actions of distributed resources has been studies in the literature, both within an ADN and between an ADN and the transmission system. However, the direct coordination between ADNs interconnected via a physical tie line is a topic boldly under-discussed, despite its practical relevance. In this paper, we consider the problem of coordinating the dispatch actions, including the energy exchange, of two interconnected ADNs, each one integrated with flexible loads (managed by demand response aggregators), energy storage systems, and microturbines (MTs). The bilateral energy trading enables the neighboring ADNs to benefit from the difference in locational marginal prices. The coordination problem is formulated as a robust bi-level program under price uncertainty. At the upper level, the total cost of the ADNs is minimized subject to the uncertainty of electricity market prices and technical constraints of the networks and the resources. At the lower level, the DR aggregators present at each ADN selfishly minimize their own cost. Moreover, the worst case realization of wholesale electricity market prices is considered. The problem is linearized using the Karush-Kuhn-Tucker (KKT) conditions and decomposed using the alternating direction method of multipliers (ADMM). Simulation results verify the convergence behavior of the proposed method and quantify the value of DSO-DSO coordination in the presence of an interconnecting line between the ADNs.