Robust Capacity Assessment of Distributed Generation in Unbalanced Distribution Networks Incorporating ANM Techniques

• Published in: IEEE transactions on sustainable energy Vol. 9; no. 2; pp. 651 - 663
• Main Authors: Chen, Xin, Wu, Wenchuan, Zhang, Boming
• Format: Journal Article
• Language: English
• Published: IEEE 01.04.2018
• Subjects: active network management; DG capacity assessment; Load flow; Load modeling; Mathematical model; Optimization; Reactive power; robust optimization; Robustness; three-phase branch power flow; Uncertainty
• ISSN: 1949-3029; 1949-3037
• DOI: 10.1109/TSTE.2017.2754421

To settle a large-scale integration of renewable distributed generations (DGs), it requires to assess the maximal DG hosting capacity of active distribution networks (ADNs). For fully exploiting the ability of ADNs to accommodate DG, this paper proposes a robust comprehensive DG capacity assessment method considering three-phase power flow modelling and active network management (ANM) techniques. The two-stage adjustable robust optimization is employed to tackle the uncertainties of load demands and DG outputs. With our method, system planners can obtain the maximum penetration level of DGs with their optimal sizing and sitting decisions. Meanwhile, the robust optimal ANM schemes can be generated for each operation time period, including network reconfiguration, on-load-tap-changers regulation, and reactive power compensation. In addition, a three-step optimization algorithm is proposed to enhance the accuracy of DG capacity assessment results. The optimality and robustness of our method are validated via numerical tests on an unbalanced IEEE 33-bus distribution system.