期刊
IEEE TRANSACTIONS ON SMART GRID
卷 13, 期 2, 页码 998-1011出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2021.3126761
关键词
Inverters; Reactive power; Voltage control; Uncertainty; Real-time systems; Power generation; Stochastic processes; Active distribution network; droop control; photovoltaic; volt; Var control; uncertainty
资金
- ARC Research Hub for Integrated Energy Storage Solutions [IH180100020]
- UNSW Digital Grid Futures Institute
- Special funding for the Construction of Innovative Hunan Province [2019RS1045]
- Australian Government Research Training Program Scholarship
This paper proposes a multi-objective hierarchically-coordinated VVC method to maximize the benefits of inverter-based VVC. By simultaneously optimizing reactive power setpoints for central control and droop control functions for local control, the method aims to minimize average bus voltage deviation and network power loss.
Due to increasing installation of photovoltaic (PV) units, reactive power compensation from PV inverters contributes significantly to Volt/Var control (VVC) for active distribution networks. While PV inverters support VVC functions, lack of systematic coordination and heavily varying PV power generation lead to low control efficiency. To maximize benefits of the inverter-based VVC, this paper proposes a multi-objective hierarchically-coordinated VVC method with droop-controlled PV inverters. This method aims to minimize both average bus voltage deviation and network power loss, by simultaneously optimizing PV inverter reactive power setpoints for central control and droop control functions for local control. The droop control characteristics of PV inverters are fully modeled, including voltage ranges of the dead band and control zones, as well as droop slope gradients. In addition, this paper applies a Taguchi's orthogonal array testing technique to handle random variations of PV power generation in the optimization problem. Moreover, to efficiently solve this optimization problem with integer variables, this paper proposes a solution algorithm based on model relaxation and a feasibility pump method. The proposed method is tested on two distribution systems, and simulation results verify highly efficient control performance in comparison with existing methods.
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