Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/160068
Title: PV inverter reliability-constrained volt/var control of distribution networks
Authors: Chai, Qingmian
Zhang, Cuo
Xu, Yan
Dong, Zhao Yang
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Source: Chai, Q., Zhang, C., Xu, Y. & Dong, Z. Y. (2021). PV inverter reliability-constrained volt/var control of distribution networks. IEEE Transactions On Sustainable Energy, 12(3), 1788-1800. https://dx.doi.org/10.1109/TSTE.2021.3065451
Journal: IEEE Transactions on Sustainable Energy 
Abstract: The increasing penetration of photovoltaic (PV) systems promotes utilization of PV inverters for volt/var control (VVC) in distribution networks. However, PV inverters are vulnerable and their reliability is one of the most critical concerns for sustainable PV energy utilization. To enhance PV inverter reliability, this paper proposes a PV inverter reliability-constrained VVC method of distribution networks under uncertainties. Firstly, a full reliability analysis procedure for PV inverters is developed to estimate the lifetimes of core devices inside inverters. Secondly, considering the impacts of VVC on PV inverter reliability, reliability constraints are proposed based on regulation of inverter apparent power and application of a PV curtailment scheme. Thirdly, a multi-objective PV inverter reliability-constrained VVC optimization model is proposed, which aims to minimize network power loss and PV curtailed power, simultaneously. Accordingly, the nonconvex model is relaxed by a second-order cone programming method, and the uncertainties such as PV power generation and loads are addressed by a scenario-based stochastic optimization method. The proposed VVC method is tested on the 33-bus and 69-bus distribution networks, and the simulation results verify high efficiency of the proposed method in energy loss reduction and inverter reliability enhancement.
URI: https://hdl.handle.net/10356/160068
ISSN: 1949-3029
DOI: 10.1109/TSTE.2021.3065451
Schools: School of Electrical and Electronic Engineering 
Rights: © 2021 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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