Distributed Integral Convex Optimization-Based Current Control for Power Loss Optimization in Direct Current Microgrids

Yajie Jiang, Siyuan Cheng and Haoze Wang ()
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Yajie Jiang: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
Siyuan Cheng: State Grid Henan Electric Power Research Institute, Zhengzhou 450002, China
Haoze Wang: POWERCHINA Central China Electric Power Engineering Co., Ltd., Zhengzhou 450000, China

Energies, 2023, vol. 16, issue 24, 1-17

Abstract: Due to the advantages of fewer energy conversion stages and a simple structure, direct current (DC) microgrids are being increasingly studied and applied. To minimize distribution loss in DC microgrids, a systematic optimal control framework is proposed in this paper. By considering conduction loss, switching loss, reverse recovery loss, and ohmic loss, the general loss model of a DC microgrid is formulated as a multi-variable convex function. To solve the objective function, a top-layer distributed integral convex optimization algorithm (DICOA) is designed to optimize the current-sharing coefficients by exchanging the gradients of loss functions. Then, the injection currents of distributed energy resources (DERs) are allocated by the distributed adaptive control in the secondary control layer and local voltage–current control in the primary layer. Based on the DICOA, a three-layer control strategy is constructed to achieve loss minimization. By adopting a peer-to-peer data-exchange strategy, the robustness and scalability of the proposed systematic control are enhanced. Finally, the proposed distribution current dispatch control is implemented and verified by simulations and experimental results under different operating scenarios, including power limitation, communication failure, and plug-in-and-out of DERs.

Keywords: DC microgrid; distributed energy resource (DER); distributed integral convex optimization algorithm (DICOA); power loss (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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