PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Data-Driven Distributionally Robust Optimization for Day-Ahead Operation Planning of a Smart Transformer-based Meshed Hybrid AC/DC Microgrids Considering the Optimal Reactive Power Dispatch
Version 1
: Received: 19 June 2024 / Approved: 19 June 2024 / Online: 20 June 2024 (15:36:32 CEST)
How to cite:
Núñez-Rodríguez, R. A.; Unsihuay-Vila, C.; Posada, J.; Pinzón-Ardila, O. Data-Driven Distributionally Robust Optimization for Day-Ahead Operation Planning of a Smart Transformer-based Meshed Hybrid AC/DC Microgrids Considering the Optimal Reactive Power Dispatch. Preprints2024, 2024061381. https://doi.org/10.20944/preprints202406.1381.v1
Núñez-Rodríguez, R. A.; Unsihuay-Vila, C.; Posada, J.; Pinzón-Ardila, O. Data-Driven Distributionally Robust Optimization for Day-Ahead Operation Planning of a Smart Transformer-based Meshed Hybrid AC/DC Microgrids Considering the Optimal Reactive Power Dispatch. Preprints 2024, 2024061381. https://doi.org/10.20944/preprints202406.1381.v1
Núñez-Rodríguez, R. A.; Unsihuay-Vila, C.; Posada, J.; Pinzón-Ardila, O. Data-Driven Distributionally Robust Optimization for Day-Ahead Operation Planning of a Smart Transformer-based Meshed Hybrid AC/DC Microgrids Considering the Optimal Reactive Power Dispatch. Preprints2024, 2024061381. https://doi.org/10.20944/preprints202406.1381.v1
APA Style
Núñez-Rodríguez, R. A., Unsihuay-Vila, C., Posada, J., & Pinzón-Ardila, O. (2024). Data-Driven Distributionally Robust Optimization for Day-Ahead Operation Planning of a Smart Transformer-based Meshed Hybrid AC/DC Microgrids Considering the Optimal Reactive Power Dispatch. Preprints. https://doi.org/10.20944/preprints202406.1381.v1
Chicago/Turabian Style
Núñez-Rodríguez, R. A., Johnny Posada and Omar Pinzón-Ardila. 2024 "Data-Driven Distributionally Robust Optimization for Day-Ahead Operation Planning of a Smart Transformer-based Meshed Hybrid AC/DC Microgrids Considering the Optimal Reactive Power Dispatch" Preprints. https://doi.org/10.20944/preprints202406.1381.v1
Abstract
Smart Transformer (ST)-based Meshed Hybrid AC/DC Microgrids (MHM) are a feasible alternative to increase the performance of conventional microgrids (MG) and to increase the penetration of Distributed Energy Resource (DER) at the same time, active and reactive power dispatch on the system. Despite this, MHMs present challenges in managing resources under uncertainties and controlling electronic converters associated with the ST and DER, making it complex to achieve optimal system performance. In this paper, a Data-Driven Distributionally Robust Optimization (DDDRO) for Day-Ahead Operation Planning of an ST-based MHM considering the reactive power dispatch of the DER that minimizes network losses, voltage deviations, and operation cost simultaneously, considering uncertainties of Photovoltaic Generators (PVG) and demand, is proposed. The Column and Constraint Generation (C&CG) algorithm and Duality-Free Decomposition (DFD) method are adopted. Besides, the original mixed-integer non-linear planning problem is converted into a Mixed-Integer (MI) Second-Order Cone Programming (SOCP) problem through second-order cone relaxation and positive octagonal constraint method. Simulation experiments and results with a connected MHM system demonstrate the effectiveness and performance of the proposed model. Finally, we observe the effect of the meshed structure of MG and the positive impact of integrating the ST to form MHM, taking advantage of the degrees of freedom of this multi-stage converter for optimal energy management under uncertain conditions.
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
