Choobdari Mahsa, Samiei Moghaddam Mahmoud, Davarzani Reza, Azarfar Azita, Hoseinpour Hesamodin
Department of Electrical Engineering, Shahrood Branch, Islamic Azad University, Shahrood, Iran.
Department of Electrical Engineering, Damghan Branch, Islamic Azad University, Damghan, Iran.
Sci Rep. 2024 Oct 4;14(1):23041. doi: 10.1038/s41598-024-73928-1.
The integration of renewable energy sources into smart distribution grids poses substantial challenges in maintaining grid stability, efficiency, and reliability due to their inherent variability and intermittency. This study addresses these challenges by proposing a novel two-level optimization model aimed at enhancing operational efficiency and robustness in smart distribution grids. The model synergistically integrates renewable energy sources, energy storage systems, electric vehicles, and demand-side management through a dynamic reconfiguration approach. It employs a robust optimization framework combined with a two-stage second-order cone optimization model to manage real-time operations and strategic grid reconfiguration. Key findings from simulations on the IEEE 33 and 69-bus networks underscore the model's effectiveness. In the 33-bus system, implementing the demand response program led to a significant reduction in power losses, from 0.64 MW to 0.52 MW, and improved voltage stability, with the minimum voltage increasing from 0.970 to 0.980 p.u. Similarly, in the 69-bus system, power losses decreased from 0.85 MW to 0.79 MW, and voltage stability improved, with the minimum voltage rising from 0.962 to 0.972 p.u. The model also demonstrated reduced energy procurement needs, showcasing its impact on enhancing grid efficiency and reliability. These results highlight the model's potential for advancing smart grid management strategies, offering significant improvements in operational performance and stability under varying demand conditions.
由于可再生能源固有的波动性和间歇性，将其整合到智能配电网中对维持电网的稳定性、效率和可靠性提出了重大挑战。本研究通过提出一种新颖的两级优化模型来应对这些挑战，该模型旨在提高智能配电网的运行效率和鲁棒性。该模型通过动态重构方法将可再生能源、储能系统、电动汽车和需求侧管理协同整合在一起。它采用了一个鲁棒优化框架，并结合两阶段二阶锥优化模型来管理实时运行和电网的战略重构。在IEEE 33和69节点网络上进行的仿真得出的关键结果突出了该模型的有效性。在33节点系统中，实施需求响应计划使功率损耗大幅降低，从0.64兆瓦降至0.52兆瓦，并改善了电压稳定性，最低电压从0.970标幺值提高到0.980标幺值。同样，在69节点系统中，功率损耗从0.85兆瓦降至0.79兆瓦，电压稳定性得到改善，最低电压从0.962标幺值升至0.972标幺值。该模型还显示出能源采购需求的减少，展示了其对提高电网效率和可靠性的影响。这些结果突出了该模型在推进智能电网管理策略方面的潜力，在不同需求条件下的运行性能和稳定性方面有显著提升。
