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Robust Simultaneous Distribution Network Reconfiguration and Optimal Placement of Renewable Distributed Generations Based on the Information Gap Decision Theory
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Robust Simultaneous Distribution Network Reconfiguration and Optimal Placement of Renewable Distributed Generations Based on the Information Gap Decision Theory
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Journal Article
Robust Simultaneous Distribution Network Reconfiguration and Optimal Placement of Renewable Distributed Generations Based on the Information Gap Decision Theory
2025
Overview
Integration of distributed generation (DG) units in distribution networks (DNs) has some benefits, such as improvement in voltage profile, decrease in power losses, and reduction in operation costs. In line with this concern, the achievement of these advantages, along with environmental benefits, can be further strengthened by the optimal placement and sizing of renewable‐based DGs. Reconfiguration is well known as another approach for optimizing the voltage profile and reducing energy losses in DNs. In this paper, a comprehensive model of simultaneous optimal reconfiguration and allocation of renewable energy DGs, including wind turbines (WTs) and biomass (BM) units in DNs, is presented, considering uncertainties of renewables and hourly load demands. In addition, environmental aspects of the proposed problem are taken into consideration by including emissions resulting from the use of other fossil fuel generations in the objective function. To cope with uncertainties in a robust framework, the information gap decision theory (IGDT) method is implemented. The proposed robust optimization model is examined on the IEEE‐33 node DN as a benchmark based on a discrete particle swarm optimization (DPSO) algorithm in MATLAB platform software. Various cases are considered to examine the impact of uncertainty budgets and robustness indices of different parameters on the results. The achieved simulation results are analyzed and compared with the other existing algorithms to verify the accuracy of the proposed method and its superiority over other algorithms in reducing costs and losses. In this paper, a comprehensive model of simultaneous optimal reconfiguration and allocation of renewable energy DGs including wind turbines (WTs) and biomass (BM) units in power distribution networks is presented considering uncertainties of renewables and hourly load demands.
Publisher
John Wiley & Sons, Inc,Wiley
Subject
