Distributionally robust optimization of voltage fluctuations and imbalance in islanded bipolar DC microgrids

DC microgrids (DCMGs) are gaining popularity due to the rise of DC devices, increased use of solar power, and the absence of frequency and reactive power concerns. Key challenges in DCMGs include voltage fluctuations due to unpredictable changes in renewable energy resources (RERs), power flow management, and power distribution among distributed generations (DGs). To ensure the stability and reliability of DCMGs, it is crucial to maintain proper DC bus voltage levels and effectively manage power flow between different components. This paper presents a new scheduling framework for bipolar DCMGs (BPDCMGs) that simultaneously considers voltage variations and imbalances. A novel objective function focused on voltage variations is developed based on advanced load flow equations for BPDCMGs. Also, distributionally robust optimization (DRO) is utilized for RERs and load consumption uncertainties based on the Kullback–Leibler divergence metric. Following the reformulation of the multiobjective DRO problem, an optimal compromise solution is found using min–max fuzzy criteria. The proposed model has been tested on the IEEE 33 bus system, simulating an islanded BPDCMG. Detailed analysis demonstrates the model's effectiveness in managing voltage fluctuations and imbalances, with numerical results indicating over a 90% reduction in voltage fluctuations and over 40% decrease in unbalancing.