Min Xu

With the rapid development of distribution networks and increasing demand for electricity, the pressure of power supply for medium- and low-voltage distribution networks (M&LVDNs) is increasingly significant, especially considering the large scale of customers at the low-voltage (LV) level. In this paper, an outage sequence optimization method for low-voltage distribution networks (LVDNs) that considers the importance of users is proposed. The method aims to develop an optimal outage sequence strategy for LV customers in case of medium-voltage (MV) failure events. First, a multi-dimensional importance indicator system for LV users is constructed, and the customers are ranked using a modified Analytic Hierarchy Process–Entropy Weight (AHP-EW) method to determine their priorities during outages. Then, an elastic net regression-based method is used to identify the topology of the LV network. Finally, an outage sequence optimization model based on the user importance is proposed to reduce the load-shedding level. Extensive case studies are conducted in the modified LV distribution network. The results show that the proposed method results in fewer outage losses throughout the restoration periods than traditional methods and effectively improves the reliability of the power supply to LV users.

To resolve the issue of the difficultly in effectively balancing the output performance improvement, cost reduction, and efficiency improvement of a medium-voltage modular multilevel converter (MMC), a novel MMC (NMMC) topology based on high- and low-frequency hybrid modulation is proposed in this study. Each arm of the NMMC contains a high-frequency sub-module composed of a heterogeneous cross-connect module (HCCM) and N − 1 low-frequency sub-modules composed of half-bridge converters. The high-frequency bridge arm of the HCCM in this study adopts SiC MOSFET devices, while the commutation bridge arm and low-frequency sub-module of the HCCM adopt Si IGBT devices. For the NMMC topology, this study adopts a high/low-frequency hybrid modulation strategy, which gives full play to the advantages of low switching loss in SiC MOSFET devices and low on-state loss in Si IGBT devices. In addition, a specific capacitor voltage balance strategy is proposed for the HCCM, and the working state of the HCCM is analyzed in detail. Furthermore, the feasibility and effectiveness of the proposed topology, modulation strategy, and voltage balancing strategy are verified by experiments. Finally, the proposed topology is compared with the existing MMC topology in terms of device cost and operating loss, which proves that the proposed topology can better balance the cost and efficiency indicators of the device.

The construction of an energy distribution network can improve the system’s ability to absorb new energy, and its stable and efficient operation has become more and more important. The security and stability analysis of a distribution network needs accurate distribution network model parameters as support. At present, the installation of PMU equipment in China’s distribution network synchronous phase angle measurement unit is limited, which brings challenges to the parameter correction of the distribution network. In this paper, an automatic correction algorithm of distribution network parameters based on the CIM model and measurement data is proposed for the distribution network system without PMU. Firstly, the distribution network topology construction technology based on XML files and key fields of the distribution network is proposed, and the non/small impedance devices (such as switches) are merged and reduced. The breadth-first traversal algorithm is used to verify the connectivity of the constructed topology. Then, based on the topology construction and the least squares method, an iterative parameter correction technique is constructed. Finally, the accuracy and effectiveness of the proposed algorithm are verified in a standard IEEE 33-bus system distribution network and an example of the China Southern Power Grid. The topology connections constructed based on the CIM model have significantly enhanced the efficiency of parameter correction.

Fueled by pressing global climate concerns, the integration of large-scale renewable distributed generation sources, including distributed wind power and photovoltaics, along with electricity substitution loads into the distribution network has been accelerated to diminish carbon emissions. This shift introduces significant challenges and necessitates the advanced operation and control of distribution systems to accommodate these changes effectively. Against this backdrop, there is a growing expectation for an open and scalable central control mode, equipped with compatible interfaces, to offer a visionary development platform for the grid. This platform is anticipated to meet the evolving needs of future distribution system development, ensuring adaptability and forward compatibility. The aforementioned platform requires open, scalable, and interface-compatible models of key distribution network equipment as its foundation. To address the challenges presented, this paper proposes a data–physics-driven modeling approach for automating simulations in distribution systems. This method employs a simplified and standardized system of linear differential equations with undetermined coefficients to capture the common physical characteristics of specific device types. The models designed through this approach are notably open, allowing for real-time data to refine undetermined coefficients and accurately depict the dynamic behavior of equipment over various periods. Their scalability also stands out, rendering them apt for large-scale distribution network simulations. The paper elaborates on models for distributed photovoltaic, wind turbine, energy storage, and electric vehicle, and demonstrates their application within an IEEE-33 node distribution network topology built on Python.