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This paper proposes a novel data driven framework for detecting topology transitions in a distribution network. The framework analyzes data from phasor measurement units (PMUs) and relies on the fact that changes in network topology results in changes in the structure and admittance of the network. Using voltage and current phasors recorded by PMUs, the proposed method approximates network parameters using an ensemble-based deep learning model and thus, it does not require any knowledge of network parameters and load models. Using the prediction error of the proposed model, a connectivity matrix which shows the status of switches is constructed. In contrast to other methods, this proposed framework does not require a library of voltage and current transients associated with possible network transitions. It can also detect simultaneous switching actions and is robust to noise and load variations. The model yields a lower error detection rate, and its performance is validated using a modified version of the IEEE 33 bus network and a real feeder located in Queensland, Australia, under full and partial observability conditions. The proposed model has also been compared with another data driven method in terms of inference time and error detection rates. [ABSTRACT FROM AUTHOR]

Volt/VAr Optimization (VVO) is becoming increasingly crucial in distribution management systems with renewable sources that require setting their reactive power in coordination with legacy voltage and reactive power control devices. This paper presents a VVO method that operates in complex variables based on the Wirtinger calculus; it employs a penalty method that keeps voltage magnitudes and controller parameters within limits together with a probabilistic rounding technique for handling switched device variables. The complex variable implementation permits using the compensation technique when solving the Karush-Kuhn Tucker (KKT) system, thus achieving a significant speedup due to limiting the number of linear system factorizations. The proposed method is contrasted with a classical VVO implementation employing discrete coordinate search from the current operating point and an enhanced version that uses sensitivity information. Numerical results on distribution networks having up to 3147 nodes show that the proposed method is significantly faster than classical methods and gives operating points free of voltage magnitude violations and lower power loss. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed coordinated voltage control scheme for distribution networks with distributed generation (DG) and on-load tap changer (OLTC). In this scheme, static synchronous compensators (STATCOMs), DG units and OLTC are coordinated to regulate voltages of all buses to be close to the nominal value in the distribution network, mitigate voltage fluctuations, and minimize the number of operations of OLTC while considering different temporal characteristics of voltage regulation devices. The optimization problem of coordinating DG units and STATCOMs is decomposed by the gradient projection (GP) method. The local controller optimizes the reactive power outputs of DGs and STATCOMs according to local voltage and reactive power measurements, and still achieves the optimal coordination of DG units and STATCOMS in a decentralized manner without a central controller or communication between local controllers. The OLTC control scheme is designed to correct the long-term voltage deviations based on model predictive control (MPC) while minimizing the number of operations. The local controllers send the calculated reactive power references of DG and STATCOMs to the OLTC controller, which achieves distributed coordinated voltage control and mitigates the computation burden. A distribution network with two 20 kV feeders and 8 DG units was used to validate the control performance of the proposed coordinated voltage control scheme. [ABSTRACT FROM AUTHOR]

Soft normally open points (SNOPs) connected to distribution networks are instrumental in maintaining uninterrupted power supply and improving power quality during the fault period. In order to achieve the optimal service restoration scheme, a novel bi-level service restoration model based on the robust optimization method is proposed in this paper. The upper level of the proposed model aims at minimizing the risk of load loss. The switch statuses and range of power transmitted by SNOP terminals can be obtained. In the lower level of the model, the interval robust optimization method is adopted to cope with the uncertainties of DGs and loads. If there are no optimal solutions, the upper level model needs to be solved once more to adjust the network topology. Finally, a test system is established to verify the effectiveness of the proposed model and solution method. The effects of forecasting errors, the DG penetration, and the ratio of single terminal capacity of SNOP to line capacity on the optimization results are analyzed. [ABSTRACT FROM AUTHOR]

Insulation monitoring is crucial to personal safety and equipment operation in the power distribution system. Recently, with the rapid development of distributed generators, the three-phase voltage-source PWM converter (VSC) is widely used as the bidirectional interface between the dc microgrids and the distribution networks. This paper presents the relationship between the response of insulation monitoring device (IMD) and the neutral-point voltage deviation (NPVD) of VSC, by analyzing the disturbances of the switching function and the dc-side insulation balancing. Then, a method of detecting the NPVD for grid-connected VSC is proposed, based on the dc signal injection and the Duffing oscillator. Furthermore, the proposed method takes the mean and spectrum of the neutral-point voltage as the primal characteristics. Thus, the dc signal injection is adopted to detect the mean of the neutral-point voltage, and the Duffing oscillator is adopted to determine the frequency disturbance of the neutral-point voltage, respectively. The test result confirms the existence of the neutral-point voltage deviation and verifies the availability of the proposed method. Hence, the proposed method could be used to improve the response of IMD. [ABSTRACT FROM AUTHOR]

The multizonal medium voltage dc architecture of all-electric ship shipboard power systems (SPSs) includes a variety of distributed energy resources, energy storage devices, and power electronic voltage source converters. Due to the limited fuel supply and tight space, control of the converters should be aimed at increasing their efficiency and compactness. In this paper, a novel approach to voltage control in all-electric ship power systems is proposed to fulfill these goals. In contrast to the traditional SPSs that emulate the land-based electricity grid, maintaining a steady bus voltage is no longer an objective here. On the contrary, the voltage is compelled to fluctuate in order to minimize switching losses in the converters. A method for calculation of the minimum required dc voltage level is described, and results of computer simulations of an SPS with a flexible-voltage dc bus are presented. The minimum-voltage operation of the system results in a significant efficiency increase. [ABSTRACT FROM AUTHOR]

This paper proposes a new bidirectional intelligent semiconductor transformer (BIST) for the smart distribution system and smart grid. The proposed BIST consists of high-voltage high-frequency ac/dc converter, bidirectional low-voltage dc/dc converter, and hybrid-switching dc/ac inverter. It features 1) input-to-output isolation with a high-frequency transformer; 2) bidirectional power flow; 3) small size and light weight; 4) capability of compensating voltage sag and/or swell; and 5) realization of three-phase structure based on single-phase module. The operational feasibility of proposed transformer was verified not only by computer simulation with PSCAD/EMTDC software but also by a hardware prototype with rating of 1.9 kV/127 V, 2 kVA, allowing a three-phase transformer of 3.3 kV/220 V, 6 kVA with three-phase construction. [ABSTRACT FROM AUTHOR]