A typical distribution network contains hundreds of medium‐voltage (MV) feeders and ten thousands of low‐voltage (LV) feeders. This work introduces an efficient taxonomy approach that combines cluster analysis with discriminant analysis to identify statistically representative MV and LV feeders in the west Australian context. Quadratic discriminant functions have been extracted and can be used as a feeder classifier for any feeder in this distribution system. The representative feeder sets provide rigorously validated test cases for the evaluation of smart grid technologies.

The rapid growth in the number of electric vehicles (EVs), driven by the ‘double‐carbon’ target, and the impact of uncontrolled charging and discharging behaviour and discharged battery losses severely limit electric vehicles’ low carbon characteristics. Existing research on systemic low‐carbon emissions and electric vehicle charging and discharging issues is usually determined by considering only carbon trading markets or charging and discharging management on the source side. In this regard, a coordinated and optimized operation model that considers the participation of electric vehicle clusters in deep peaking and the source network load and storage adjustable resources is proposed. The upper layer establishes a real‐time price‐based demand response mechanism for the load side with the minimum net load fluctuation as the objective function; the middle layer establishes a comprehensive operation mechanism for the source and storage side that includes an orderly charging and discharging peaking compensation mechanism for electric vehicles, and a deep peaking mechanism that takes into account clean emission, and constructs an optimal operation model with the minimum comprehensive operating cost as the objective function; the lower layer establishes a distribution network loss minimization model for the network side that takes into account the orderly charging and discharging of electric vehicle as the objective function. The optimal load model with the objective function of minimizing the distribution network loss is established at the lower level. Finally, the original problem is transformed into a mixed integer linear programming problem, and the model's effectiveness is verified by setting different scenarios. The model reduces the total cost by 22.22%, improves the wind power consumption rate by 19.55%, reduces the actual carbon emission by 16.66%, and reduces the distribution network loss by 13.91% compared to the basic model.

The conventional overcurrent protection is ineffective in isolating faults in microgrids due to the low fault current levels contributed by inverter-interfaced distributed generations (IIDGs). To extend the microgrid protection methods, the distance protection is considered as a common alternative to detect faults. However, the fault-ride-through (FRT) requirements and the high impedance fault (HIF) detection challenge the application of the conventional distance protection. To solve the two problems, a new inverse-time distance (ITD) protection for medium-voltage AC microgrids was proposed in this paper. The primary ITD protection was designed to meet the FRT requirements, and the backup protection was coordinated to isolate faults. The fault resistance and distributed generation infeed effect on the measured impedance were mitigated by a communication-assisted method proposed in this paper. Owing to the shorter communication channel time in distribution feeders and lower communication investments without a synchronous clock, the proposed method can be used to improve the ITD protection performance. An 11 kV AC microgrid was simulated with different fault types in the islanded mode and grid-connected mode. Time domain simulation verified the effectiveness of the proposed ITD protection.

The relay protection sensitivity is one of the determined factors in the power system, however, it is often overlooked in current distribution network (DN) planning. The relay protection sensitivity can be decreased to below the minimum values, failing to meet the requirements for electrical installations. To address this challenge, a new optimization model integrated with the relay protection sensitivity to maximize the inverter interfaced distributed generator (IIDG) penetration level while minimizing IIDG investment was proposed in this paper. The IIDG effect on the relay protection sensitivity was analysed and the relay protection sensitivity re-evaluation method was developed. The relay protection sensitivity evaluation was integrated into the proposed model and the particle swarm optimization (PSO) algorithm was developed to solve the nonlinear issue. The proposed optimization method was tested on different cases, and results confirmed the effectiveness of the method. Furthermore, the relay sensitivity profiles obtained through the proposed method and the optimization without considering the relay sensitivity limits were compared. The proposed method improves the average and minimum sensitivity factors by 28.77 % and 51.76 %, respectively, when the DTO protection functions as the backup for the protected line in the thirty-three-node system. When DTO acts as the backup for the adjacent line, the average and minimum values increase by 29.91 % and 50.95 %, respectively. Comparative analysis confirms the efficacy of the proposed method. The new method extends the power system panning approaches and can be integrated into the DN planning tools to support the low-carbon initiatives.

The integration of the inverter interfaced distributed generation (IIDG) challenges the conventional fault current calculation methods. The existing fault current calculation methods for distribution networks with IIDG connection generally use nodal admittance matrix and its implicit inverse, which take a longer calculation time and are not suitable for electrical engineering. To simplify the calculation process and reduce the calculation time, a new method was proposed. The new method can estimate fault currents of the feeders with IIDG connection with a higher computation speed, using fault current values obtained in networks without IIDG connection as the initial values in the procedure. The proposed method can obtain results without modifying the node impedance matrix and the calculation time was not affected by the nodes number, which can be used for fast short-circuit current calculation in radial distribution networks with IIDG connection. The new method can be conveniently integrated into software packages for power system analysis and relay protection evaluation.•The proposed method can estimate fault currents of the feeders with IIDG connection with a higher computation speed, which is beneficial for electrical engineering.•The new method has advantages in calculation time and accuracy of the results in comparison with the conventional bus-oriented methods.•The method proposed in this paper can be conveniently integrated into software packages for power system analysis and relay protection evaluation.

In the future, with the large-scale integration of distributed generation (DG) and electric vehicle (EV), due to the dual uncertainty of time and space, it is bound to pose new challenges to the economic and safe operation of urban distribution network. As one of the important means of power grid optimization, distribution network reconfiguration can dynamically adjust the power grid structure according to the spatial and temporal changes of EV charging load. Therefore, in order to improve the economy and safety of urban distribution network operation, this paper proposes a dynamic reconfiguration model of active distribution network considering EV charging demand under the guidance of real-time electricity price. At the same time, the reconfiguration period is divided based on the peak-valley membership degree. The ratio of active network loss at each moment of the system and the operating loss cost after the introduction of time-of-use electricity price is used as the operation index, and the reconstruction period is reasonably divided by the change rate of membership degree. The demand response (DR) mechanism is introduced before the reconfiguration, and the active distribution network reconfiguration model with the minimum operating loss cost is established. The model is solved by the improved binary particle swarm optimization algorithm. Finally, a case study of a city's traffic network and an improved IEEE33 node coupling system is carried out to verify that the time-sharing reconstruction method in this paper can effectively deal with the influence of DG output, EV charging and other factors on the urban distribution network, and improve the economy and safety of the overall distribution network operation.