The soft open point (SOP) plays a pivotal role in enhancing the flexibility of the distribution networks. However, there is a lack of clear criteria for selecting various SOPs tailored to specific application scenarios. This paper analyzes three common SOP schemes and conducts an economic evaluation based on the definition of the annualized comprehensive cost. Utilizing actual economic data, the annualized comprehensive cost of each scheme is calculated under different phase differences, serving as a crucial selection criterion in practical engineering. Considering the application scenario presented in this paper, the shunt-series type SOP, based on the multi-winding transformer and the compact unified power flow controller (UPFC), is chosen. The corresponding action logic for the transformer’s taps is designed by calculating the required series voltage. Additionally, control strategies for the shunt and series converters are devised to optimize stability, accuracy, and response speed. The proposed method is validated through simulation results using the established model in PLECS.

Short-term electric load forecasting is crucial for the safe and economical operation of distribution networks. Due to the non-stationary and nonlinear variations of load caused by weather and periodicity, the accuracy of a single prediction model often fails to meet practical requirements. This paper proposes a hybrid prediction model based on ensemble learning, integrating least squares support vector regression (LSSVR) and convolutional neural network-long short-term memory (CNN-LSTM) models. Firstly, the seasonal decomposition algorithm is performed to divide the electric load into periodic load components and non-periodic load components. Subsequently, based on the bagging ensemble learning strategy, two types of deep prediction models are build to predict the non-periodic load components separately. Finally, the composite prediction value is obtained through weighted averaging. Simulation experiments on real load datasets verify the effectiveness of the proposed hybrid prediction model

With the rapid development and widespread application of renewable energy, its large-scale access to the low-voltage AC distribution network has brought many challenges. Among them, the problem of voltage violation is particularly prominent. If it is not effectively managed and regulated, it will directly affect the normal power demand of users. Aiming at this problem, this paper proposes a voltage coordinated control scheme based on soft normally open point (SNOP) for flexible interconnected low-voltage distribution network, which is suitable. The scheme effectively overcomes the difficulty caused by the imperfect communication network in the low-voltage distribution system, and combines the distributed energy storage system (ESS) to realize the control of the terminal voltage violation of the interconnected distribution line, which further improves the safety and stability of the system operation. By constructing a flexible simulation model of the interconnected distribution network in Matlab/Simulink, the feasibility and effectiveness of the proposed control strategy are verified.

Loop closure operations can enhance the power supply reliability of traditional distribution networks, but may pose the risk of feeder overcurrent tripping. Existing loop closure devices suffer from issues such as complex structure, large volume, and high cost. Therefore, this paper first introduces the concept of phase-shifting transformers and compares the characteristics and application scenarios of different types of phase-shifting transformers. It proposes a loop closure device based on a SingleCore Asymmetric Phase-Shifting Transformer (SAPST). Subsequently, the intrinsic characteristics of SAPST are analyzed in-depth, and a corresponding intrinsic simulation model is established. A typical distribution network loop closure network model based on SAPST is also developed. Finally, through numerical simulations using PSCAD/EMTDC and practical case analyses, the simulation verification of loop closure and uninterrupted load transfer based on SAPST is conducted. Experimental results indicate that compared to direct loop closure, the loop closure method based on SAPST can safely and reliably achieve impact-free loop closure between different feeders in the distribution network and uninterrupted load transfer.

The analysis and utilization of massive recording data of distribution grid fault indicator is beneficial to improve the effect of distribution grid fault diagnosis. In this paper, the distribution grid monitoring are realized by the random matrix theory (RMT) of high dimensional statistical analysis. The fault diagnosis method based on RMT has the advantages of no need for detailed distribution grid topology, comprehensive utilization of wide-area spatiotemporal data, and observation from a muti-dimensional view. By explaining the application principle of limit spectrum distribution function, the linear eigenvalue statistics (LES) is proposed as the state monitoring index. Distribution grid fault diagnosis based on fault indicator and RMT provides a new data-driven method for distribution grid fault diagnosis while efficiently utilizing massive fault indicator data.

Soft normally-open points (SNOP) can flexibly adjust the power flow between different feeders with power electronic technology. Nowadays, SNOP generally adopts the BTB-VSC topology with bulky size and high initial cost, which is not conducive to promotion and application. To compensate the limitations, a series-shunt multiport SNOP topology was proposed, offers superior power density, reduced weight, and enhanced flexibility for further expansion. Nevertheless, in the event of a short-circuit fault affecting one of the feeders, the remaining healthy feeders will also be subjected to the fault current, thereby threatening the safety of both the S2-MSNOP's devices and feeders. This paper proposes a post-fault restoration scheme for a distribution network system equipped with S2-MSNOP. The scheme ensures the reliable isolation of the faulty feeder and the restoration of the healthy feeders' operation. This paper discusses the configuration and implementation of the scheme. The simulation results provide verification of the effectiveness of the proposed protection scheme.

As a typical power quality problem, voltage sag will affect the power experience of important power users. Controlling voltage sag is one of the shortcuts for important power users to obtain premium power. This paper starts from the public power grid level, user power grid level and electrical equipment level, studies the premium power measures at all levels, constructs the corresponding cost benefit quantitative model, and analyzes the strengths, weaknesses, opportunities and threats of implementing premium power measures at all levels based on SWOT method, providing important reference for the subsequent design of premium power services.

The integration of distributed generation and the diversity of loads generally associated with bidirectional power flow transmission result in uneven power flow distribution and line overload, which may deteriorate the normal operation of the transmission and distribution systems. As one of the practical solutions, the power flow controller enhances the network’s flexibility and controllability significantly within smart grids. This paper extensively investigates the topologies of power flow controllers used in AC grids. A comprehensive classification system is established, incorporating multiple hierarchical classifications to encompass various power flow control topologies. To provide a deeper understanding, thorough investigations of the flow control mechanism outline the structural characteristics and operational modes of corresponding representative topologies. Furthermore, analyses in terms of functionality and cost are performed to facilitate comparisons between different power flow controller topologies, thereby aiding in the identification of suitable application scenarios for each topology type. This study aims to provide a reference for selecting power flow control topologies based on different criteria. Moreover, the conclusion offers guidance for enhancing the relevant topologies, ultimately supporting the widespread implementation of flow control devices in power grids.

With the development of China's electric vehicle market, the participation of electric vehicles in the electricity market has formed a certain scale and pattern. However, the problems of difficulty in consuming new energy and significant impact on the power grid still exist, which poses challenges to the construction of new power systems. Therefore, reasonably guiding the participation of electric vehicle loads in the electricity market is an important measure to solve the contradiction between electricity supply and demand. Reasonably guiding electric vehicle loads to participate in the power market is an important measure and strategic requirement to alleviate the contradiction between power supply and demand. This article first investigates the policies for electric vehicle participation in the market, including charging prices and encouraging participation in the market; Secondly, it introduces the current ways of electric vehicle participation in the market from three perspectives, and studies the specific pilot implementation of electric vehicles in different markets; Finally, by analyzing the typical models of electric vehicle operators participating in the market, the development direction of future electric vehicle participation in the market is summarized, providing certain theoretical support for the development of electric vehicle participation in the market.

Efficient utilization of massive recorded data from fault indicators in distribution grid is beneficial to improve fault diagnosis. In this paper, the state detection and fault diagnosis of distribution grid based on fault indicator data were realized by combining high-dimension statistical analysis and artificial intelligence methods. Spectral residual algorithm was used to obtain saliency map of fault recorded data in rolling time windows, which can filter out useless background information. By training the distribution grid fault diagnosis model based on saliency map, a GRU network with high real-time and accuracy was obtained, and the overall accuracy of fault diagnosis reached 98%. The distribution grid fault diagnosis based on SR-GRU can not only make efficient use of massive fault indicator data, but also improve the universality and intelligence of the distribution grid fault diagnosis.

The high cabled rate of urban power grid aggravates the risk of resonance and harmonic amplification. In addition, the system side of DC receiving end urban power grid contains converter station high-power harmonic sources, while the user side contains other nonlinear user harmonic sources. There are two-way conduction characteristics of harmonics in transmission lines. The problem of resonance and harmonic amplification in distribution network is aggravated by high cable ratio. Therefore, the response of the system side injected harmonic voltage at the end of the line and the potential harmonic amplification problem after the user side injected harmonic current are studied respectively. The influence of key factors (line type, length, load rate and power factor) on harmonic propagation is analyzed. The characteristic harmonic of converter station is not amplified and the most severe condition of amplification is summarized. The harmonic limit of the harmonic injection terminal is also proposed.

The voltage sag mitigation is a non-standardized, due to the lack of customer side details, treatment capacity estimation difficulties, easy to cause excessive or inadequate treatment. This paper studies the identification of the tolerance and capacity of the mitigated devices, and proposes an improved severity index that considers the severity of voltage sag’s residual voltage and duration. And the treatment capacity identification method based on the improved sag severity index and object capacity ratio is put forward and then estimates the required treatment costs. Based on the actual monitoring data of a city power grid, the empirical analysis results show that the proposed method is effective and reasonable.

Voltage sag is an inevitable power quality problem in power system. This paper reviews and summarizes IEEE (Institute of Electrical and Electronics Engineers), IEC (International Electro technical Commission) and Chinese standards related to voltage sag, mainly including voltage sag definition, monitoring, indices evaluation, voltage sag tolerance test of sensitive equipment and governance measures. This paper also summarizes the differences and focuses of each standard and analyzes the problems that are still worthy of improvement in the existing standards so as to provide reference for scientific understanding and solving the voltage sag problem.

With the increasing connecting of photovoltaic systems, the harmonic pollution in power grid is deteriorated. The evaluation of the harmonic emission levels for photovoltaic system is significant for harmonic mitigation. However, when the background harmonics are unstable, traditional evaluation methods have large calculation errors. To solve this problem, a method based on the relevant vector machine is proposed in this paper. Compared with the traditional vector machine based method, the novel one can reach a high calculation accuracy, even when the background harmonics is relatively unstable. The validity for our proposed method is verified by simulation analysis.

There are a large number of power quality problems with large-capacity dedicated line users of the power grid. The monitoring data of power quality presents a large number of irregular characteristics. The signal samples obtained directly by measuring the signals contain a lot of complicated and useless information, and cannot be used for the type identification of special load power quality. Regarding this problem, this paper proposes a method for identifying the type of power quality disturbances with special loads based on S transform and support vector machine (SVM). Simulation and actual data experiments show that the method can accurately identify, and it is of great significance for grasping the features of power quality, as well as useful for the supervision, analysis and management of power quality.

In the future, the power grid will face a series of changes, which are reflected in different levels of source, network and load. At present, the power grid's ability to deal with natural disasters, operation faults, internal and external shocks is weak, the structure and tolerance of the power grid still need to be improved, and the power grid needs to be further improved, so the tenacity in the power system has been widely concerned. However, most of the existing researches focus on the recovery ability of power grid under extreme natural disasters. However, in addition to extreme natural disasters, there are also serious system failures, man-made damage, terrorist attacks and misoperation which have a small probability and have a great impact on the power system. Therefore, this paper holds that the tenacity of the power grid refers to the ability of the power grid to predict, retain and release all kinds of energy, that is, the means and ability to adapt to environmental changes and respond to external disturbances. Therefore, from the concept of tenacious grid, this paper discusses the research field and evaluation index of flexible.

Traditional anomaly detection has some shortcomings, such as time delay, low sensitivity and lack of overall situation. The wide area measurement system (WAMS) and synchronous phase measurement unit (PMU) that can be widely applied can improve the anomaly detection level of distribution network. The maximum and minimum eigenvalue method of random matrix is first applied in the field of cognitive radio to detect weak signals in radio networks. An algorithm for anomaly detection of distribution network based on the maximum and minimum eigenvalue method is proposed in the paper. The method adopts the global sampling data of PMU to detect anomaly of distribution network in real time, so as to improve the detection sensitivity. The algorithm and its threshold are deduced through theoretical analysis. The effectiveness and feasibility of the method are verified by simulation of short-circuit anomaly and harmonic anomaly. Case analysis shows that this method can detect disturbance signal quickly, sensitively and accurately, and has good robustness.

This paper proposes an optimization control of micro-grid system economy operation model. It coordinates the new energy and storage operation with diesel generator output, so as to achieve the economic operation purpose of micro-grid. In this paper, the micro-grid network economic operation model is transformed into mixed integer programming problem, which is solved by the mature commercial software, and the new model is proved to be economical, and the load control strategy can reduce the charge and discharge times of energy storage devices, and extend the service life of the energy storage device to a certain extent.

Trend predicting of distribution network operation states is an important basis for understanding the safe operation of distribution network. In view of the impacts of measurement data and prediction accuracy, a novel trend predicting method of distribution network operation states is proposed in this paper. It is based on an improved multi-dimensional grey-neural network hybrid coordination prediction model and a branch current forward and backward substitution power flow model considering Phasor Measurement Unit (PMU). This trend predicting method analyzes the errors existing in the historical measurement data and establishes the distribution network measurement database as the input of the trend prediction. Improved multi-dimensional grey-neural network hybrid coordination prediction model is designed to achieve high-precision power prediction in the short term. The result of the power prediction is used as the input of the branch current forward and backward substitution power flow model utilizing PMU to calculate the system trend in the future and to implement the trend predicting of distribution network operation states. The feasibility and effectiveness of the proposed method are verified by analyzing the predicted and true values of IEEE33 system.

As the penetration rate of distributed generation is increasing on the user side, an on-line energy management system for the building microgrid based on the improved gray prediction is proposed. Firstly, the whole model of building microgrid is established, including the energy storage system model, the electric vehicle model, the interaction model with the upper power grid and the controllable load model. Then the basic gray prediction model is improved to make it predict the real-time electricity price, the photovoltaic power generation and the home loads, and also improve the prediction accuracy. And then an online energy management system is put forward for building microgrid, to solve the daily optimal electricity plan aiming at the maximum profit of home energy and stabilizing the power fluctuation of tie line. Finally, the effectiveness of the energy management strategy is verified by comparing the control effect under different energy management modes for building microgrid.