Smart Grid

Journal Information
ISSN / EISSN : 2161-8763 / 2161-8771
Published by: Hans Publishers (10.12677)
Total articles ≅ 492
Archived in
SHERPA/ROMEO
Filter:

Latest articles in this journal

华邓 天
Published: 1 January 2022
Journal: Smart Grid
Smart Grid, Volume 12, pp 36-42; https://doi.org/10.12677/sg.2022.122005

Abstract:
In recent years, China’s power system has followed the pace of science and technology and achieved unprecedented development. Therefore, in order to ensure the stable operation of the transmission system, the detection and identification method of foreign matter adhesion fault of transmission line has become a research hotspot of relevant personnel in the power industry. In order to effectively identify and detect the foreign object attachment fault of transmission line, so as to improve the efficiency of power inspection, combined with the image characteristics of foreign object attachment fault of transmission line, this paper effectively improves the common SSD algorithm (Single Shot MultiBox Detector), replaces the VGG16 feature extraction network with ResNet50, and aims at the shortcomings of the original model in small target detection, the feature fusion module is designed and applied, and the data of 1241 foreign object attachment fault images of transmission line are expanded and made into a data set containing more than 5000 images, so as to train the target detection network model. Finally, the mean accuracy mAP (mean Average Precision) of the training data set is about 97%, which meets the requirements of fault detection accuracy.
旭于 佳
Published: 1 January 2022
Journal: Smart Grid
Smart Grid, Volume 12, pp 67-74; https://doi.org/10.12677/sg.2022.123008

Abstract:
As a high-quality renewable energy power generation technology, wind power generation can not only alleviate energy shortage, but also improve environmental pollution. However, with the increase of the proportion of wind power connected to the grid, the network loss of wind power system increases sharply. In this paper, taking the minimum active power network loss of the system as the objective function and the conventional generator set, wind turbine set, static reactive power compensator, capacitor reactor and transformer tap as the reactive power control resources, the mathematical model of reactive power optimization control of wind power system is established, and the particle swarm optimization algorithm is used to solve the model. Finally, based on MATLAB platform, the established mathematical model is analyzed in the IEEE30 node system after wind power grid connection. The results show that this method is effective and feasible in reducing the network loss of wind power system.
伟冯 宜
Published: 1 January 2022
Journal: Smart Grid
Smart Grid, Volume 12, pp 155-167; https://doi.org/10.12677/sg.2022.125016

Abstract:
With the penetration of distributed energy, such as photovoltaic and battery energy storage systems in the distribution system, how to improve the power quality based on the control strategy of the inverter presents new challenges. In this paper, from the perspective of inverter in intelligent microgrid, the basic principle of inverter in the intelligent microgrid and the classic inverter types are described; Different inverter topologies are analyzed and their different functional characteristics and advantages and disadvantages are summarized; This paper analyzes the problems and solutions that affect the power quality output, and summarizes the different control strategies of the current inverter. Finally, the future research direction of inverter technology has prospected.
伟冯 宜
Published: 1 January 2022
Journal: Smart Grid
Smart Grid, Volume 12, pp 130-140; https://doi.org/10.12677/sg.2022.124014

Abstract:
Smart microgrid combined with communication network has attracted great attention at domestic and overseas for its high flexibility, wide adaptability and controllable economy. Communication constraints are the key factors influencing the microgrid intelligent integrated scheduling. Firstly, the control structure of smart microgrid including hierarchical control and secondary control is briefly described, and the common communication constraints in microgrid such as communication network delay, communication bandwidth limitation and communication link uncertainty are comprehensively summarized. At the same time, the secondary control methods of smart microgrid under different communication constraints are analyzed, and the stability analysis methods of smart microgrid under various communication constraints are summarized. Finally, the development status and future direction of this field are discussed and prospected.
江曾 丕
Published: 1 January 2022
Journal: Smart Grid
Smart Grid, Volume 12, pp 141-153; https://doi.org/10.12677/sg.2022.124015

Abstract:
The under-frequency load shedding (UFLS) in the third line of defense of power system is one of the significant measures to prevent the rapid and continuous decline of the system frequency and ultimately maintain the stability of system frequency after disturbance. Meanwhile, when a large amount of clean energy is connected to the power grid, the frequency characteristics of the power system become worse. How to explore and exploit the optimal configuration strategy of UFLS under high penetration level of clean energy is a key issue to be solved urgently. Therefore, under the background of large-scale grid-connected clean energy, this paper deduces the correlation degree index which can effectively realize load shedding. On this basis, the improved scenario-based method is utilized to describe the uncertainty of clean energy. Further, the setting process of UFLS solution based on the adjustment power and steady-state frequency is proposed. Finally, taking the IEEE standard test system as an example, the validity of the proposed optimal configuration strategy of UFLS is verified by simulations and comparative analysis.
林丁 洪
Published: 1 January 2022
Journal: Smart Grid
Smart Grid, Volume 12, pp 107-118; https://doi.org/10.12677/sg.2022.124012

Abstract:
Low frequency oscillation occurs frequently in power system. Aiming at the problems of inaccurate positioning of oscillation source and large amount of calculation at present, based on the relationship and characteristics of forced oscillation energy function and energy conversion in the steady-state stage of oscillation, this paper proposes a disturbance source positioning method based on parameter identification on the basis of traditional Prony positioning disturbance source. This method is improved by combining the principal component method, which greatly reduces the amount of calculation and makes the disturbance source positioning more accurate when taking a large amount of data. Finally, a simulation model is established to verify that this method can locate the disturbance source more quickly than the traditional Prony method, and it is easy to perform the calculation online.
达潘 可
Published: 1 January 2022
Journal: Smart Grid
Smart Grid, Volume 12, pp 56-65; https://doi.org/10.12677/sg.2022.122007

Abstract:
Due to policy support, low cost and easy applicability, distribution photovoltaic systems (DPVSs) are increasingly popular among residential community. However, small-scale DPVSs of less than 10 kWp are always installed behind the meter (BTM), without metering the photovoltaic (PV) power generation separately, which results in the invisible of the PV power generation. Only access of net load data can result in non-optimal distribution network control and optimization, leading to a series of energy management problems. In order to solve the aforementioned problems, this paper proposes a BTM net load disaggregation method focusing on small-scale DPVSs, with only net load data of residential users in a community, without relying on weather data and models assumption. Considering that community users’ DPVSs usually exhibit approximate output characteristics, neighboring net load is used to extract PV power generation information as mutual proxies. After obtaining approximate PV proxy data by subtracting composite power of inter-users, Maximal Information Coefficient (MIC) is performed to obtain final PV power generation disaggregation results. Testing results show that the proposed method achieves considerable disaggregation accuracy in the absence of weather data.
仑庞 清
Published: 1 January 2022
Journal: Smart Grid
Smart Grid, Volume 12, pp 82-91; https://doi.org/10.12677/sg.2022.123010

Abstract:
In today’s world, the environmental problems in the world are becoming increasingly prominent, and the development of integrated energy system has become an important means to realize the low-carbon energy industry. Based on this, this paper proposes an integrated energy carbon emission optimization method aiming at carbon reduction. Firstly, the carbon emissions of all kinds of energy in the integrated energy system are analyzed. Secondly, aiming at reducing carbon emissions, the optimization model of carbon emissions of integrated energy is established and the particle swarm algorithm is used to solve the model. Finally, the simulation results show that the proposed method can not only effectively reduce the carbon emissions of the integrated energy system, but also increase the consumption level of wind power and photoelectric energy of the integrated energy system.
刘 艳
Published: 1 January 2022
Journal: Smart Grid
Smart Grid, Volume 12, pp 9-15; https://doi.org/10.12677/sg.2022.121002

Abstract:
With the development and progress of artificial intelligence technology, all aspects of our daily life have undergone tremendous changes, especially the application of convolutional neural networks in the fault detection of power conductors in power transmission lines, which has greatly eliminated power transmission. Potential safety hazards ensure people’s electricity consumption, but the application of conventional convolutional neural networks to visual tasks requires a lot of training data, and certain defects in the transmission line are extremely scarce. Collecting and marking these training data consumes huge manpower and material resources. Based on this, this paper proposes to apply self-supervised representation learning algorithm to the fault classification and recognition task of power conductors in transmission lines to alleviate the problem of data labeling difficulties. The self-supervised representation learning algorithm can learn from unlabeled samples and does not require negative sampling. It has higher training efficiency. In the experiment, the self-supervised representation learning algorithm is compared with other baseline methods and its performance is excellent. In the task of classification and identification of wire damage, the average accuracy can reach 0.87, which shows the effectiveness and practicability of the algorithm.
李 正
Published: 1 January 2022
Journal: Smart Grid
Smart Grid, Volume 12, pp 17-27; https://doi.org/10.12677/sg.2022.122003

Abstract:
The application of power routers in the energy Internet increases the diversity of power supply, and also solves the problem of multi-directional power flow. In this paper, a small-capacity single-phase AC and DC power router is designed according to the actual needs of home users. The AC and DC systems are connected by bidirectional DC/AC converters to ensure reliable power supply to the load. Since the output of distributed power is easily fluctuated by the weather, this paper proposes an improved sliding average algorithm for the grid-connected control strategy of power routers, which can obtain the output command power of distributed power. By controlling the distributed power output to track the command power, a smooth grid-connected power can be obtained and fluctuations can be reduced. Finally, the correctness of the proposed grid-connected control method is verified by simulation.
Back to Top Top