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2023-01-20
An, Guowei, Han, Congzheng, Zhang, Fugui, Liu, Kun.  2022.  Research on Electromagnetic Energy Harvesting Technology for Smart Grid Application. 2022 Asia-Pacific International Symposium on Electromagnetic Compatibility (APEMC). :441—443.
The electromagnetic energy harvesting technology is a new and effective way to supply power to the condition monitoring sensors installed on or near the transmission line. We will use Computer Simulation Technology Software to simulate the different designs of stand-alone electromagnetic energy harvesters The power generated by energy harvesters of different design structures is compared and analyzed through simulation and experimental results. We then propose an improved design of energy harvester.
2021-12-02
Wang, Zhiwen, Hu, Jiqiang, Sun, Hongtao.  2020.  False Data Injection Attacks in Smart Grid Using Gaussian Mixture Model. 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV). :830–837.
The application of network technology and high-tech equipment in power systems has increased the degree of grid intelligence, and malicious attacks on smart grids have also increased year by year. The wrong data injection attack launched by the attacker will destroy the integrity of the data by changing the data of the sensor and controller, which will lead to the wrong decision of the control system and even paralyze the power transmission network. This paper uses the measured values of smart grid sensors as samples, analyzes the attack vectors maliciously injected by attackers and the statistical characteristics of system data, and proposes a false data injection attack detection strategy. It is considered that the measured values of sensors have spatial distribution characteristics, the Gaussian mixture model of grid node feature vectors is obtained by training sample values, the test measurement values are input into the Gaussian mixture model, and the knowledge of clustering is used to detect whether the power grid is malicious data attacks. The power supplies of IEEE-18 and IEEE-30 simulation systems was tested, and the influence of the system statistical measurement characteristics on the detection accuracy was analyzed. The results show that the proposed strategy has better detection performance than the support vector machine method.
2017-03-08
Wang, X., Teng, Y., Song, M., Wang, X., Yuan, H..  2015.  Joint Optimization of Coverage and Capacity Based on Power Density Distribution in Heterogeneous Cellular Networks. 2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC). :251–255.

The paper presents a joint optimization algorithm for coverage and capacity in heterogeneous cellular networks. A joint optimization objective related to capacity loss considering both coverage hole and overlap area based on power density distribution is proposed. The optimization object is a NP problem due to that the adjusting parameters are mixed with discrete and continuous, so the bacterial foraging (BF) algorithm is improved based on network performance analysis result to find a more effective direction than randomly selected. The results of simulation show that the optimization object is feasible gains a better effect than traditional method.