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Yu J.-Y.,North China Electrical Power University | Wang Z.-P.,North China Electrical Power University | Sun J.,Yantai Power Supply Company | Yang G.-S.,China Electric Power Research Institute
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2014

To solve the premature issue of particle swarm optimization (PSO), this paper introduces the idea of simulated annealing into the dynamic inertia weight adjustment to make the inertia weight decrease with the increase in the number of iterations and avoid the algorithm falling into local optimization. And it uses population fitness variance to judge the particles' similarity in order to mutate the particle adaptively, i.e. control the mutation number "big then small" and select particles randomly and rebuild displacement. In order to improve the search speed of PSO algorithm, the PSO algorithm and branch exchange algorithm are combined, in which the particle displacement is just the contact switch connecting non-fault power-lossing area and normal area, as for the scheme of forming looped network, the branch exchange algorithm is used to determine the section switch to open. The combination of PSO and branch exchange could ensure the radial operation requirements of distribution grid, and make the network formed by a lower net loss. The example shows that the distribution network fault recovery based on branch exchange-PSO can quickly restore power supply of power failure area. Source

Wang J.,Harbin Institute of Technology | Wang J.,ShenYang Agricultural University | Cai X.,Harbin Institute of Technology | Ji F.,Harbin Institute of Technology | Li X.,Yantai Power Supply Company
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2012

With the rapid development of renewable energy power generation, its intermittence and stochastic of output power have significant influence on available transfer capability (ATC). The characteristics of the renewable energy power generation, e. g. the intermittence, stochastic, load fluctuation, and status uncertainty, are simulated through Monte Carlo simulation method. The ATC under specific status and parameters of system are solved through optimal power flow. The probability density of ATC samples is defined by applying probability statistics theory to establish a risk benefit model, and to achieve ATC with maximum comprehensive benefits. To analyze the influence of renewable energy power generation on ATC, with respect to position of power generation equipment, uncertainty of power output and penetration level etc. The method is validated by simulation on a modified IEEE 118 system involving wind power and solar power. Source

Chen F.,Shandong University | Chen F.,University of Jinan | Han X.,Shandong University | Kang K.,Yantai Power Supply Company
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2011

In generalized state estimation, to identify the misinformation of the connected region formed by the closed breakers, the concept of virtual breakers is used to build the minimum feature network based on the generalized network that does not affect the quality of identification. In addition to analog measurements, zero-voltage-drop for virtual closed switch as equality constraint is added to formulate the model of weighted least squares with equality constraints. The relation between residual and Lagrange multiplier from the probability standpoint is discussed alongside the approach to identifying bad data. Furthermore, it can be seen that the identification of the bad analog data is distinguished from that of the bad breaker status under normal conditions. Finally, the validity of the model and algorithm is verified with a three-node simple system and the data from Yantai grid of Shandong Province. © 2010 State Electric Power Research Institute Press. Source

Huamao Z.,North China Electrical Power University | Yazhou L.,North China Electrical Power University | Yazhou L.,Yantai Power Supply Company | Shusheng Z.,North China Electrical Power University
IEEE Sensors Journal | Year: 2016

Ultra-high-frequency (UHF) sensor is the vital component of a partial discharge detection system and its coupling performance is affected by structural parameters. On the basis of the cavity model theory, this paper studied the influence of the disc electrode diameter, the thickness, the dielectric constant of the dielectric substrate, and the position of the coaxial connection on the performance of the disc-type UHF sensor with the application of the XFdtd software. The simplified finite-difference time-domain simulation model for the gigahertz transverse electromagnetic (GTEM) cell has been established, and the influence of the coaxial feed position on the performance of the disc-type UHF sensor is studied via the frequency domain effective heights in the simulation. The result shows that as the disc electrode diameter, the thickness, and the dielectric constant of the dielectric substrate increase, the working frequency band shifts toward the reducing direction. The position of the coaxial connection has an obvious effect on the resonant mode of sensor, too. © 2016 IEEE. Source

Li Z.,Shandong University | Han X.,Shandong University | Yang M.,Shandong University | Lei Y.,Shandong University | Kang K.,Yantai Power Supply Company
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2010

As wind power capacity in a power grid reaches a certain level, the system dispatch becomes more complex for efficient utilization of wind power. In a power grid with wind farms connected, there is a contradiction between fuel cost and effective utilization of wind power in the scheduling process. The fuel cost saved by the wind power is taken as the measurement for the value of wind power. A scheduling method considering wind power integration is proposed so that a fluctuation range can be calculated to coordinate the fuel cost and wind power grid connection. Case study in the Yantai power grid shows that the method proposed is appropriate for the power grid scheduling in accordance with the principle of economic generation dispatch. © 2010 State Grid Electric Power Research Institute Press. Source

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