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Liu W.,North China Electrical Power University | Liang C.,North China Electrical Power University | Xu P.,North China Electrical Power University | Dan Y.,North China Electrical Power University | And 2 more authors.
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | Year: 2013

Power flow betweenness and its application in vulnerable line identification in the power system are presented. Compared with (weighted) betweenness models in which power flow is supposed to be not directional and transferred only through the shortest path, the presented model bases on current operating mode and flow distribution, can effectively reflect and quantify actual effect of each line by "plant-load" pair with a more comprehensible physical background, in which maximum available transmit power between generator and load is also considered. Meanwhile, to reflect the impact of the critical line fault on the power system, analytic hierarchy process (AHP) is presented to evaluate transmission line over-load, voltage-limit, and transient stability level comprehensively. The Evaluation results are more objective and close to power system characteristics. Numeric examples of the CEPRI36 and Gansu power system show critical line identification method proposed in this paper can better reflect the degree of importance of the line in the entire power grid, and the correctness and effectiveness are verified. © 2013 Chin. Soc. for Elec. Eng. Source


Li J.,Lanzhou University of Technology | Cao J.,Lanzhou University of Technology | Jiang M.,Gansu Electric Power Research Institute
Dianwang Jishu/Power System Technology | Year: 2011

Taking the measured audible noise data of 330 kV EHV transmission lines in Gansu power grid for example, a back propagation (BP) neural network-based approach to audible noise prediction is researched. Based on the interpretation and analysis of measured audible noise data of 330 kV single-circuit transmission lines with triangle structure, the dataset sample is obtained, then 13 factors that influence audible noise are taken as input variables and the values of audible noise as output variables, and then a BP neural network prediction model with 3-layer structure is built and the proposed prediction model is trained and verified by the dataset sample. Results of simulation verification, in which partial data of some 330 kV transmission lines in the dataset sample are utilized to predict the audible noise of the rest 330 kV transmission lines, show that the predicted results of audible noise of the rest 330 kV lines by the proposed method approximately conform to the measured audible noise data of these 330 kV lines in the dataset sample, thus the proposed approach can be used as a simple and effective method for audible noise prediction of EHV transmission lines. Source


Liu W.,North China Electrical Power University | Xie C.,North China Electrical Power University | Wen J.,North China Electrical Power University | Wang J.,North China Electrical Power University | Wang W.,Gansu Electric Power Research Institute
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | Year: 2013

Taking the minimum maintenance cost and expected energy not supplied (EENS) as objective functions, this paper built a multi-objective optimization model for maintenance scheduling of transmission network and proposed an improved multi-objective particle swarm optimization algorithm based on niche technology for the built model. Through getting a set of Pareto optimal solutions, the model can coordinate the economic and reliability objectives of maintenance scheduling optimization problem. The algorithm used a niche sharing mechanism to update particle's position so as to keep the diversity of solution and the uniformity of distribution. Besides, by means of leading in chaotic mutation to part of non-dominated particles, the global searching ability of the proposed algorithm was enhanced, and local optimum was also avoided. In order to make the algorithm apply to maintenance scheduling optimization problem better, this paper processed the constraints by using a penalty function, and selected the best compromise solution from the Pareto optimal solution set according to fuzzy membership degree, and provided the scientific decision basis for maintenance plan makers. Simulation of IEEE-RTS 79 bus system testify that this algorithm can avoid the premature phenomenon and local convergence effectively in solving transmission network maintenance optimization problem, and convergence to the Pareto optimal solution set rapidly. © 2013 Chinese Society for Electrical Engineering. Source


Liu W.,North China Electrical Power University | Wang J.,North China Electrical Power University | Xie C.,North China Electrical Power University | Wang W.,Gansu Electric Power Research Institute
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | Year: 2012

The essence of cascading failure in complex power system, which is the main reason of large-scale blackouts, is brittleness process when the brittleness source is excited. To study how large-scale blackouts take place and the defense measures, meanwhile, find out the high-risk lines, the author proposed a brittleness source identification model for cascading failure based on brittleness theory of complex system. From the view that brittleness is the nature of power system, the model used power flow entropy to measure the condition of power grid, and analyzed the mechanism of cascading failure by brittleness relevance and entropy increase from component and macroscopic aspects respectively. Take the identifying method of brittleness sources and brittleness relevance degree of grid components into consideration, a determining process of high-risk lines was given. Through simulation of cascading failure, brittle risk entropy was applied to assess the impact of component outage from power grid operation and the load removed, and this can provide a basis for defensive strategy making. Taking Gansu power network as an example, the feasibility and effectiveness of the proposed defense model were validated. © 2012 Chinese Society for Electrical Engineering. Source


Wang X.-L.,Lanzhou University of Technology | Li J.-L.,Lanzhou University of Technology | Ma C.-X.,Gansu Electric Power Research Institute
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2013

In order to enhance the ability of wind farm actively integrated into grid, the super short-term prediction model of wind speed and power is established. Then with the goal of the maximum wind power capture and the smooth output power and taking generator speed and pitch angle as control variables, the minimization control criterion is set out and the corresponding multi-objective optimization models are established to reduce mechanical and pitch angle stresses. The genetic algorithm is used to solve the optimal solution which is applied to wind power generation system to optimize performances. A 1.5 MW variable speed constant frequency wind power generation system is studied by the computer simulation. The results show that the output power is increased and the turbulence of power in low frequency is reduced compared with the traditional maximum power point tracking (MPPT) control strategy. Source

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