Advanced Materials Research Vols. 986-987

Abstract: A dual-stator toroidal motor with hybrid excitation was proposed and its structure and operating principal were introduced. The spiral currents of worm armature coils were resolved into two orthogonal components. The FEM analytic models for current components were built. Distributions of static magnetic field were simulated. Air gap flux density curves were obtained. The simulation results justify the rationality of the electromagnetic parameters of the motor. The research results are useful for analyzing electromagnetic characteristics of the motor, and offer meaningful instruction for further research and practical application of the novel motor.

Abstract: in practical application of SVC, unbalanced load system exists on many sites, and the voltage at system access point is required to meet the demand of power grid operation. This paper describes a SVC constant voltage control method for an unbalanced load system. the control algorithm controls the voltage at evaluation point to reach the preset range while compensating reactive power of unbalanced load system. the control method could compensate an unbalanced load system into a balanced system, at the same time, the voltage at access point could meet the demand of power grid operation. This control method is particularly applicable to reactive control requirements of steel mills, wind power, solar power grid systems. This algorithm has been applied in Lishizhai 66kV SVC Project in Fushun, inhibits three-phase unbalance of the grid, has achieved good compensation effect.

Abstract: To realize the electric vehicle braking energy recycling and driving smooth, bipolar PWM modulation mode is often adopted. To avoid the bridge arm shoot-through, a dead zone needs to be set in the complementary upper and lower bridge arm driving signal. Using hardware circuit dead zone setting has the advantages of simple setting and high reliability, is often used in the integrated driving module, however different dead zone mode has different influence on the inverter output voltage. This paper carried analysis on motor speed nonlinear problems caused by output voltage jump around a specific duty ratio in hardware dead zone setting mode, and gives the improvement of hardware circuit. Simulation and experimental results indicate that the method can well solve the output voltage jump in the vicinity of a specific duty ratio problem.

Abstract: The optimal energy saving routing algorithm proposed in this paper is based on the shortest path tree. This algorithm introduces the concept of node classification and builds the weight function based on link energy consumption factor, neighbor node’s residual energy factor and type weight and so on. It uses different weight factor according to different types of nodes, and finally generates the shortest path tree, all nodes send data to sink node along the shortest path tree. The simulation results show that the algorithm can prolong the network life time, balance energy consumption of each node, and reduce the average network delay.

Abstract: This paper proposes a way-predicting algorithm which is specially equipped with a Partial Tag Comparison Filter (PTCF) to reduce the energy consumption in high associative D-caches. Conventional way-predicting algorithm achieves good performance and energy efficiency on I-cache which usually can guarantee the high prediction accuracy. However, the D-cache usually cannot reach such high prediction accuracy; therefore it suffers unavoidably from severe prediction inaccuracy penalties. The introduced PTCF aims at reducing energy penalties in case of prediction-miss and thus brings improvement in energy efficiency. The experiments show that the new D-cache reduces energy consumption by about 20%~60% without any latency degradation compared to conventional way-predicting D-cache.

Abstract: Audible noise prediction is a hot research area in power transmission engineering in recent years, especially come down to AC transmission lines. The conventional prediction models at present have got some problems such as big errors. In this paper, a prediction model is established based on BP network, in which the input variables are the four factors in the international common expression of power line audible noise and the noise value is the output. Take multiple measured power lines as an example, a train is made by the BP network and then the prediction model is set up in the hidden layer of the network. Using the trained model, the audible noise values are predicted. The final results show that the average absolute error in absolute terms of the values by the audible noise prediction model based on BP neural network is 1.6414 less than that predicted by the GE formula.

Abstract: With increasingly complex of the power grid structure and increasingly user requirements of power quality, Power grid voltage reactive power optimization is still the difficult points in power system operation control. This paper introduces the general optimization methods of multi-objective reactive power optimization, intelligent algorithm, the development of the hybrid method, and their respective advantages, disadvantages and improvement; It also analyzes and summarizes the simplification of search space for reactive power optimization and the key issues and research development trend of the real-time reactive voltage control system.

Abstract: In order to cope with the defects of traditional particle swarm optimization (PSO) algorithm, such as its prematurity and deficiency in global optimization, a cloud model migration particle swarm optimization (CMMPSO) algorithm is proposed. Firstly, the X-condition generator based on Cloud model is introduced to adjust the inertia weights of particles; then migration action is implemented to lead the flight of global optimal particle. In allusion to the mixed integer programming problem of reactive power optimization, discrete variables are treated as continuous variables in early iterations, and a discretization operation based on Gaussian penalty function is conducted in later stages. Taking the minimum network loss and minimum voltage offset as objective functions, simulations of IEEE 30-bus system is performed to verify the feasibility and effectiveness of the proposed algorithm.

Abstract: Clustering algorithm can effectively solve the imbalance of energy consumption of different nodes. Based on the analysis of traditional LEACH protocol, we propose an improved sensor network clustering routing protocol, which reduced the cost of control information in formation process of clusters by adopting a new kind of competition parameters of cluster head, so as to solve the problem of energy heterogeneous of network node. The simulation results show that the protocol can effectively save the energy consumption of the nodes, and prolong the network life time.

Abstract: Load modeling has become a critical problem that is urgent to be solved in power system modeling. In this paper, CQDPSO algorithm, a hybrid optimization algorithm that combines quantum delta-potential-well-based particle swarm optimization (QDPSO) algorithm and chaotic optimization algorithm (COA), is proposed to identify parameters of the selected load model. Numerical results illustrate that the proposed method can improve the accuracy and reduce the computation complexity for load model parameter identifications.