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Huang K.,Shanghai University of Electric Power | Wang X.,Shanghai JiaoTong University | Zheng Y.H.,Shanghai JiaoTong University | Li L.X.,Shanghai JiaoTong University | Xiu S.H.,Siping Power Supply Company
Advanced Materials Research | Year: 2014

Economic Load Dispatch (ELD) is a critical matter of improving the operating efficiency of power system and reducing the cost of generating electricity. In this paper, an Artificial Fish Swarm Algorithm (AFSA) which takes network loss into account is designed to search the optimization. Firstly convert the capacity of the generating units in decimal into a binary number which means the location of an artificial fish. And then foraging behavior of fish school algorithm is utilized to make a successive comparison of fitness within the visual distance of current fish. Additionally to avoid getting into local optimization, the position of current fish is changed with a small probability. The simulation results suggest that the algorithm is efficient and feasible in the case of less precision. © (2014) Trans Tech Publications, Switzerland.


Liu J.,Shanghai JiaoTong University | Zheng Y.,Shanghai JiaoTong University | Yao G.,Shanghai JiaoTong University | Zhou L.,Shanghai JiaoTong University | And 3 more authors.
Lecture Notes in Electrical Engineering | Year: 2014

In order to solve the neutral-point imbalance problem and to improve the control precision of three-phase four-wire STATCOM, this chapter focused on the three-phase four-wire STATCOM control method based on neural network PI controller. First by analysis of the voltage imbalance problem of the split capacitors in three-phase four-wire STATCOM, a neutral-point balance control method based on the zero-sequence current is proposed. Then in order to improve the control precision, the neural network PI controller is introduced into three-phase four-wire STATCOM. Finally, the neutral-point balance control and neural network PI controller are combined together to get the neural network triple close-loop control method. Simulation result illustrates that the proposed control method is capable of neutral-point balancing control in three-phase four-wire STATCOM and the control precision is higher than that of the conventional control method. © 2014 Springer Science+Business Media New York.


Wang J.,Shanghai JiaoTong University | Zheng Y.,Shanghai JiaoTong University | Yao G.,Shanghai JiaoTong University | Wang X.,Shanghai JiaoTong University | And 2 more authors.
Dianli Zidonghua Shebei/Electric Power Automation Equipment | Year: 2011

The single-phase shunt APF is taken as the hardware platform in studying the balance between convergence speed and steady state accuracy of adaptive harmonic current detection algorithm. The dynamic factor least mean square based on the adaptive noise cancellation technology is proposed to detect APF harmonics. The momentum term is introduced and the estimated mean of error signal in adjacent time point is used to control the updating of step size, which greatly increases the convergence speed. The dynamic factor term is applied to adjust the error again. Performance analysis is carried out for the proposed algorithm. Simulation and APF experiments show its faster dynamic response, less steady state offset under low SNR conditions and better anti-noise capability.


Wang C.,Shanghai JiaoTong University | Wang X.,Shanghai JiaoTong University | Yao G.,Shanghai JiaoTong University | Zheng Y.-H.,Shanghai JiaoTong University | And 2 more authors.
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2012

A mathematical model of reactive power in the distribution network optimal allocation is established, in which the least active power loss is taken as objective function and node voltage beyond limit and the generator reactive power output beyond limit as penalty function. Then the chaotic particle swarm optimization based on golden section (GCPSO) is designed to calculate the above model. This method divides the particle swarm into standard particle and chaos particle using the judge principles based on golden section according to the level of fitness. It solves the problems of easily falling into local optimum if using PSO and repeating searching part of the solution if using chaotic optimization. Using GCPSO can be more effective in searching the global optimal solution, and the speed of reactive power optimization can also be improved. The algorithm is thus more applicable to solving the problem. The simulation results show that the method is technically feasible and effective.


Zhou C.,Shanghai JiaoTong University | Zheng Y.H.,Shanghai JiaoTong University | Yao G.,Shanghai JiaoTong University | Li L.X.,Shanghai JiaoTong University | And 2 more authors.
Applied Mechanics and Materials | Year: 2014

Aiming to dealing with the problems of power factor compensation and the limitations of the conventional PI controller in the Static Synchronous Compensator (STATCOM), a new control strategy based on multi-model and neural network PI controller is proposed. This control scheme applied the multi-model and neural network technology to the PI controller to meet the accuracy and speed of the power factor compensation under different impact loads. Meanwhile, the neural network technology is used to tune the PI controller parameters values according to an optimal control law, which can meet the requirements of full range working conditions and optimality. Simulation experiments show that compared to the traditional PI controller, PI controller based on multi-model and neural network is proved to be better capable of adapting to the changes of impact loads with a higher compensating precision, which makes the power factor maintained at about 1 after compensation. © (2014) Trans Tech Publications, Switzerland.

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