In order to obtain the primary parameters and operating characteristics of a DC motor without directly measuring its torque and rational speed, it is proposed to use a PC and a data acquisition card to acquire both th...In order to obtain the primary parameters and operating characteristics of a DC motor without directly measuring its torque and rational speed, it is proposed to use a PC and a data acquisition card to acquire both the dynamic and static data of armature current to establish the performance of a DC permanent magnet motor. The accuracy and validity of this virtual test system proposed were verified by comparing the measurements made with the system proposed with the measurements made with conventional torque meters. It is concluded from the results of comparison that from the mathematic model established for the DC permant magnet motors, both major parameters and operating characteristics can be directly established for the DC motors without measuring their torques and rotational speed, a perfect on line measurement and test system has been established for the DC permanent magnet motors using the theory of virtual test system. The system proposed features shorter test time, higher efficiency and lower cost.展开更多
This paper proposes an efficient method for optimal power flow solution （OPF） using particle swarm optimization （PSO） technique. The objective of the proposed method is to find the steady state operation point in ...This paper proposes an efficient method for optimal power flow solution （OPF） using particle swarm optimization （PSO） technique. The objective of the proposed method is to find the steady state operation point in a power system which minimizes the fuel cost, while maintaining an acceptable system performance in terms of limits on generator power, line flow limits and voltage limits. In order to improvise the performance of the conventional PSO （cPSO）, the fine tuning parameters- the inertia weight and acceleration coefficients are formulated in terms of global-local best values of the objective function. These global-local best inertia weight （GLBestlW） and global-local best acceleration coefficient （GLBestAC） are incorporated into PSO in order to compute the optimal power flow solution. The proposed method has been tested on the standard IEEE 30 bus test system to prove its efficacy. The results are compared with those obtained through cPSO. It is observed that the proposed algorithm is computationally faster, in terms of the number of load flows executed and provides better results than the conventional heuristic techniques.展开更多
文摘In order to obtain the primary parameters and operating characteristics of a DC motor without directly measuring its torque and rational speed, it is proposed to use a PC and a data acquisition card to acquire both the dynamic and static data of armature current to establish the performance of a DC permanent magnet motor. The accuracy and validity of this virtual test system proposed were verified by comparing the measurements made with the system proposed with the measurements made with conventional torque meters. It is concluded from the results of comparison that from the mathematic model established for the DC permant magnet motors, both major parameters and operating characteristics can be directly established for the DC motors without measuring their torques and rotational speed, a perfect on line measurement and test system has been established for the DC permanent magnet motors using the theory of virtual test system. The system proposed features shorter test time, higher efficiency and lower cost.
文摘This paper proposes an efficient method for optimal power flow solution （OPF） using particle swarm optimization （PSO） technique. The objective of the proposed method is to find the steady state operation point in a power system which minimizes the fuel cost, while maintaining an acceptable system performance in terms of limits on generator power, line flow limits and voltage limits. In order to improvise the performance of the conventional PSO （cPSO）, the fine tuning parameters- the inertia weight and acceleration coefficients are formulated in terms of global-local best values of the objective function. These global-local best inertia weight （GLBestlW） and global-local best acceleration coefficient （GLBestAC） are incorporated into PSO in order to compute the optimal power flow solution. The proposed method has been tested on the standard IEEE 30 bus test system to prove its efficacy. The results are compared with those obtained through cPSO. It is observed that the proposed algorithm is computationally faster, in terms of the number of load flows executed and provides better results than the conventional heuristic techniques.
