Pulsed power network with potential gradient method for scalable power grid based on distributed generations

Abstract

The potential gradient method is proposed for system scalability of pulsed power networks. The pulsed power network is already proposed for the seamless integration of distributed generations. In this network, each power transmission is decomposed into a series of electric pulses located at specified power slots in consecutive time frames synchronized over the network. Since every power transmission path is pre-reserved in this network, distributed generations can transmit their power to individual consumers without conflictions among other paths. In the network operation with a potential gradient method, each power source selects its target consumer that has the maximum potential gradient among others. This gradient equals the division of power demand of the consumer by the distance to its location. Since each of the target consumer selection is shared by power routers within the power transmission path, the processing load of each system component is kept reasonable regardless of the network volume. In addition, a large-scale power grid is autonomously divided into soft clusters, according to the current system status. Owing to these properties, the potential gradient method brings the system scalability on pulsed power networks. Simulation results are described that confirm the performance of soft clustering.