A Bio-Inspired Multi-Agent System Framework for Real-Time Load Management in All-Electric Ship Power Systems
MetadataShow full item record
All-electric ship power systems have limited generation capacity and finite rotating inertia compared with large power systems. Moreover, all-electric ship power systems include large portions of nonlinear loads and dynamic loads relative to the total power capacity, which may significantly reduce the stability margin. Pulse loads and other high-energy weapon loads in the system draw a large amount of power intermittently, which may cause significant frequency and voltage oscillations in the system. Thus, an effective real-time load management technique is needed to dynamically balance the load and generation to operate the system normally. Multi-agent systems, inspired by biological phenomena, aim to cooperatively achieve system objectives that are difficult to reach by a single agent or centralized controller. Since power systems include various electrical components with different dynamical systems, conventional homogeneous multi-agent system cooperative controllers have difficulties solving the real-time load management problem with heterogeneous agents. In this dissertation, a novel heterogeneous multi-agent system cooperative control methodology is presented based on artificial potential functions and reduced-order agent models to cooperatively achieve real-time load management for all-electric ship power systems. The technique integrates high-order system dynamics and various kinds of operational constraints into the multi-agent system, which improves the accuracy of the cooperative controller. The multi-agent system includes a MVAC multiagent system and a DC zone multi-agent, which are coordinated by an AC-DC communication agent. The developed multi-agent system framework and the notional all-electric ship power system model were simulated in PSCAD software. Case studies and performance analysis of the MVAC multi-agent system and the DC zone multi-agent system were performed. The simulation results indicated that propulsion loads and pulse loads can be successfully coordinated to reduce the impact of pulse loads on the power quality of all-electric ship power systems. Further, the switch status or power set-point of loads in DC zones can be optimally determined to dynamically balance the generation and load while satisfying the operational constraints of the system and considering load priorities. The method has great potential to be extended to other isolated power systems, such as microgrids.
SubjectAll-electric ship power system
real-time load management
Feng, Xianyong (2012). A Bio-Inspired Multi-Agent System Framework for Real-Time Load Management in All-Electric Ship Power Systems. Doctoral dissertation, Texas A&M University. Available electronically from