全局安时无功优化调度的MAS方法

电力系统无功优化调度问题在数学上属于一种具有多目标、多不确定因素、多约束、多极值、非线性的组合最优化问题。通常的寻优方法遇到了许多困难，因此目前无功优化调度技术的应用还停留在计算规模较小的地区局部电网中。为实现电网全局实时的无功优化调度，提出一种基于分布式人工智能中多Agent系统(MAS)的无功优化调度模型。将全网无功调度按区域分解为若干个相互关联的调度子系统进行分布式求解，全局调度系统采用网络控制结构，各调度子系统则采用分层控制结构。在各子网局部实现无功优化的基础上，采用多Agent智能协调技术实现全网的全局无功优化。

Multi-agent system based approach for real-time global optimal reactive power dispatch

Optimal Reactive Power Dispatch (ORPD) of power systems is one of combinatorial optimization problems with multi-object, multi-uncertainty, multi-restriction, multi-extremum and non-linear characteristics mathematically. It is difficult to solve for the traditional optimization methods so that the technique of ORPD is applied to nothing more than small-scale local electric networks. To realize real-time global ORPD of power systems, this paper presents an ORPD model based on Multi-Agent Systems (MAS), a technique of Distributed Artificial Intelligence. The ORPD system of whole power network is decomposed some interacting sub-systems according as terrains to process distributed problem solving. A network control structure is adopted for the global dispatch system and a layer control structure for each sub-system. On the basis of local ORPD of sub-networks, the real-time global ORPD of power systems can be achieved through multi-agent intelligent coordination technique.