A Multi-Agent based distributed computing platform for new generation of EMS

In order to make the platform more effective, reliable and flexible, Multi-Agent technology has been used to construct a distributed computing platform for New generation of EMS (N-EMS) in this paper. Staged Event Driven Architecture (SEDA) model and cluster-computing technology are proposed to implement the agents for a single function, and then taking Blackboard model as a media, these agents are coordinated and integrated into a full-functional application for EMS, which makes all the agents deployed in the EMS are loosely coupled and can be plugged-in and plugged-out dynamically. The distributed computing platform developed in this paper has been used by the N-EMS and the results from field operation shows that this distributed computing platform can satisfy the needs for huge amount of calculations for N-EMS.

I. Introduction

Agent is an important concept in computer science and distributed artificial intelligence, which represents a new method to conceptualize, describe and implement complex systems. In recent years, the application of Multi-Agent System (MAS) technology in power engineering field has received more and more attention. A range of applications have been developed with this method, including fault diagnostics[1], power market simulation[2], power grid control[3], substation automation [4], voltage control[5], etc. The Intelligent System Subcommittee of IEEE PES has also formed a working group to investigate how the MAS can be used in power system. In 2007, the working group published paper [6] to report their research result. The paper [6] has examined the great potential value of MAS technology to power industry, and also defines some key technical issues which must be addressed before this technology can be successfully employed in the power and energy sector, such as the necessity to develop an effective, reliable and flexible agent platform and a toolkit to reduce complexity in agent development, as well as the issue how agents communicate with each other.