Grid Computing

Abstract

Power systems have been reformed from isolated plants into individual systems and interregional/international connections throughout the world since the 1990s (Das, 2002). Due to constant expansions and deregulations in many countries, future power systems will involve many participants, including generator owners and operators, generator maintenance providers, generation aggregators, transmission and distribution network operators, load managers, energy market makers, supplier companies, metering companies, energy customers, regulators, and governments (Irving et al., 2004). All these participants need an integrated and fair electricity environment to either compete or cooperate with each other in operations and maintenances with secured resource sharing. Moreover, it has been widely recognised that the Energy Management Systems (EMS) are unable to provide satisfactory services to meet the increasing requirements of high performance computing as well as data resource sharing (Chen et al., 2004). Although many efforts have been carried out to enhance the computational power of EMS in the form of parallel processing, only the centralized resources were adopted, and equal distributions of computing tasks among participators were assumed. In parallel processing, tasks are equally divided into a number of subtasks and then simultaneously dispersed to all the computer nodes.