Effective data compression model for on-line power system applications

The main objective of this paper is to develop an efficient data compression model for online power system applications such as load flow studies, state estimation, contingency analysis etc. and to calculate the round triptime taken for sending the compressed data in client/server architecture. Martin Burtscher algorithm is used for data compression since most of the power system data is expressed in per unit representation which is in floating point format. Many research works have been reported for representing and solving power system problems in distributed environments which include RMI, Component based, SOA and Grid computing. As the size of power systems is growing larger and larger due to increase in demand and as the interconnections between large power systems may vary from time to time due to addition of new generating units and due to geographic conditions, it becomes difficult to estimate the current operating states of the real time electric power system networks and data communication between the networks becomes difficult. The proposed method of power system data compression finds faster rate of data communications where the data is required for real–time analysis in a distributed environment