Service oriented architectural models for power system transient stability analysis

Abstract

The main objective of this research is to develop enhanced service oriented architectural models for power system transient stability analysis using Web service technologies. Due to deregulated environment in the power sectors and unpredicted increase in demand, there is an exponential growth in power system networks to meet the desired operational level. As the size of power systems is large, data exchange is a major concern because of the complex nature of power system operations. The exchange of data needs to be reliable and adaptable to different types of software used for power system operations. The computation of power system services has become cross-discipline that covers the current technology of bridging the gap between conventional Web enabled power system analysis and the application of recent distributed concepts of IT Services. To cope up with the new paradigm, a distributed architecture that uses the concepts popularized Internet technologies is required. The Service Oriented Architecture (SOA) based on Web services standards provides a mechanism for open and flexible interaction between heterogeneous power system operations. The proposed SOA model includes stability services which are accessible to the power system clients when the system is subjected to large disturbances. The stability services are configured and deployed in the service provider and then published in a registry for enabling universal visibility and access to the power system clients. The message oriented style of SOA using Simple Object Access Protocol (SOAP) makes the power system service provider and the clients to exist in a loosely coupled environment. The performance analysis of the proposed distributed models using JAX-RPC, SOA and Cloud Computing for representing and solving transient stability problems has been carried out for the sample and real-time systems. The RTT has been considered as the performance measure and it has been analyzed with respect to different distributed models by considering the number of clients