Experiences in Delivering Power System Decision Support Tools over the Web Using Software-as-a-Service (SaaS) Model

Abstract

Power System Analytics Applications have always been available only as in-premise licensed software -- the use of a SaaS model for delivering the Analytics to the user is a first in the history of the power sector. In this paper, we describe how SaaS based webDNA architecture [1] can be extended to facilitate common power system data repository and associated analytics. We present case studies in delivering two power system decision support applications using this platform. First case study details the experience gained from providing Short Term Load Forecast (webSTLF) service to a leading private electricity distribution company in India. The second case study shares the experiences from delivering a Transmission System Usage Cost and Loss Allocation service (webNetUse) to the electricity regulators and system operators in India. Experience with managing various aspects critical to success of SaaS model like data security, scalability, usability, high availability and disaster recovery is described.