Smart Grid Analytics : What it really means?
In many of the meetings with Utility executives and experts in last couple of month, I noticed one common theme that is "Analytics". Almost all of the people I meet these days in Smart Grid circles talk about Analytics. As one of the favorite subject I thought of sharing my thoughts on this subject.
Analytics is a very broad topic and has a different meaning to different people.
Hence I like to use a new term when talking about analytics, that is "Contextual Analytics", which can do the justice to the definition of analytics based on the audience one is talking to. What I mean by "Contextual Analytics" is that the objective of outcome or purpose of analytics will differ in different contexts, e.g. when you talk to an executive or manager responsible for grid operations he will have need to have "Operational Analytics", v/s an executive responsible for program management of large Smart Grid Programs where the context will change with resepect to what will make sense to Program Director/Manager. Similarly an executive responsible for Customer Service Operations will have a different needs for analytics than an executive responsible for Regulatory Affairs or Power Delivery.
This is what I call "Contextual Analytics". Hence in the context of Smart Grid I don't think a single definition of Analytics can cover all aspects of Smart Grid Analytics.
So what does Analytics really mean in the context of Smart Grid?
I would say Analytics in the Smart Grid context is the basic building block to implement a Decision Support System that will help shape the day to day operation of the Utility of The Future.
Why so? Well let's consider this, almost each and every business unit/department of an Utility (implementing Smart Grid) has embarked on a project that is going to generate new kind and category of data. The understanding of this new kind and category of data does not exist because there is no precedence to it. These new data will have to be correlated and analyzed in order to make business sense and take business decision out of this data. Classically Analytics has been performed on historical data and very few use cases (and instances of these use cases) can be found where historical data is correlated with the new data for the purpose of analytics. Smart Grid needs both classical analytics as well as real-time and near real-time analytics for effective and efficient analytics that can deliver business value.
An ideal Smart Grid Analytics will be able to collect, correlate and analyze the data and events from heterogeneous systems and applications across business functions, operational technology and information technology and produce actionable analytics with a single pane of glass to support a decision support system via data unification. Here data collection and correlation needs to happen from both historic as well as real-time sources. This Decision Support System when applied in individual contexts will enable to implement "Contextual Analytics".
One of my area of interest is mathematical modeling & algorithms to solve complex real-life problems. Hence Smart Grid Analytics is one of my favorite subject.
I will write more on this topic in my future blogs to keep the discussion alive. This is my point of view about smart grid analytics and hence please provide your critical comments and suggestions on this blog.
For more information about what we at Infosys are doing in the area of Smart Grid Analytics please visit us at Distributech 2012 @ San Antonio, TX where will demo our Smart Grid Integration & Analytics Platform "Smart Integrator" and Contextual Analytics as part of Smart Customer Portal (Customer Service Operation Context) & DSM (Energy Efficiency Context).