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Exploring Distributed Computing Capabilities for the Electric Grid of the Future

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Chaitanya Srinivaspura's picture
Sr. Manager - Utilities Vertical Brillio

Expertise in Defining Problem Statement and crafting Digital Solutions addressing key pain areas of Utility clients. Passionate about crafting persuasive solutions with underlying Digital...

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  • Jan 17, 2019 7:30 am GMT
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This item is part of the Special Issue - 2019-01 - Predictions & Trends, click here for more

Grid in Transition

The Electric Grid is undergoing profound changes and transitioning in to a more proactive data driven, information-based monitoring and management. Information and data are playing a significant role in the following areas

  • Balancing supply and demand
  • Voltage frequency control services
  • Energy back up
  • Seamless integration of DER in to the grid
  • Energy transfers and transactions – buying and selling

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Managing Unprecedented Flood of Data

Power grids are becoming richer with sensor data and communication systems at every touch point.  Soon we will have grids with vast communication networks, intelligent monitoring and sensing capabilities. Numerous sensors across the grid will throw up humongous amount of data and many of them will be continuous streaming data, such as data coming from a smart meter. It can be extremely challenging to manage this huge flood of data.

Even during the current transitory phase, Utilities are being challenged to have end to end awareness and visualization of their systems. To manage and draw inferences from the unprecedented influx of data, Utilities are heavily investing in to collecting, storing and analyzing data. Utilities are striving to use this rich data by incorporating meaningful analytics for better and informed management.

Key Questions to Answer

Most Utilities are looking to address the data storage, management and analytics aspects by adopting a centralized computing approach. They are heavily investing in to building data warehouses, bandwidth infrastructure to move ever-increasing data to a centralized location for further computation and analysis.  But is this the right approach? In this approach every bit of data need transmission, storage and processing of full data sets before analytics can show its magic. Some, of key things to comprehend, before investing in to infrastructure are

  • How much of the information / data collected is really acted upon, given the fact that investment in to collection of data and its further analysis pays off only if its actionable
  • Another more basic question is - do Utilities need all this data / information at every instance?
  • Is centralized computation and analysis of data the most optimized approach?

How convenient would it be if Utilities could get pre-computed pieces of information from the nodes of the grid as compared to raw bits of data? How effective will it be if Utilities were able to control this feed of actionable information as against getting continuous feed of raw data?

A small but a fundamental change can lead to a Paradigm Shift

The sensor technologies are maturing at a brisk pace. They are becoming not just smart but also intelligent, bringing with it the ability to respond to an external stimulus and interface with other computational infrastructure. This maturity may lead to the emergence Distributed Processing of Data within the Grid. Distributed processing allows to divide larger problem into smaller slices and having multiple networked computers process the slices, making it more effective and relevant. This approach will also build in toleration mechanism with in the computational infrastructure to overcome individual computational infrastructure failures.

This small but fundamental change could solve most of the problems of having a centralized computing approach. Distributed processing will allow pre-processed relevant information to be transmitted over the communication network making it more meaningful, relevant, timely and actionable. This can also solve the problem associated with choking bandwidth and heavy investment in to computational infrastructure.

This Concept is Not New

The approach to distributed computing and processing is not new. Its has been practically used across industries and many computational architectures are readily available around this concept. This approach is already being used by big data and internet-based technology organizations such as Twitter.

In Summary Benefits of Distributed Processing for the Electric Grid

  • Relevant and actionable information is transmitted
  • Allows greater control that may lead to streamlining of operations
  • Data can be easily managed
  • Allows opportunities to instill intelligence and analytical capability at specific nodes on the grid
  • Possible realization of cost efficiencies with desired level of performance
  • Minimize upfront heavy investment on high- end systems; Restrict Investment to a cluster of low- end computing systems
  • Distributed systems/processing may be easier to expand and manage as compared to a large monolithic centralized approach to computing

Bibliography:

  1. Research articles from EPRI.com
  2. Articles from Navigant Research
  3. Articles on Distributed Computing
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