Friday 13 April 2018

Big Data in Demand Response

Big Data in Demand Response

As we continue to march forward to a decarbonised electricity network and distributed energy loads continue to grow - it's only logical to assume that more data is going to be captured, and more computational power will be required to make sense of it all.

Large-scale Utilities, TSOs, DNOs and Demand Response Aggregators are all looking for better transmission & distribution network controls; and end-users want smarter grids and energy-efficient buildings. Big Data companies like Intel see this as a new business opportunity - but one could justifiably argue that they're late-comers to the party. KiWi Power has been working with its NOVICE Project partners to do precisely that: explore the potential to combine energy efficiency and demand response flexibility through better analysis of building energy data. All of which will help in developing innovative business models in the energy industry.

Mike Bates, of Intel, in a recent interview, spoke about how Intel plans to embed computing at the edge of the grid that can forecast energy loads. Again, this is something KiWi Power has actively been engaged with for quite some time. By working with large I&C and DER (Distributed Energy Resource) clients, KiWi is able to aggregate capacity within specific geographic areas that can then be turned on or off remotely at times when it is required to help balance the grid.However, instead of calling this "Demand Response," Bates prefers the term: "Demand Flexibility." Nevertheless, whatever you call it - the end result is the same; and these initiatives are the key to enabling a low-cost, low-carbon electricity grid: whether it be from shifting major loads (i.e. comfort heating & cooling) or ramping-up DER assets (i.e. peaking plants, CHPs, etc).

One thing remains clear: Big Data will certainly have a role to play.

This is a promoted article. 

Written by

Bruna Pinhoni

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