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One of the smart grid’s key value propositions is that it allows the energy industry to move processes that were previously analog and manual toward a digital and automatic framework.
At the heart of the smart grid is automation, as it is the component that enables the technologies housed within the grid’s digitized network to automatically work together -- and ultimately, to help manage the country’s energy use around the clock.
While automation is one of the key cogs in the smart grid, the same is true for demand response. And when examining elements that underpin successful demand response programs, automation is at the top of the list.
Lately, there is growing commentary around behavior-based demand response. What needs to be kept in mind, though, is that while this may be an interesting approach, behavior alone does not guarantee response without certain vital technology. There is a clear distinction between a request and a response, and the real value of residential demand response is delivered by the speed and predictability of load reduction.
When utilities are working to evade blackouts or meet regulatory demands, this speed and predictability created by automation isn’t merely a luxury: it’s essential.
To understand how truly essential automation is, we need only look back at this summer and consider how demand response played a key role in maintaining grid reliability amid soaring temperatures. In July, heat waves swept across the country and temperatures rose to dangerously high levels, from New York to Missouri to California. During heat waves, increased strain is placed on the grid as individuals blast their air conditioners to combat the high temperatures. As a result, demand response is key in helping ensure that the grid is able to stay operational and blackouts don’t occur.
So why is automation critical to successful demand response programs? Because it provides a predictable, reliable resource for utilities.
Residential load control programs have always been automated, which is why they are such a valuable asset compared to commercial and industrial programs. When it comes to dynamic pricing, study after study shows that enabling technology drives significantly superior results for demand response programs. And the importance of automation to the future of residential, commercial and industrial demand response programs is being recognized throughout the industry. According to Pike Research, annual spending on automated demand response will balloon from $401 million globally in 2012 to more than $1.7 billion by 2018.
Earlier this year, New York Times columnist David Brooks examined the unpredictability of human behavior in an article that outlined the benefits and limitations of something that’s much in vogue right now: big data.
From dedicated sessions at the World Economic Forum in Davos to federal government research programs (and even its own Dilbert comic strip), big data has entered the mainstream and is now part of the discussion across a huge range of industries. In his article, Brooks made the argument that there is a subtle but significant logical leap made when analyzing big data to try to draw conclusions on how people will behave: the shift from correlation to causation. The crux of Brooks' argument was that people are dynamic beings prone to random shifts in behavior, and looking at behavioral patterns from a purely data-driven or statistical standpoint can only yield so much insight.
The same is true for the energy industry and smart grid. For the smart grid and the residential energy management sector in particular, big data offers great promise and has a very important role to play. The analysis of a range of data sets, such as home energy data, consumer behavior data, and smart meter data, among others, can help utilities influence how customers use energy and how automated demand response programs can be more rapidly and cost-effectively introduced.
In addition, big data can be used to optimize customer participation in innovative energy management programs such as dynamic pricing. Dynamic pricing enables utilities to give their customers multiple options for controlling energy costs, such as a fully automated critical peak pricing program. But the analysis of big data cannot be the sole driving force behind the success of demand response programs, as automation plays such a critical role in enacting load reduction.
For demand response programs to be as successful as possible and help maintain the reliability of the smart grid, there is a need for guaranteed action. Without guaranteed action, there is not a guaranteed result. This is the stark difference between “demand request” and “demand response.” When utilities are faced with the possibility of blackouts, brownouts or extremely high energy costs, the ability to take advantage of an automated system to reliably reduce load at the touch of a button is invaluable.
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Blake Young is CEO of Comverge, an intelligent energy management firm that enables utilities, grid operators, and commercial and industrial organizations to optimize their energy usage.