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Published on February 12th, 2014 | by Guest Contributor

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Predictive Energy Optimization: Smart Buildings, Smart Grids, Smart Cities

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February 12th, 2014 by
 

By Alberto Fonts, Product Manager, BuildingIQ

PredictiveEnergyOptimization_graphA weather system just passed by the wind farms out in the eastern hills, the turbines have been cranking all night. Not finding much demand, energy prices in the morning have plummeted. Alas, the bonanza won’t last long, as the change in weather means the wind energy production is going to taper down in the afternoon; the warmer temperatures will result in skyrocketing demand later in the day. The utility, reluctant to bring all of its peaking plants online, will declare it a peak pricing day, catching many building managers unprepared.

Building managers and property owners dread days like this. A few years ago, no one would have noticed a small ‘blip’ on the power bills. Today it is different: budgets have been tightened. Adding insult to injury, environmentally conscious tenants are asking about LEED certification, and the ever-raising bar of Energy Star ratings mean that buildings must reduce energy use to stay valuable. If only one had the time to monitor the BMS on days like this, or the budget to get some hours from the local controls contractor. Never mind the fact that the only engineer who understands the pneumatics that are still used across the portfolio is about to retire.

Take a step back and imagine now that your building could be aware of what is about to happen on the eastern hills. Imagine that, with no prompting or programming, it knew to be more aggressive during the overnight purge; the fans and maybe part of the plant would work harder thanks to the cheaper energy – yes, you could be participating in the whole sale market when it suited you. This way, when the prices increased later in the day, you could comfortably coast right under your peak pricing day baseline – it is nice to finally get those credits!

Imagine your building knew that on Fridays it is OK to re-set the duct static pressure a bit earlier than the rest of the days because most tenants are out by 4pm. Maybe it also knows that a gradual decrease in the discharge air temperature is the way to avoid a morning spike on some days, but not others. Perhaps it also knows how to curtail usage in the plant and fans on one of those dreadful peak demand days. Needless to say, your tenants would never notice.

Now take an even bigger step back to the grid level. Imagine your building could automatically communicate with the utility company to become more responsive to the grid. During demand response events, your building automatically curtails non-critical building loads or turns on back-up energy sources. Through automated demand response and predictive controls, your building energy consumption is continuously adjusted to reduce demand at critical times of the day in response to hourly pricing signals from the grid. For this, you receive compensation from the utility provider. So all of a sudden your building is not only using less energy and decreasing your energy bill, but it is actually making money for you. Imagine that.

If your building is in Las Vegas, you’re in luck. NV energy is one of the first utility providers to integrate predictive energy optimization. In 2013, the Las Vegas’ utility provider launched a new energy management program, called mPowered, which is helping its largest customers — including Las Vegas’ famous casinos and resorts — become smart buildings.

By leveraging cloud-based energy management software, NV Energy is able to directly communicate and exchange data with its customers in order to increase energy efficiency and reliability of the city’s power grid. The program saves energy at the source and allows the utility to act as the brain, sending signals to the buildings and making real-time adjustments to energy consumption.

Now lets look at the city level. One prominent customer of the mPowered program is the City of Las Vegas itself, which today is using energy management software in all of the city’s government buildings, including its award-winning, LEED Gold city hall. With this program in place, the City of Las Vegas is seeing measurable energy and peak load savings. Thanks to the use of data analytics, the City of Las Vegas is now educated and aware of it energy consumption as it continues on the path towards becoming a Smart City.

Las Vegas is an example of what the future world of Smart Cities will look like — fully connected infrastructures that utilize big data, analytics, cloud-based predictive energy optimization technology to proactively manage our most valuable resources, protecting our earth and creating a healthy environment for future generations.

And Las Vegas is just an example of what is possible for your building, your grid, your city. It doesn’t require expensive BMS upgrades or hundreds of consulting and contractor hours. All you need is an Internet connection.

Imagine a web-based SaaS product that automatically and continuously obtains data on the local weather forecast, the occupancy for the building, energy prices, tariffs and demand response signals. Based on those inputs, the software runs thousands of simulations to arrive at the most efficient HVAC operating strategy for the next 24 hours. It then communicates to the BMS to make changes at the air handle units (AHUs). Small changes at the AHUs result in large financial savings without impacting occupant comfort.

The software works with a BMS to automatically fine tune temperature and pressure set points. Changes are made at the air handler unit AHU level. Typically, the software only needs to communicate with a few points per AHU, so the cost and complexity of deploying the solution is minimal.

At the core of this energy management solution are advanced artificial intelligence algorithms, which automatically learn and model the building’s thermal characteristics and usage patterns. There is no need for engineers to laboriously document or update the technical details of every component of a building’s HVAC system, or make adjustments once information is gathered.

You no longer have to imagine. The technology is available today.

Welcome to the world of truly smart buildings, smart grids and smart cities. Welcome to the world of predictive energy optimization.

About the Author: Alberto Fonts is a product manager with BuildingIQ, the provider of an advanced energy management software that uses a cloud-based energy optimization technology to actively predict and manage HVAC loads in commercial buildings. He is based in Foster City, CA.

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  • mike_dyke

    I’d like to see the time where, during the cheap period, I fill a lot of batteries. I then use most of that stored power during the day. When we get to the next cheap period – fill the batteries back up again. Repeat for each day.

    I’m not sure this is currently possible on a business scale due to the amount of batteries required – Yet.

    • Matt

      For Las Vega and other hot location. The better approach would be to “store cold” at night, then use it during the day. This has been around for decades. AS batteries become cheaper then you couple also store power and use it to run your lights/motors to cut peak more. But since biggest load is AC and cold is easier/cheaper to store that electrons today, that is the fastest way to get there.

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