Put sunshine in your pocket

Put sunshine in your pocket

UD grad students empower homeowners with smart data

By Kevin J. Gray

What if your utility company could tell you about your energy usage in as much detail as you get from your cell phone company? How could this change your life?

This was the challenge that University of Dayton graduate students Mithun Mohan Nagabhairava, a software developer in UD’s renewable and clean energy program, and Dustin Pohlman, a mechanical engineer, answered earlier this year. The U.S. Department of Energy, through a challenge called “Apps for Energy,” asked programmers and engineers to look at ways that more detailed energy usage data could help residential and commercial building owners.

In response, Nagabhairava and Pohlman developed a computer program that allows homeowners with solar photovoltaic (solar PV) cells and batteries to maximize the economic benefits of their systems. Sounds complicated, but it really isn’t that hard to understand. You just need to know a few key details.

First, the Energy Department challenge references data from smart meters, high-tech energy meters in use in California and Texas. Residents with smart meters can receive energy usage data broken down by the hour. The advantage to this approach? Homeowners are able to see not just the total amount of energy used over a given month (which is the way bills in Ohio are calculated), but also see periods of peak usage.

For instance, in a given household, early evening might be the time of highest usage. Why? Everyone is home from work and school. Someone is cooking dinner, while the kids are on laptops or watching television. The thermostat, bumped down during the day when the house is empty, kicks on to heat the house. A smart meter reading would likely show this period as the highest energy usage.

Second, what many homeowners don’t know is that the usage rate, or tariff, on a utility bill is often an aggregate rate. Actual tariffs vary depending upon the times of usage. Tariffs during peak times are often higher than those of non-peak hours. The more energy being drawn from the grid, the more the power company has to produce. Additional production means ramping up equipment and labor hours. The cost is passed onto the consumer in terms of higher tariffs. Remember when folks would wait until after 10 p.m. to make a long distance call because the daytime rates were so high? Same case here –throughout the day, the actual cost of electricity fluctuates, with some hours being more expensive and some being less.

Finally, homes with solar PV cells can be configured in one of two ways. Most commonly, solar panels pump energy that isn’t used in the house back into the grid. When the solar PV cells are producing energy, that energy flows into the grid, and the homeowner can actually watch his or her electric meter run backwards. At night, when the solar PV cells are dormant, the meter draws from the grid. Most solar users with this type of configuration compensate by producing more electricity than they draw from the system, thereby creating a new balance in their favor. Yet a unit of energy sold back to the power company is often worth less than a unit bought (because the homeowner is credited for generation charges when selling, but is debited generation and transmission charges when buying).

However, some solar PV users combine their system with a battery. The solar PVs can either charge the battery or dump power into the grid. If the battery is charged, power can be drawn from it during times of high energy usage (and high tariffs), even if those are during times when the PV cells are dormant, like for instance, in the early evening hours.

Simple concepts, but a lot of data to manage. Nagabhairava and Pohlman’s software program makes it easier for homeowners to triangulate all of this information. Their program calculates the hourly usage in a household, the tariff information from the power company and the capacity of a home’s solar PV cells and battery. The results of this data are a sophisticated cost-benefits analysis customized to a specific home.

Using the UD grad students’ program, a household could, for instance, decide to use the solar PV energy produced during the day to charge a battery. The household could draw from the battery at the times when energy is the most expensive and draw from the grid during low cost energy times. Homeowners are able to more quickly recoup the cost of their solar PV/battery systems by making the most informed economic choices. Or households could make more effective purchasing decisions when buying their solar PV/battery system initially.

Pretty cool, huh? The Energy Department thought so, and awarded the duo a $4,000 prize. Their application came in second in the “Popular choice” category. As a result, Nagabhairava and Pohlman recently flew out to DC, where they received their award in a White House ceremony and got to meet with other prizewinners and companies working with the same energy data.

What’s next for these two? Nagabhairava is continuing to develop the software, adding more sophisticated algorithms and a user interface. He is also looking at other potential extensions to the software. The next phase of the project will be his Master’s thesis. Pohlman is working on energy conservation and recently won an award for a proposal titled “Energy Efficient Humidity Control in Manufacturing,” which deals with more effective air conditioning systems. He will be following that proposal through as part of his graduate work.

Although smart meters and solar PV systems aren’t prevalent in Ohio (yet), it’s great to see solid work on green energy and energy conservation here in the Miami Valley.

Reach DCP freelance writer Kevin Gray at KevinGray@daytoncitypaper.com

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