Campaign: App/Services "Killer Ideas"

Green ROI

While I have been a renewable advocate for a very long time, a problem I have had is with Return-On-Investment (ROI) for a system. A few years back I attended a seminar presented by a potential solar system installer who admitted that if you take into account the cost of money, their systems would never pay for themselves. However, today things have changed.

 

In recent years the cost of solar systems have gone down, electric rates have gone up, and the cost of money (interest rates) are at historic lows. But how big should the system be and still pay for itself? How long will net metering be available? How can the cost of money be kept at a minimum? What incentives (tax or other) are available to lessen the ROI time? Here in southern California a solar photovoltaic system currently has a very favorable ROI (at least in the higher utility tiers), but what about Maine? What about other types of systems? While your local installer could try to answer these questions for you, he has a bias toward selling you a system. These questions and more can be answered without bias with the assistance of an app that could access the government datasets available.

 

The app would first want to establish where the project would be. With that information the app can use the multiple datasets available, such as the data set that creates the map seen at

 

http://www.nrel.gov/gis/images/eere_pv/national_photovoltaic_2012-01.jpg ,

 

to estimate the energy return rate for the various green energies (photovoltaic, solar heating, wind, etc.) at that location.

 

Next the app would need to establish the household energy use and the monthly costs for the energy. This could come initially from dataset estimates based on house size and energy rates from datasets for major utility rates. This can later be replaced by information from actual bills and supplemented from estimated future rate increase estimates based on historic data.

 

Combining this and estimates for system and installation cost, maintainance, lending costs, savings interest, incentives, etc. from other government and commercial datasets, the app will calculate and reporte estimates for return-on-investment time ( and profit) for each type of system.

 

As actual system/installation costs, interest rates and other considerations are determined, the ROI can be updated to ensure the project is on course or improved. If the results are also stored in part on the government system, then updates can be sent to the user automatically as changes in rates, incentives, etc. that might make a difference in the ROI for the user’s system.

 

An application of this nature will allow people to make informed decisions and find green systems will work in more places than expected.

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Idea No. 107