Thursday, February 7, 2013

Solar Metrics & the need to know where to look.

If you can't measure it, you can't know if you're succeeding or failing.  If you can't analyze it, you don't even know what you don't know. 

As I've talked and tweeted about in the past, I've become a solar energy fan, installing a grid-tied solar system on my roof.  This means when it's sunny out, my solar panels change energy from light to electricity.  It's measured instantaneously in watts or kilowatts (kW), and measured over time, it's in kilowatts/hour (kWh).   Obviously, solar power is only created during the daylight.  Because it will vary based on the amount of sun for obvious reasons like season, number of hours, strength, and amount of clouds, good monitoring is essential. The graph below is actual production data from my solar energy system:



 It is pretty obvious, that some days are good solar days (September 11-17) and some are not (September 28-30; heavy clouds and rain.)  What's most important for me as an owner, is being able to see what I'm generating, and know if I'm above or below my solar energy plan.  Metrics are good like that.

However, metrics are just the first part.  I don't have any tools to understand the actual data.  I may remember that the end of September was cloudy and rainy, but I don't remember the weather on September 4th.  I really need  analytics too.

Wikipedia says:
Analytics is the discovery and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statisticscomputer programming and operations research to quantify performance. Analytics often favors data visualization to communicate insight.  (http://en.wikipedia.org/wiki/Analytics) 
I look at it more simply:  analytics tells me what the data means.  How to interpret it. What's truly related.  Where to look for problems.  For example, there is publicly available weather data that states how much of each day was actually sunny, cloudy, raining, etc.  I need something that can look at the expected "normal", and compare that with MY actual experience.  Have trees grown to cover my solar panels?  Did a wire come loose and disable a panel?  Did a circuit breaker trip?  I can dig into these things if I know to look for them. It's about gaining insight.

Of course, analytics don't just apply to my solar system.  It helps provide insights into things that aren't as obviously related.  Without analytics, nobody would know that when it rains, the sale of cake goes up.  When it's sunny, people buy more paninis.  (See IBM Analytics at http://youtu.be/HbHTvqZE3D8 and http://www.ibm.com/analytics/us/en/).  I'm always amazed by the things that don't seem to be associated, but are.

Meanwhile, my little solar PV system keeps cranking away, generating more power almost every day.  I'm gathering the data.  Someday I'll  sit down and have the analytical tools to understand it.  Maybe I can get someone at IBM to help.





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