Archive for April, 2012

Cruise control for the home

Drivers and pilots make use of technologies that make their life easier and increase energy savings, why not home owners?

I’ve been thinking a bit lately about the future of energy monitoring and intelligent control systems. We recently installed an energy monitoring system from Powerhouse Dynamics. It is very good at telling us how much energy we’re using for which circuits, and advice about how we can use the appliances on those circuits more efficiently. Although we don’t own one*, Nest has been in the news a lot lately for their intelligent use of occupant behavior history and weather predictions to actively optimize your heating/cooling equipment, and for telling you how much you saved by using their product.

I’m imagining an energy monitor that tracks our energy usage for major appliances and through a combination of active control or user suggestion determines the ideal time to use those appliance to 1) optimize their effectiveness, 2) increase our enjoyment of said appliances and 3) lower our energy usage.

Example 1. Water heater. Nest says the thermostat controls 50% of your home energy usage. For us it’s the water heater because our heating and cooling requirements are so low. Now that Martin Holladay has determined that tankless water heaters are a waste of money, we should be able to make tank style heaters more efficient. Let’s say our monitor knows generally when and how much we tend to use hot water. Similar to the calculations required to heat and cool the house, it could determine the optimal water temperature between 120 or 140 degrees F and when the heat is required. For us, it is mainly needed in the morning when we take showers and a bit in the evening when we do a bit of hand washing of pots and pans that don’t fit in the dish washer. No need to stay at 120 or 140 degrees F 24/7/365.

Example 2. Clothes washer and dryer. Let’s say our monitor energy tracks how often we wash clothes and dry them. Let’s say it understands some correlation between season, outdoor temperature and humidity. It might suggest after a few months of usage and weather data that if we wash our clothes this Sunday rather than Saturday then we can dry them on the drying line versus having to use the dryer because there is a higher chance of rain on Saturday. Or maybe it knows we don’t have a drying line but we have a solar array that can supply the required energy without going to the grid. It could predict the energy savings if we follow the monitor’s advice.

Where to control these appliances? At the circuit box or at the device? Circuit level control seems crude. It seems like it would make more sense to have more intelligent devices, each knowing what factors affect it’s efficiency. But then you end up with lots of appliances with redundant functionality. Plus, you may be missing out on efficiencies across appliances.

Consider if we decide to wash and dry our clothes in the winter when the sun is shining and powering our solar PV system while adding passive heat via our high solar gain windows that face south? Maybe we can lower the set point on the heating thermostat so that we don’t overheat. Or maybe we use the condensing dryer to heat the house instead of the air-source heat pump.

This is one of the scenarios that makes me think that someone is working on a Nest-like appliance for the entire home. It will monitor not only energy and hot water usage, but also every generation, occupant behavior and weather predictions to put the house on auto pilot, or suggestion or cruise control mode. Occupants can override this mode manually whenever required and then compare at the end of each month to see who did better, them or the algorithm. Who knows, maybe the user gets a credit on the system if they out perform the algorithm more than 3 consecutive months.

None of these ideas are new, and I’m guessing most are already being used in large scale commercial operations. But I think the Nest shows us that the future is closer than we think for home owners. We don’t need a lot of intelligent appliances, or a lot of intelligent appliances talking to each other. We don’t even need automated controls, but a simple auto pilot for the home can maximize the efficiency of home appliances and the happiness of the home owner.

* Note to Nest. We don’t currently own a Nest thermostat because our heating and cooling loads are so low, but we would gladly own one if it could use similar logic to control our water heater.

March performance

Actual vs. Projected for 2012

March madness, the weather that is. March was freakishly warm and much sunnier than February (33% less heating degree days, 31% more sun). This partially resulted in 23% lower energy usage in March. Our daily average usage was down 28% from February. We generated a 345 kWh surplus in March, the first since we moved in Jan 1st.

All values in kWh (except HDD) Jan 20121 Feb 20122 Mar 20126 Apr 2012
Solar PV generation 369 597 860
Usage 873 666 515
Net usage or (generation) 504 69 (345)
Average daily usage 28 23 17
HDD (base temp 68F)3 1,2124 1,0455 7045

1 January values based on meter reads.
2 February values based on TED data.
3 Heating Degree Days (a measure of how many outside degrees in a day it is below a target inside temperature)
4 Downloaded from, Station ID: KALB (Albany International Airport).
5 Calculated from my HOBO outdoor weather monitor hourly data.
6 March values based on meter reads. (TED died March 1st, eMonitor installed March 16)

The chart at the top of the page illustrates our actual performance for the first three months of the year, and our projected performance for the rest of the year based on estimated output of our array and historical heating degree days for the last 10 years. The usage numbers are a complete guestimate, but based on these numbers we could be net positive at the end of the year by 242 kWh. In any case, it will be interesting to track actual values against the projected values.

We’re also happy to report the TED folks accepted our return last month without incident and we’re enjoying our new eMonitor circuit level monitoring. Although we don’t have a full month of data for March, we are able to share the 15 days of data we did collect. It is available at You can now view solar, usage, net usage, temperatures and HDD for all of February and circuit-level data for 15 days in March. We’ve included a few snapshots below.

Heatmap composite including all options

The composite image shows all the high-level data heat maps. You can see very easily that the third week was warmest and sunniest days of the month that we collected data.

Air source heat pump mapping and day chart

The above snapshot shows March 16, the first day we started collecting circuit-level data. It wasn’t a particularly cold day, temps were in the mis 40’s, but there was very little sun as evidenced by the relatively flat solar curve. This required the heat pump to kick in enough to make it the most active out of the recorded days. This is a bit misleading because if you compare March to February, power use that day was quite low. Now that we have multi-month data, we’ll have to find a better way to compare across months.

If you have any questions or spot any math errors drop us a note in the comments.

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