Category Archives: Solar PV

Smartening up

We will shortly have been in this house for six years. During that time I have created three smart control systems that improve my energy costs or efficiency:

heating controls to minimise gas purchase
self-consumption controls of the electricity generated by my solar panels to maximise value of self-consumption
smart tariff controls to buy grid electricity at the lowest price

Heating Controls

Most homes have a single heating zone with one timer and potentially one thermostat controlling the whole house with perhaps some thermostatic radiator valves (TRVs) capping the temperature in specific rooms.

By contrast we have seven heating zones created by electronic temperature control valves (eTRVs). Each zone has its own timer. There is no central timer or thermostat. Each eTRV can summon the boiler on when cold rather than simply cap the maximum temperature like a TRV.

Some rooms also have links to other smart devices such as disabling room heating when the window is open or turning off heating early when there’s no movement in the room.

The intent is to save energy by only heating rooms that are in use.

Self-consumption Controls

These controls manage the diversion of any excess output from my solar panels rather than give that energy to the grid. The loads are prioritised as follows:

Powervault storage battery (fully proportional)
Car charger (stepped proportional driven by ImmerSUN relay output)
Hot water (driven by ImmerSUN fully proportional output)

Last year these controls helped me to use over 90% of the output of my solar panels avoiding buying £100s of electricity and gas. The priorities are set to maximise value – #1 avoid daytime electricity use at 16 p/kWh, #2 avoid car charging at 5-16 p/kWh, and #3 avoid gas consumption at 2.96 p/kWh.

Smart Tariff Controls

These controls manage my electric devices for lowest grid energy cost. The controlled devices are:

Battery storage (Powervault)
Dishwasher
Electric car charger
Hot water heating (ImmerSUN)
Washing machine

The hardware that has this control is known as a Home Energy Management System (HEMS). My HEMS is based on a simple computer known as a Raspberry Pi. The HEMS uses foreknowledge of the electricity price and predicted solar panel output to determine when best to run the above devices. It was designed around a tariff called Octopus Agile which has 48 half-hourly prices that change daily, but is currently working with a simpler two-rate smart tariff.

device	Central Heating	self-consumption	smart tariff
Battery Storage		#1	X
Central Heating Boiler	X
Dishwasher			X
Electric car charger		#2	X
Hot water heating		#3	X
Washing machine			X

Devices controlled by smart systems

Most of these solutions are made up of commercially-available items that I have perhaps combined in a way not anticipated by their manufacturers. In particular:

I created a relay module to enable the gas boiler to be turned on remotely and programmed a series of logical rules for the Apple TV’s that act as the controllers.
I identified a way to prioritise different self-consumption devices by configuring their current clamps.
I built my smart car charger integrating various items of hardware and writing the ladder logic program that runs it.
I built the HEMS from commercially-available parts and wrote the software that runs on it to control my devices.

Payback time

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It been over a year now since I last reviewed what return I was getting on my investment in energy smart technology – solar panels, battery storage etc – so I think an update is due. This time I’m going to take the input data from my immersun system – one year of data from start of June 2020 to end of May 2021.

Diverted – this is where the immersun sends any surplus solar electricity to my immersion heater to make hot water. In 2020/1 we diverted 1056.6 kWh to hot water saving gas at 2.82 p/kWh. However the gas boiler isn’t 100% efficient losing heat both via the flue to the outside world and also via the hot water pipes to the home rather than hot water. If we assume 80% efficiency at the tank then 2.82 p/kWh as gas at the boiler is 4 p/kWh as heat in the tank. 1056.6 kWh at 4 p/kWh saved £37.25.

Exported – this is where I’m unable to use the solar power that we generate and it overflows into the grid. I’m not paid for Export so this is worth nothing to me.

Generation – this is the energy that we generate in the solar panels. I’m on the UK’s legacy Feed-in Tariff (FiT) scheme which pays me to generate electricity. In 2020/1 I was paid 14.65 explicitly for every kWh that I generated. I also received deemed (rather than metered) Export which paid 5.5 p/kWh on 50% of the kWh that I generated (which is where the ‘deemed’ part comes from). 5.5 p/kWh on 50% is equivalent to 2.75 p/kWh on 100% of the Generation making my revenue 17.4 p/kWh per kWh generated or £693.51 on the 3985.7 kWh that I actually generated.

Imported and House – these are respectively the electricity that I buy from the grid and that which I used within the home including appliances and car charging, some of which will comes from my own solar panels. The difference between House and Imported is the electricity that I used from my solar panels which would otherwise have been bought from the grid. If I assume that each kWh that I use from my solar panels avoids buying a kWh of electricity from the grid at 16.36 p/kWh (current Energy Saving Trust value for the average UK electricity price) then I avoided buying £423.81 of electricity by using the output of my solar panels.

Diverted	1056.5 kWh	*	£0.04	=	£37.25
Exported	338.6 kWh	*	£0.00	=	£0.00
Generated	3985.6 kWh	*	£0.17	=	£693.51
Imported	4748.9 kWh	*	-£0.16	=	-£776.92
House	7339.4 kWh	*	£0.16	=	£1,200.73
Total					£1,154.56

Return on smart energy investment @ 16.36 p/kWh grid price

With an investment of £8,670, £1,154 represents 7.5 years to pay back the capital invested.

I’m actually on a smart tariff so my electricity cost in this period at 8.05 p/kWh was significantly less than the UK’s average 16.36 p/kWh. This lower price will arguably reduce the value of the energy generated by the solar panels for self-consumption, but equally the ability to maximize the value of a smart tariff is itself a saving.

Diverted	1056.5 kWh	*	£0.04	=	£37.25
Exported	338.6 kWh	*	£0.00	=	£0.00
Generated	3985.6 kWh	*	£0.17	=	£693.51
Imported	4748.9 kWh	*	-£0.08	=	-£382.29
House	7339.4 kWh	*	£0.08	=	£590.82
Total					£939.29

Return on smart energy investment @ 8.05 p/kWh grid price (excluding the tariff benefit itself)

Using my actual average energy price rather than the higher UK average grid price pushes down the return by over £200 (£929.29 versus £1,154.56). However the costs of buying the imported 4,748.9 kWh falls by £394.63 through the tariff benefit, increasing the annual return to £1,333.93, and reducing the payback period from 7.5 to 6.5 years.

Thus, had I invested in this technology at one time back five and a half years ago and shortly after we moved to this house, then we’d have been in sight of payback with 1 or 2 years left. In practice of course I’ve made the investments at different times (solar first five and half years ago, battery around a year later, smart tariff later still), so my payback will be achieved a little later.

A snapshot of the ImmerSUN diverting to hot water

Some other statistics:

Of solar panel output:
- 91.5% replaced bought energy (self-consumption)
- 65.0% replaced bought electricity
- 26.5% replaced bought gas for water heating
- 8.5% was exported to the grid
Of incoming electricity:
- 54.4% was from the grid
- 45.6% was from the solar panels (“green contribution” in ImmerSUN’s terminology)

Thoughts on intensity (of the CO2 variety)

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CO2 production is increasingly of interest as the world struggles to limit man-made climate change. As we use different energy sources each represents a certainly amount of CO2 reflecting a combination of the energy invested to create that power source (e.g. the wind turbine may generate wholly renewable power, but its construction created some CO2) and the CO2 created as it generates energy once constructed (nothing for renewables but relatively high for fossil-fuelled generation).

I’ve previously shared this table showing the IPCC’s view of the embedded CO2 in different sources of electricity generation.

IPCC’s view of embedded CO2 in different sources of electricity generation

A recent question and resulting discussion in an on-line forum prompted me to think more about the area of embedded CO2.

My first observation would be that my rooftop solar panels do quite well on this scale with a CO2 figure of 41 gCO2/kWh.

The second observation would be regarding energy storage. My view would be that any energy storage device from a small scale domestic battery like my own to a large pump storage scheme can never deliver better embedded CO2 that the source of its energy. So, for example, if I charge my battery from my own solar at 41 gCO2/kWh with a cycle efficiency of 80% (the maker’s claim) then the embedded CO2 in the energy coming out of the battery cannot be better than 41 gCO2/kWh / 80% = 51 gCO2/kWh. Indeed it would be worse than that as this doesn’t account for the CO2 generated in creating the battery nor its operational life, but I don’t have figures for those.

Thirdly, as my own embedded CO2 is relatively low whether exported directly from my panels or indirectly via the storage battery, then the CO2 intensity of the grid always benefits from my export. The 116 gCO2/kWh illustrated above is pretty low for the UK grid which varies widely but is still more than my solar PV directly or stored solar PV. Indeed had I exported onto the grid at the time illustrated above then my 41 gCO2/kWh versus the grid’s 116 gCO2/kWh would have saved 75 gCO2 for each kWh that I exported.

However if, for example, I export electricity but need to then buy more gas to make hot water then that too has a CO2 impact.

CO2 intensity of different fossil fuels (source: Volker Quaschning)

If I need to buy a kWh of gas to make hot water that’s 0.2 kgCO2/kWh or 200 gCO2/kWh even before I’ve accounted for the relative inefficiency of the gas boiler versus my electric immersion heater. If I assume that the gas boiler is 90% efficient then I will be responsible for 200 gCO2/kWh / 90% = 222 gCO2/kWh for a kWh used to make hot water. Thus, while exporting 1 kWh of solar PV may save the electricity grid 75 gCO2/kWh, it’s added 222 gCO2/kWh to gas consumption – a net deterioration of 147 gCO2/kWh.

Natural gas of course is the lowest CO2 of the fossil fuels listed above – if your home is heated by oil, coal or wood then the analysis is further skewed towards using your own self-generated power rather than exporting electricity and importing another fuel for heating.

The electricity grid’s carbon intensity also varies. In 2019 the UK average was 256 gCO2/kWh (a little higher than my estimate for gas) however this varies considerably through the year with the highest embedded CO2 in early winter evenings when I have little if any solar PV to contribute to the grid, and may well be lowest when I and others have surplus solar PV. My understanding is that the lowest grid CO2 occurs with a combination of high renewables (such as particularly windy weather) coupled with low demand (such as summer nights).

Thus my own strategy is to:

Maximise self-consumption of my own solar PV as my energy source with the lowest embedded CO2 (except in the event of an extreme plunge pricing event when the grid is under highest stress)
Make best use of storage to minimise consumption from the grid in the evening peaks when embedded CO2 is likely to be highest.
When a solar-shortfall is anticipated then buy electricity selectively from the grid at lowest CO2 (using Agile electricity price as a surrogate for CO2).

Monitoring the HEMS

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For some time now I’ve been thinking about creating a real time display which pulls together data from a variety of sources around the home to provide an overview of what’s going on without the need to visit multiple web pages or apps. Until the last 10 days or so that involved little more than thoughts of how I might evolve the existing immersun web page with more content (I don’t have the skills to write my own app), but then about 10 days ago I saw an online gauge that someone else had created to show energy price and inspiration struck. Ten days later I have my monitor working, albeit not complete:

The monitor pulls together information from:

My electricity tariff for p/kWh
My immersun for power data (to/from: grid, solar, water, house)
My storage battery for power in/out and state of charge
My HEMS for electricity cost thresholds between different battery modes.

The gauge consists of two parts: (i) an upper electricity cost part and (ii) a lower power part.

The upper electricity cost part is effectively a big price gauge from 0 p/kWh to 25 p/kWh with a needle that moves each half hour as the price changes. It has various features:

The outer semi-circular ring (blue here) shows today’s relationship between battery mode and electricity price. Today is very sunny, so no electricity was bought from the grid to charge the battery, and this part is all blue for normal battery operation. If the days was duller and electricity was to be bought to charge the battery, then two further sectors would appear:
1. a dark green sector from zero upwards showing the grid prices at which the battery would be force charged from the grid, and
2. a light green sector showing when the battery is not permitted to discharge but may continue to charge from solar.
In inner semi-circular ring (green / yellow / red here) currently just colour-codes increasing electricity price, but will be used to show today’s prices at which car charging and water heating are triggered from the grid.
The current price per kWh is taken from Octopus’s price API, while the current cost per hour is derived both from this and the grid power from the immersun.
The needle grows from a simple dot indicating the price per kWh only when no power is drawn from the grid to a full needle when the electricity cost is 10 pence per hour or more.

The lower power part is effectively a power meter ranging from 5,000 Watts of export to the left to 5,000 Watts of import to the right. It updates every few seconds. It has various features:

The outer semi-circular ring (orange /maroon / green here) shows how power is being consumed:
- orange – shows consumption by the house less specified loads
- maroon – shows battery charging
- blue (not shown) – shows water heating
- green – shows export to the grid
The inner semi-circular ring (yellow here) shows the source of power. The sum of the sources should equal the sum of the consumers. The sources are:
- maroon (not shown) – shows battery discharge
- yellow – shows solar power
- red (not shown) – shows grid power
The power value shows the net import or export from / to the grid, while SoC refers to the state of charge of the battery (0-100%). The combination of import power and electricity price gives the cost per hour in the top gauge.
The needle position shows net import (to the right) or next export (to the left). The needle should thus be to the left of the green sector, or to the right of the (unseen) red sector. Needle length show the full power being handled and is thus proportionate to the angle of the sector including all the colours in the lower gauge and extends from 0 to 5 kW.

Monitor installed on an old phone in the kitchen.

The gauge scales to fill the smallest of screen height or width and translates to be centrally positioned regardless of screen size. My intention is to display it on an old mobile phone as an energy monitor, but I can also access it on any web browser on any device within the home.

Saving on electricity

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I’ve been seeing a few online advertisements recently touting 70% savings on electricity through a combination of solar panels and battery storage. I’ve also been looking for a way to express my savings through my smart tariff so this seemed like a opportunity to try that.

My start point is a years data from my monitoring system..

Monitoring data for March 2019 to February 2020

I also went through a year of electricity bills (with slightly different start and end dates) concluding that my average purchased electricity cost was 7.08 p/kWh. Thus my average electricity costs (including solar) are on the right of the table below:

source	quantity	est unit price	Est total	my uniT price	mY total	my saving v. Est
Bought	4,309 kWh	15.75 p/kWh	£678.67	7.08 p/kWh	£305.08	£373.59
Generated	2,473 kWh	15.75 pkWh	£389.50	0.00 p/kWh	£0.00	£389.50
Total / Average	6,783 kWh	15.75 p/kWh	£1,068.32	4.5 p/kWh	£305.23	£763.09

Comparison between my electricity cost and the UK average

If I look at the Energy Saving Trust’s assumptions as a baseline, they have the average UK cost of electricity as 15.75 p/kWh. If I’m paying an average 4.5 p/kWh for each kWh used with my combination of solar PV, storage battery and smart tariff then I’m paying 28.6% of the cost of someone who used the same amount of electricity bought at the average UK rate or saving 71.4% of electricity cost. To put it another way, I’m paying £305.23 for electricity that would have cost the average UK consumer £1,068.32 (on the left of the table above) – a saving of £763.09.

(The baseline assumption that someone would have used the same amount of electricity as me without my level of technology is a slight over-estimate as I flex water heating between gas and electricity since my bought electricity price is sometimes lower than my bought gas price causing me to substitute electricity for gas. Someone on a conventional electricity tariff and gas would never make that substitution as their gas would always be cheaper than their electricity, hence my electricity consumption is a little higher than someone who would be on a conventional electricity tariff.)

I’m also generating feed-in tariff due to the age of my system (approximately 4.5 years old) which would be £714.59 per annum at current rates, and making 1,075 kWh of hot water from surplus solar electricity which saves £38.22 in gas (the diverted / hot water saving in the screenshot above is based on a notional electricity price, not a gas price). Unless I’ve missed something that’s an annual return of £1,515.90 (£763.09 + £714.59 + £38.22).

In my previous post I estimated my investment at £8,670 so with an combined annual savings and revenue of £1,515.90 that’s a 17.5% return or a payback of 5.7 years. Previously I’d estimated 9 years including the battery, but this was without the benefit of the smart tariff. As we’ve now had the solar PV for 4.5 years that’s very promising, although as my return seems to be accelerating it will take more than 4.5 past years + 1.2 future years (total 5.7 years) to achieve payback.

The current 5.7 years to payback would have achieved payback in spring 2021 as the near bookend, while the prior 9 years would have been autumn 2024 as the far bookend. In practice I could not have achieved the lower bookend of 5.7 years, even had I invested in all the supporting technologies simultaneously, because I’m combining the legacy Feed-in Tariff (FiT) scheme for my solar PV with the Octopus Agile dynamic smart electricity tariff which started in February 2018,

How green was my xxxxxx solar?

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One question that gets asked periodically is how green are technologies like solar panels given that there much be some emissions created in their manufacture and ultimate disposal.

Lifetime gCO2/ kWh for various generation sources

It’s probably no surprise that the rooftop solar PV is considerably less carbon-intensive than any fossil fuel (1/20th of coal for example) but that it beats biomass or even utility scale solar (I.e. solar farms) may be a surprise. My understanding is that the recent switch of emphasis in the UK from rooftop solar (with elimination of FiTs) to solar farms is driven more by investment costs than ultimate carbon-intensity.

Source: Intergovernmental Panel on Climate Change (IPCC) as quoted by Spirit Energy

The Big Picture

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After a series of quite detailed posts, I think that the time has come for an updated high level overview of what we have.

We moved to our early 1970s house almost 4 years ago bringing with us our electric vehicle. The house had already been refurbished with new double-glazed windows, had cavity insulation (although that wasn’t recorded on EPC so must have predated the prior owners), and a token level of loft insulation. The existing gas boiler was arthritic, couldn’t heat the whole house, but was quite good at heating the header tanks in the loft! We had gravity-fed gas hot water (i.e. no thermostat or pump on the cylinder) which was completely obsolete, the cylinder dated back to the building of the house and had no immersion heater (although we had the wiring for one). So what did we do?

Space heating:

We substantially increased the loft insulation to reduce heat loss.
We had a modern condensing gas boiler installed to improve efficiency.
We updated to smart controls using eTRVs to set both temperature set points and schedules at room level. I built a smart interface to the boiler so that heating can be enabled remotely. I programmed a series of rules into Apple Home allowing the smart thermostats to enable the boiler when any thermostat wants heat and disable it when no thermostat wants heat. Some rooms also have additional rules linking heating to open windows or movement sensors. All of this reduces heat losses by only heating rooms that are (or will be shortly be) in use.

Electricity supply:

We installed our own solar panels given 4 kWp generation. (I also own a small share of a solar farm although there’s no contract that I’m aware of between that farm and my home energy supplier)
I invested in an immerSUN to maximise self-use of our own solar by enabling loads when surplus solar is available.
We switched to a green electricity supplier so when we need to buy electricity it comes from renewable sources.
We bought a small storage battery 4 kWh to store some of our solar production for use later in the day. Subsequently I can also use it in winter to buy when the electricity price is relatively low to avoid buying when the price is relatively high.
We chose a dynamic smart tariff to buy electricity at the lowest price based on market prices established the day before. The prices change each half hour and are established in the late afternoon on the day before.

Water heating:

We replaced the old hot water cylinder with a modern insulated one (to reduce heat loss) with a low immersion heater (to allow more of the water volume to be heated).
Our principal water heating is now by diverting surplus solar electricity proportionately to the immersion heater, that’s backed up by the gas boiler which is enabled briefly in the evening for water heating in case the water isn’t yet up to temperature, and when the electricity price falls below the gas price I can enable the immersion heater on full power.
All accessible hot water pipes are insulated.

Electric car charger:

I built my own electric car charger that takes an external radio signal to switch between four settings 0, 6, 10 and 16 Amps to help me adjust consumption to match to availability of output from my solar panels. (Subsequently such products were developed commercially with continuously variable current limits, but the limitations of my immersun and on/off radio signal don’t allow me to go quite that far. Having said that my car only does 0, 6, 10 and 14 Amps so I would gain no benefit from a continuously-variable charger paired with a 4-level car).

Smart electricity controls:

Smart controls
top: HEMS (to manage bought electricity) and junction box
mid: radio transmitter (to car charger)
bottom: immersun (to manage self-consumption)

We have two systems for smart control of electricity:
1. The immersun to maximise self-use of our solar electricity by proportional control of loads.
2. A HEMS to manage the purchase of electricity (when necessary) at the lowest price by maximising consumption when the price is lowest.
When both systems want to enable loads (because the bought price is low and we have a surplus from our own panels) then cost is prioritised, so we’ll buy from the grid any demand not being met from our own panels.
Both systems are linked to 3 devices:
1. Battery storage. The immersun is configured to work alongside the battery storage with the battery storage as the top priority to receive surplus solar PV. The HEMS can switch the status of the battery as required to charge from the grid when the price is lowest, or to discharge when the price is highest, or indeed to revert to default behaviour.
2. Car charger. Second priority for the immersun after battery storage.
3. Immersion heater. Third priority for the immersun after car charging.

The future

I have no firm plans for the future. I’m toying with adding to the HEMS various features including:

Making the display switch between GMS and BST as appropriate (it’s all UTC at the moment).
Edit configuration via the web interface rather than a virtual terminal.
Control a domestic appliance. Our washing machine was replaced relatively recently, but the dishwasher is playing up a little and may be a candidate for HEMS integration where the optimum start time is selected to deliver lowest energy price.

Different perspectives

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Smart Meter HAN
Smart Meter WAN
Powervault
Immersun

The above images show four different perspectives on the same day of data (April 24th) from different sources within the home.

Firstly, the Smart Meter HAN image shows bought electricity to the home. Each smart meter sits on a Home Area Network (HAN) which is how the In-home display provided with the meter gets its data. The in-home display is an example of a Consumer Access Device (CAD). In my case I also have a Hildebrand Glow Stick as a CAD. The Glow Stick, which looks something like an oversized USB stick, also connects as a CAD to the smart meter allowing the meter to be read. An associated app, Hildebrand’s Bright, allows the Glow Stick to be read via the cloud. In principle the Bright app can display either energy in kWh or cost, but in my case can only display energy in kWh as Octopus don’t push the price data into the smart meter so energy cost always reports as zero. The data is presented by the minute.

Secondly, the Smart Meter WAN image shows the same data but from the perspective of the Wide Area Network (WAN) whch connects the smart meter to the energy retailer (Octopus for me). This half-hourly data is reported via the Octo Watchdog app. The data reported is cost per kWh (the blue line) and energy consumer / kWh (the red columns). The energy data in the red columns follows that of the red line in the prior illustration but in lower resolution (half-hourly versus minute-by-minute). You can clearly see most energy being bought when the price is lowest.

Thirdly, the Powervault image shows grid in/out and battery in/out. The green grid-in line mimics the red data from the above images. The battery in/out data is solely visible in this image. The resolution is good enough to see shorter events like kettle boil cycles.

The final image, from the Immerun, is probably the most useful although it lacks energy price and hides battery in/out within the House data (hence ‘House’ being zero at times). The immersun alone reports output data from the solar panels and diversion to the immersion heater. It also lumps the car charger energy within ‘House’, indeed none of these views can directly report the car charger behaviour although its the dominant energy consumer here.

I’m planning to construct my own view showing all the different prices of data together in one place. I already have access to:

The Immersun data via the same API called by their app. I came across a blog post that described how to do this.
The Powervault data API (I only have a control API at the moment) which should give me battery in/out (at least I’m on a promise of the API at the moment).
The Hilbebrand data which duplicates the Powervault Import/Export at the moment, but has the potential to provide independent monitoring of my car charger.

In principle then that would leave me able to report 3 x energy sources (grid, panels and battery; of which grid and battery would be bi-directional) and report 3 x energy consumers (car, water heating and home).

Solar PV Generation to July 2018

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What contrasts 2018 has been so far for solar PV!

As ever, my graph shows the maximum, average, and minimum daily output for each calendar month of each year since the system was installed in late September 2015 (approaching 3 years ago). As can be seen from the middle group (the daily average) 2018 has produced a run of 3 months May to July with the best daily average outputs for their respective months since installation. February 2018 was also the best ever February; although January, April and May managed to be the worst examples of their respective months. Hence certainly a year of contrasts as every month is either the best or worst for its respective month since installation.

At the level of the best day in any calendar month (the blue line), May is remarkably stable with the best daily output for May for each of the last three years being almost identical, while new monthly records were set for February, June and July.

July 2018 was also a record-breaker for another reason – it was the first month in which our earnings from the feed-in tariff (which in the UK has both generation and export components) exceeded £100. That achievement is helped by the index-linking of the feed-in rates which rise every year, and by July having 31 days which gives a slight edge over June’s 30 days.

Electricity use 2017

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The image above shows my solar electricity generation and usage in 2017 by calendar month.

The purple line shows the use of electricity (excluding gas replacement) by month. It’s relatively stable through the year, although it does rise in the autumn as my daughter started school and so my electric car mileage increased.
The green line shows the output from the solar panels. From April to August (5 months) solar panel output exceeded usage giving the potential not to buy electricity with sufficient smart capability – be that electricity storage or alignment of consumption with availability.
The red line shows import of electricity from the mains. It tends to be the reverse of the solar panel output. It’s never zero indicating potential (at cost) to improve smart usage. Solar power is a more significant energy source than imported power from March to September (7 months).
The blue line shows diversion of surplus electricity to water heating as gas replacement.
The turquoise line shows export of electricity to the grid. This occurs when there is insufficient energy smart resource available to store or self-use the surplus power. Export amounts to about 12% of total solar panel output. While this potentially free energy, the economics of storage or smart controls make using this remainder increasingly costly from an investment perspective. In my case this surplus occurs on particularly sunny summer days when the electric car is not at home or is already fully charged – which might be vacation periods when the house is unoccupied for example.

Greening Me

One man's steps to a greener lifestyle.

Category Archives: Solar PV

Smartening up

Payback time

Thoughts on intensity (of the CO2 variety)

Monitoring the HEMS

Saving on electricity

How green was my xxxxxx solar?

The Big Picture

Space heating:

Electricity supply:

Water heating:

Electric car charger:

Smart electricity controls:

The future

Different perspectives

Solar PV Generation to July 2018

Electricity use 2017