Category Archives: Electricity storage

Payback time

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.

Diverted1056.5 kWh*£0.04=£37.25
Exported338.6 kWh*£0.00=£0.00
Generated3985.6 kWh*£0.17=£693.51
Imported4748.9 kWh*-£0.16=-£776.92
House7339.4 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.

Diverted1056.5 kWh*£0.04=£37.25
Exported338.6 kWh*£0.00=£0.00
Generated3985.6 kWh*£0.17=£693.51
Imported4748.9 kWh*-£0.08=-£382.29
House7339.4 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)

Power(vault) to the people

It’s now around four and half years since I bought my Powervault G200 storage battery and two years since I started managing it from my Home Energy Management System (HEMS).

Originally the Powervault set up simply to store surplus electricity from my solar panels for later use but, following my change to Octopus’ Agile tariff, I started to use the Powervault to optimize electricity costs when there wasn’t going to be enough solar, charging when electricity was relatively cheap and discharging when electricity was relatively expensive. Initially I configured the Powervault manually to achieve this but later moved to the HEMS doing it automatically.

The fundamental principle has remained the same through both manual and automated periods, with the battery being set into one of three modes depending on price:

  1. Force charge – where the battery charges at full power (usually from the grid) for the required number of hours – when grid electricity price is cheapest.
  2. Only charge – when the battery charges proportionally to the solar surplus (but will not discharge) – when grid electricity is mid-price (i.e. too close to the price at which the battery was being force charged to be economically advantageous to discharge)
  3. Normal – when the battery charges or discharges proportionately to the solar surplus/shortfall – when grid electricity is comparatively expensive compared to the force charge price.
Battery operating mode for different conditions

The current logic now reflects electricity price, time of day and state of charge. The fundamental relationship is with grid electricity price as previously described, but with two further refinements:

  1. During the day, even when the electricity price is relatively high, the battery is held in charge only until 80% state of charge is obtained. This helps ensure that a high state of charge is obtained before the early evening peak in Agile prices from 4 to 7 PM by not allowing the battery to discharge while the expectation is that it is being charged from solar. In the depths of winter, when the battery is more likely to be charged overnight and thus start the day with a high state of charge, the same logic allows the battery to discharge to 80% if electricity is costly during the day but still preserves charge for the early evening peak.
  2. Similarly if the battery is full, but the grid price is medium, then the battery is also allowed to discharge to 95% during the day. This allows the battery to discharge slightly to cover small peaks of demand on the assumption that a small amount of solar recharge may well be possible even if the solar forecast wasn’t high enough for recharging at full power.

To consider the two bookends of behaviour:

  1. On a really sunny day like tomorrow, the HEMS doesn’t anticipate any need to buy electricity from the grid for battery charging so all electricity is relatively expensive. The HEMS will allow the battery to discharge overnight (completely if necessary) . From 8:00 AM the battery will only be allowed to charge until 80% state of charge or 4:00 PM is reached after which the battery will be put back in Normal operation when it has the freedom to either charge or discharge.
  2. On a winters day, the HEMS potentially fully charges the battery overnight. Between 8:00 AM and 4:00 PM the battery is allowed to discharge to 95% if grid electricity is mid-price (with some hope that the 5% may be recovered from solar), or to 80% if grid electricity is high price. After 4:00 PM the battery reverts to Normal operation for the evening peak period.
Example Agile prices with typical UK domestic consumption.

I’m very pleased with how robustly my battery integration operates. It is however reliant on the continuing availability of the Powervault G200 cloud which may not be around forever as the G200 model has now been superseded. My own example is currently four and a half years old.

Current clamps

Main electricity supply cutout with current clamp above

As previously noted, I recently had the main supply cut-out to my house uprated from 60 to 100 Amps in preparation for installation of an additional electric vehicle charger. That involved my Distribution Network Operator (DNO) replacing the fuse within the black fuse holder with the torn red label above and replacing the brown live and blue neutral cables between the cutout and the electricity meter to the top right of the picture. In my case the technicians involved automatically moved the black current clamp that sits above the cutout from the old live cable to the new one without even mentioning it, but it did occur to me that it would be worth documenting what current clamps I have, what they do and where they are for the benefit of any future trades who may not replace like-for-like.

I have two devices that currently use three current clamps between them:

  1. Immersun. Has two current clamps, one for control and one for solar generation data only.
    1. Immersun control clamp is around the main live feed between cutout and meter as pictured above and illustrated below. It measures any flow of electricity to the grid and prompts the Immersun to divert this to water heating or car charging.
    2. Immersun generation clamp is around the main live feed between the inverter for the solar panels and consumer unit and specifically inside the rotary isolator on this cable (being a good location where the live alone can be encircled without the neutral).
  2. Powervault battery. Has 1 current clamp inside the consumer unit which encircles both the incoming live and the live feed to the immersion heater. These two cables are orientated such that flow from the solar panels to the grid or to the immersion heater passes in the same direction through the clamp as illustrated below. (This is unorthodox and not what the installation manual describes, but is done to force the priority of the battery over the immersun when a solar surplus is available)
Positions of 2 of 3 current clamps.

There were previously three additional current clamps which were used by UK Power Networks (UKPN) my local DNO who part-funded my battery storage four years ago as part of a trial. Some of these clamps may still be present as I can still see some of the associated cables, but are no longer actively used as the associated data loggers are long gone. These clamps monitored: grid in/out (duplicates 1.1 above), battery in/out (duplicates battery’s own internal measurements), and solar panel in/out (duplicates 1.2 above).

DNOs tend to be concerned about excessive exports to local electricity grids which can cause voltage quality issues. Any export from a battery could add to any export from solar panels and could cause the DNOs preferred export limit to be exceeded. Given that the battery, as installed to the manufacturer’s advice, would measure the total export then it would be possible software within a battery to limit battery export such that the sum of battery plus solar export never exceeded the DNO’s recommended value. In practice the gross output of a 4 kWp solar array rarely exceeds the 16 Amp export limit even before the load of the home is subtracted to achieve the export from the home, so in many battery + solar installations there’s little prospect of the limit ever being exceeded even without such software limits.

The question that recently occurred to me is whether if a battery had such a software limit would that limit be defeated by my unorthodox installation of the battery’s current clamp?

Conceptual arrangement of clamps

My physical arrangement on the battery clamp encircling both the feed to the consumer unit and the cable to the immersion heater is equivalent to feeding the immersion heater from a connection between the meter and the consumer unit and having the clamp between that connection and the consumer unit. As such the battery clamp may read higher than the actual export since some of the power from the solar panels that is measured by the clamp may be diverted to the immersion heater without actually being exported. Thus, if the battery has a software function to limit to export, an arrangement like mine will cause the export limit to operate more aggressively than design intent and the DNO’s export recommendation will not be exceeded. Once the water is hot, and no further diversion occurs, then a battery clamp positioned like mine will record the same current as the meter and the Immersun’s clamp. Since I regard export as an error state then such a more aggressive limit on export is of no consequence to me.

Leading the charge

Regular readers will know that my Energy Smart home includes a storage battery. That battery is either charged from my solar panels (effectively free electricity), or low cost electricity bought from the grid, or some combination of the two depending on the solar forecast for the day ahead.

The logic of how much battery charging is required has until now been driven by a set value for the number of charging hours required. The number of hours of solar charging predicted is deducted from the the number of charging hours required to calculate the number of bought charging hours required outside the solar production window.

Bought charging hours required :=

Total hours required – Solar hours predicted

However with experience this appears to be a sub-optimal arrangement. At one extreme on a very sunny day the battery will fully charge and then be allowed to discharge continuously through all other hours, there is no middle ground in which the battery is not permitted to discharge through the night. However at the other extreme if the battery is replenished entirely from the grid then there will be hours when discharge is not permitted since, after accounting for cycle efficiency, the value of the electricity in the battery is higher than the cost of that from the grid and thus it’s better value to use grid electricity than stored electricity. As there are fewer discharging hours then fewer hours of charging will be required to refill. Thus the depth of discharge is greater when charged from solar than from the grid requiring more charging hours to refill. Leaving the longer charge time for a full charge in use then creates a risk of charging the battery when the grid price is higher than necessary leaving the battery possibly full by the time the lowest cost grid energy is available. Having a more accurate target for the charge time would enable the lowest cost charging periods to be selected more precisely.

Schedule with some solar

The new refinement is to automatically adjust the bought charging hours between two existing user-defined values: the existing target hours and the maximum charging hours currently used just to cap charging hours during plunge pricing events (i.e those with negative cost events). The new algorithm can adjust to any value between the two limits in half hour intervals. As currently configured that’s anything between five and seven hours. The new algorithm is:

Total hours required := minimum (Maximum hours from plunge,
maximum (Target hours, Solar hours predicted + 1))

max hours (A)Target hours (B)Solar hours (C)C + 1Max (B, c+1)Min (A, Max(B, C+1))
7.05.0>= 6.5>= 7.5>= 7.57.0
7.05.06.07.07.07.0
7.05.05.56.56.56.5
7.05.05.06.06.06.0
7.05.04.55.55.55.5
7.05.04.05.05.05.0
7.05.0<= 3.5<= 4.55.05.0
Output of new algorithm,

Opportunities in the import / export business

Most of us are used to a simple world of electricity where we pay for what we consume. For most folks like myself based in the UK that’s typically a fixed price per kWh/unit consumed regardless of time of day, even through dual-rate tariffs have been around for decades – the best known being “Economy 7” tariffs. However as the grid gets smarter then there are increasing opportunities to save on, or make money from, electricity.

Electricity opportunities for import / export and positive /negative cost.

Conventional – pay for power.

This is the area with which most of us are most familiar. We all get the idea of paying for the power we consume. Most UK households pay a fixed price per kWh/unit regardless of the time of day. We have a competitive electricity market, so there are the choice of 70 to 80 different providers who will make different offers regarding standing charge (sometimes marketed as a subscription) and unit cost.

There’s also the opportunity to choose between a flat rate tariff or Economy 7 even on conventional meters that provide a discounted night rate for 7 hours.. These typically provide a discounted night rate, but may charge a little more during the day. They used to advertise these as ‘less than half-price electricity’ but that’s often not the case now.

Stepping up in complexity (and opportunity) smart meters provide the opportunity for a more diverse range of tariffs including different cheap night time periods, more than two rates at different times of day (in extreme 48 half-hourly rates), and a free day at the weekend (i.e. a zero rate of a weekend day) etc.

Beyond that my own tariff (Octopus Agile) not only has up to 48 different half-hourly prices/day that change daily based on that day’s market prices. That might sounds a bit scary but it can yield very cheap electricity prices – 4.48 p/kWh for me in April/May 2020 (for example) which is a third of what most people pay.

My electricity costs April/May 2020

(The original version of this post wrongly had the table from my gas bill above and mistakenly claimed that I had paid “a quarter of what most people pay” rather than a third. Total consumption is untypically low at the present time due to limited miles driven.)

Agile – paid to consume

Top left on my initial diagram is Agile – paid to consume.

One of the features of the wholesale electricity market is that at times the market price for electricity goes negative. At such times the a significant excess of supply (typically because of high output from wind turbines) over demand (often but not always at night) yields a negative price so electricity companies looking to buy electricity are being paid to take it. Most electricity companies will continue to charge their customers the standard price in these circumstances but, with the octopus Agile tariff, the negative pricing is passed to the consumer so that you are paid to consume electricity. This is one of the reasons that my electricity costs are so low.

My electricity costs – Saturday 23rd May 2020

The above chart shows my electricity costs for Saturday 23rd May 2020. The blue line shows the half-hourly electricity price varying between minus 10 p/kWh and plus 15 p/kWh. The red bars show my electricity consumption in each half hour. You can see how consumption tends to be highest when the price is lowest leading to an average price paid of minus 6.22 p.kWh (i.e. they paid me to use electricity) – indeed they paid me 82.4 p to buy electricity that day.

Conventional export – paid to export

The next opportunity to make money from electricity is to sell it to the grid. Obviously that depends on having a source for the electricity typically a generating asset like solar panels or a wind turbine, possibly coupled with a storage device like a battery. It’s also possible with a battery alone, but I know no-one who does that as the economics are more challenging.

The UK currently has a scheme called Smart Export Guarantee (SEG) where you can sell your export to an electricity company. Prices vary enormously so it’s worth shopping around and not just assuming that your electricity company will give you a good offer.

SEG rates from the Solar Trade Association

There is also a smarter SEG option where Octopus offer a dynamic SEG based on market rates (Octopus Agile Export) which may at times offer a high rate, but also offers a lower rate at times, and is thus perhaps better suited to those with storage.

I myself am NOT on such a tariff as I’m on an older legacy Feed-in Tariff (FiT). Despite its name FiT is a generation incentive, not an export incentive. As a generation incentive FiT encourages self-consumption since each kWh that I consume myself does not reduce my income, whereas on SEG each kWh that I use myself (such as making hot water) would reduce export income. So, for example, if I use a kWh of electricity to make hot water that’s saved a kWh (or thereabouts) of gas at around 3 p/kWh, but if I was on SEG then I might have lost 5.5 p/kWh of export revenue to save 3 p/kWh on gas which is clearly an on-cost not a saving. There are other benefits of course because I’ve reduced my carbon footprint by using my own low CO2 electricity to replace a fossil fuel, but it’s not (in this case) improving my financial position.

A further area of research by others is V2X (V2H and V2G) – taking electricity stored in an electric vehicle and using that within the home (V2H) or exporting it to the grid (V2G).

Export penalty – penalised for export

A logical consequence of this smart grid that I’ve outlined is being penalised for export. If there are times when the market price for electricity is negative then if I were part of that market then I might expect to be penalised for export. This doesn’t actually exist in the UK, as the only model that links SEG payments to the market price, Octopus Agile Export, protects its customers from negative pricing.

Should consumers be exposed to this risk then a logical behaviours would be:

  1. To manage self-consumption into the negative export periods, and potentially thus increase export in the positive export periods. For example disable diversion to an immersion heater or car when export price is positive, and then maximise self-consumption when the export price (and presumably the import price also) is negative.
  2. To disable the generating asset to avoid the export penalty.

Conclusions

Some people like myself will find developments in the smart energy sector a fascinating and engaging topic with opportunities both the save money and engage in creating a cleaner and greener electricity system.

However given that many choose not to even participate in the competitive market for electricity supply created when the regional electricity companies were privatised in late 1990 (i.e. 30 years ago) then there will be a significant number who are not so motivated.

This then creates opportunity for a wider variety of smart offers. Some products, at the Agile Octopus end of the spectrum, giving the consumer the opportunity to benefit from their own decision making, while others look more like a traditional dumb tariff with a very simple price structure but potentially making the energy company a more active manager of the home appliances so that the consumer hopefully plays a lower unit rate while the energy company takes responsibility for managing the assets within the home.

Thoughts on intensity (of the CO2 variety)

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.

Example of UK grid CO2 intensity

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:

  1. 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)
  2. Make best use of storage to minimise consumption from the grid in the evening peaks when embedded CO2 is likely to be highest.
  3. 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

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:

HEMS monitor

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.

Tonic solar, a little light music

As winter turned to spring my thoughts for my HEMS turned to thinking about how to adjust the operation of the HEMS in managing battery charging to account for anticipated solar production. Previously the HEMS was configured to buy a preset number of hours of charge from the grid each day, typically overnight when the power tends to be cheapest. Through 2019 as the seasons changed I periodically adjusted this figure to create headroom to store charge from the solar panels later in the day. However I would like to make this adjustment automatically day by day.

Late last year I came across solcast a website that predicts the output of solar panels. The user creates an account, describes their PV array (location, capacity and orientation), and can then download predictions via API.

Solar prediction for the next three days

The orange line shows the predicted output for the next few days, with the light grey area showing the confidence interval from 10 to 90%. As a prediction there’s a degree of uncertainty associated with the prediction as there is with a weather forecast. The 10% line shows that 1 day in 10 the output will be lower than the grey area, while the 90% line shows that 1 day in 10 then output will be higher than the grey area.

My original prediction were based on the orange line (the 50th percentile) where output was equally likely to be above or below this amount. However my risk on an incorrect prediction is not even. If I fail to buy enough power from the grid when the price is low then I risk paying up to 35p/kWh to buy when the price is high, whereas if I buy an unnecessary cheap kWh from the grid I may spend an unnecessary 5p/kWh on average. Thus I decided to take a more conservative position on risk to obtain the lowest cost position. I opted for a 20% risk, so 1 day in 5 I might underestimate my purchase from the grid reflecting the ratio of grid prices high:low. I estimated this 20th percentile assuming a normal distribution on the low side where the 20th percentile = 0.34 * 50th percentile + 0.66 * 10th percentile.

The process is as follows:

  1. download the data in a half-hourly format to be comparable to the half-hourly Agile electricity price data,
  2. calculate the 20th percentile from the 10th and 50th percentiles,
  3. count the number of half-hours in the 20th percentile data above a threshold that provides for charging the battery at full power,
  4. establish the earliest half hour when solar would charge the battery at full power,
  5. adjust the period for buying power from the grid by the period anticipated for solar charging (tomorrow a total of 7 hours is to be achieved by 6.5 hours from solar leaving 0.5 hours from the grid),
  6. adjust the end time for buying power from the grid to align with the earliest hour when the battery can charge at full power from solar.
HEMS schedule with battery behaviour modified for predicted solar generation

The result of these calculations can be seen above. One half-hour of lowest price battery charging has been identified overnight to meet the requirement for charging from the grid. Normal HEMS behaviour has also identified several other periods of grid charging at lower cost during the day, but these are not counted towards the target for buying from the grid due to the potential for a double count of solar and grid charging during the day. (In a similar manner there are multiple start times during the afternoon when the dishwasher or washing machine can be run on grid power more cheaply than the optimal overnight start time.)

No explicit command from the HEMS is required to enable proportional charging of the battery from the solar panels when there is a solar surplus as 2 of the 3 used battery operating modes (normal and charge-only) have this capability, and the third mode force charges the battery. If the battery is force charged during solar surplus then the source of the energy will of course be the solar panels, but any shortfall will be met from the grid.

modecharge behaviourdischarge behaviourcomment
NormalProportional to solar surplusProportional to shortfallUsed at high grid prices (today discharging enabled at > 8 p/kWh)
Charge onlyProportional to solar surplusNo dischargeUsed at mid grid price to save stored energy for period of higher grid price (between 5 and 8 p/kWh today)
Force chargeFull powerNo dischargeUsed at lower grid price to buy from grid (today buying at < 5p/kWh). If low price occurs at time with reasonable solar generation then use of solar output will happen automatically, with only any shortfall coming from the grid.
Battery behaviour in different operating modes

Smart Export Guarantee – FiT for purpose?

Solar PV installations like mine that are a few years old generally qualify for the UK’s Feed-in Tariff (FiT) which pays both for generation and notionally for export, while newer installations are covered by the Smart Export Guarantee (SEG). The older FiT scheme was universal in the sense that all larger electricity companies had to participate and they all paid the same rates, while with the newer scheme there’s still an obligation for larger companies to participate but the rates are all different. Older installations like mine can optionally swap the export component of the FiT for the SEG, but is that an attractive option?

SEG Payments by provider

SEG payments differ widely between providers so it’s worth shopping around.

My FiT export payment is currently 5.38 p/kWh on a deemed export basis, which means that, rather than measure actual export, it is assumed that half of my generation is exported. My electricity supplier Octopus offerers one of the best SEG rates at 5.5 p/kWh but that’s on the actual export, not the deemed export.

Monitoring data March 2019 – February 2020
AlternativeDescriptionEnergy exportedRate paidTotalComment
Baseline FiT2,098 kWh (50% of 4,196.1 kWh) 5.38 p/kWh£112.87
Scenario #1 Switch to SEG without other changes 647.1 kWh5.50 p/kWh£35.5968% reduction
Scenario #2Add disable water heating from solar to above.1,722.4 kWh (1,075.3 + 647.1 kWh)5.50 p/kWh£94.75
Provide equivalent water heating from gas1,075.3 kWh 3.2 p/kWh / 90% (£38.23)
Total£56.5250% reduction

Octopus Energy does also offer the alternative of a variable export rate based on wholesale prices, akin to their Octopus Agile import tariff, but for export. However it’s my belief that I would need a much larger battery than I have now (4 kWh) in order to benefit from this as it will always be generally better value to use that stored energy to avoid the early evening peak price period (up to 35 p/kWh) than to sell it back to the grid at a lower price and then need to buy more energy myself. If I had a bigger battery (both in terms of energy and power) then I could both meet my own needs and sell back to the grid.

Overall however I think that it’s clear that, with my current relatively small battery and deemed export tariff, I’m better off on the older FiT scheme than the newer SEG scheme even with one of the better-paying SEG providers.

Saving on electricity

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:

sourcequantityest unit priceEst totalmy uniT pricemY totalmy saving v. Est
Bought4,309 kWh15.75 p/kWh£678.677.08 p/kWh£305.08£373.59
Generated2,473 kWh15.75 pkWh£389.500.00 p/kWh£0.00£389.50
Total / Average6,783 kWh15.75 p/kWh£1,068.324.5 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,