Nigel Morris, who heads up business development at Solar Analytics, readily admits electricity plan comparison products aren’t usually particularly exciting.
Still, it’s clear talking to Morris that Solar Analytics is excited about its recently-launched Plan Optimiser, and Morris reckons both subscribers and solar installers will be as well.
Morris told SolarQuotes this week that all too often installers are expected to have the best electricity plans at their fingertips – and they don’t.
After all, in putting together Plan Optimiser, Solar Analytics found several thousand plans across the country. Most people are eligible for at least 20 different offers, with some able to choose between 38 different retail offerings.
And, as the Australian Energy Regulator recently found in its State Of The Energy Market 2021 report (PDF), energy providers tweak plans constantly; partly because that makes it hard for anybody to keep track of which electricity plan is the best.
Hence the launch of Plan Optimiser, a service Solar Analytics is offering as a standard inclusion to all existing and new customers. This enables a subscriber to “go in at any time, and look at what plan is best for them, and what switching plans would save them,” he told us.
Morris said each month Solar Analytics uploads the latest electricity plans to keep the tariffs up-to-date.
Plan Optimiser Can Compare Time Of Use Tariffs
The other key angle is Plan Optimiser draws on the huge amount of data collected from Solar Analytics customers.
“By using real data, we can do some extremely cool things,” Morris said.
“We can tell when energy is being used, when it’s being generated, and we can see if a battery is connected.”
This means the Plan Optimiser can go beyond just comparing per-kWh prices to letting a customer know which time-of-use plans will provide the most benefit, as the company can see the time a customer is importing and exporting power.
Also, as a customer’s electricity demand and generation profiles change over time, Morris said Plan Optimiser can track those changes and suggest suitable alternatives.
Ever since the launch of Solar Analytics, the company has wanted to put together a software offering that would let its customers get the best possible electricity plan price, and Morris told me the company has devoted the last two years to collecting and analysing customer data and building algorithms to match customer electricity usage to the available offers.
“The main effort has been going on over the last year”, Morris said.
“That involved testing theories we had, capturing the plan data the right way, scraping and uploading that data from providers, and developing the algorithms.”
Other work included creating a digital bill uploader (due for imminent launch) and creating the comprehensive tariff engine, “My Electricity Bill”, to retain customers’ historical data.
Also on the roadmap are optimisers for batteries, electric vehicle charging/discharging, and virtual power plants (VPPs).
“Most solar owners don’t realise how much is left on the table”, Morris said.
Mostly they get as far as suspecting they’re on the wrong plan, but aren’t sure, and are rightly intimidated by how hard electricity plan comparison can get.
“Energy plans are deliberately built like that – providers are tweaking to get the most perceived advantage. Some plans look great until you get over 10kW of solar, then the whole deal changes. It’s mindbogglingly complex and constantly changing.”
That’s why the number of people switching providers has been falling for the last three years (according to the Australian Energy Regulator): nobody wants to analyse energy offers to work out if they should change.
“The providers have made the comparison of plans incredibly complicated”, Morris said.
He said when Solar Analytics analysed their pilot group, they found 70% of households would save money by switching electricity plans, at an average saving of $400 a year. With Plan Optimiser now in the wild:
“we expect to find that between 80% and 90% of people will be able to find savings.”
And if you don’t have Solar Analytics installed, you can find the cheapest flat-rate electricity plan1 in about 30 seconds using SolarQuotes’ own electricity price and feed in tariff comparison tool.
If you have 12 months of bills to hand you will get a very accurate comparison. If you don’t, you’ll still get an excellent estimate based on typical imports and exports for your location and system size.
By the way, you can learn more about the many benefits of installing advanced solar power system monitoring here.
Footnotes
- Time of use plans coming as some as Finn gets time to design it ↩
About Richard Chirgwin
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I have similar service in pvoutput
PVOutput does not have this option.
You can certainly input an alternative plan into PVO for it to do the comparison calculation but you have to find the plan yourself in the first place.
SA is tapping into the data base of the hundreds/thousands of retail plan options there are available and which are constantly changing.
I purchased a lifetime subscription to Solar Analytics when I installed my solar PV system (using your website to select the installer) – based n your advice to have a monitoring system. It’s worked a treat …. thank you muchly !!
The Plan Optimiser is definitely a big and very useful improvement to the Solar Analytics functionality and makes its subscription cost (especially the lifetime subscription) even better value for money than it already was.
I’ve had a quick-sh look at the Plan Optimiser and it looks like it will be very helpful in looking for the “best” retail plan. However, unless I’m missing something” it appears that it only looks at the last 3 months of data (usage, solar generation and feed-in) which seems unnecessarily restrictive in its application.
I would think that using as much available data as possible – up to a full year if it’s available – would be much, much more useful and meaningful as it includes the significant variation in usage and solar generation across the 4 seasons. (Maybe even allow the user to decide whether to use 3, 6, 9 or 12 months of data.) I’ve suggested this to Solar Analytics and am awaiting their response presently.
Nevertheless, I reckon the Plan Optimiser will be very useful in helping to minimise electricity costs.
Hi Saslim
Nige from Solar Analytics here – great feedback thanks. Yes, we selected a 3 month period to match typical billing periods. However, we know that other periods (longer or shorter) will suit some user better so stay tuned for some udpates! This is our first iteration and it will continue to evolve over the coming weeks and months.
Hi Nige,
Thanks for your response to my comment.
My suggestion for reusing 12 months data is not so much about billing periods as to do with taking into account the significant differences in solar generation, local usage, and energy exported to and imported from the grid.
The following illustrates the point I’m trying to make:
I’ve been thinking about switching to Energy Locals Flat plan (online member).
Based on the last 3 months of my data the plan optimiser shows a cost of
$332.26 for the Energy Locals plan versus $411.26 for my current AGL plan, a potential saving of $79 for the last 3 months. (It would be tempting – but incorrect – to multiply that by 4 and obtain a potential saving of $316 for a full 12 months or approximately $263 since 10 Dec 2020. (I only have about 10 months of usage data in Solar Analytics ie. since 10 Dec 2020.
I used the “Solar Savings” function in SA to determine the cost of energy imported from the grid since 10 Dec 2020; it was $806.31.
I then replaced the tariffs for my current AGL plan with those for the Energy Locals plan and then used the “Solar Savings” function to determine the cost of energy imported from the grid since 10 Dec 2020 ($630.47) and added $130 (10 months of membership for online members) which resulted in a total cost of $760.47.
This is just $45.84 less than my current AGL plan for the cost of energy since 10 Dec 2020 – not the $263 obtained by (incorrectly extrapolating the amount based on just the last 3 months of data).
This illustration based on actual data since 10 Dec 2020 indicates how misleading it can be with the Plan Optimiser using just the last 3 months of data to calculate potential savings.
I look forward to the next iteration(s) of the Plan Optimiser addressing this issue.
Kind regards
Thanks Salim – will keep you posted on updates!
Couple of questions for Solar Analytics if they are watching:
1. Does the comparison include analysis of demand plans? I ask because it’s starting to look like a demand plan is our best option. And in some places demands tariffs are going to become mandatory for many (e.g. QLD).
2. What data is SA using to make a comparison? The post above indicates the comparison is only using recent import/export data. I’d have thought a full year is really needed to get a decent idea given the seasonal variability. e.g. the best plan over the last 3 months would not be the best plan over a year.
As a couple of comments:
a. Past performance is not necessarily a good guide of what’s ahead when it comes to selecting the best plan. You have to take into consideration if you think there will be any substantive changes in household consumption and production, e.g. adding an EV, or more solar PV, or a new baby, or becoming an empty nester.
b. One of the other challenges with assessing tariffs is discerning which consumption is time of day discretionary and which isn’t. Plan assessment does need to account for this. Is it better to use daytime solar PV with a mix of daytime tariffs, or a predictable night time off-peak tariff?
Hi Alex – great feedback thank you.
On your first question on demand tariffs – if a demand plan is published and available, then we’ll be including it however, we currently focus on energy flows not demand for our economics.
We are aware of and considering the implications of demand tariffs and how we might calculate savings based on peak demand rather than energy flows and will keep you posted.
On your second question, we collect plan data for comparisons from a variety of sources and update our calculations on a monthly basis. We have launched with a 3-month comparison to coincide with a typical billing period but do intend to release updates and are already working on other periods.
On your final question, we hear you and understand that predictive forecasting would be cool – it’s also something we have talked about. For now, we believe our use of real data provides a huge advantage to most comparisons because we can calculate time-based energy use and thus recommend appropriate flat or TOU plans quite accurately. As is always the case, there is a never-ending range of options, use cases and features for us to consider but the good news is, our software is constantly and endlessly being refined – so stay tuned!
Does Solar Analytics cover the whole market, like billhero.com.au, or are they limited to retailers who contracted with them?
I’m on the Ausgrid network in NSW, in case this makes a difference.