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Comment by andyferris

4 months ago

> averaging power over 15 minute chunks, and taking the worst one of a year.

What an interesting metric. Wouldn't even a very cheap and small battery (definitely small enough to keep inside an appartment) provide enough smoothing to, like, halve this peak number? You could rig it to not even output energy until you are beyond the current year's peak usage... How much money would you save this way?

I just feel this number is so prone to small mistakes (grandma plugs in the wrong things at the wrong times) and hacks (like the above) that the relationship between users' reward/punishment and the grid's health seems wildly disproportionate.

> market rate price of the energy in each 15 minute chunk separately

I am currently on a plan with 5 minute market rates, can buy and sell in (sell prices can go negative - as can buy, actually), all automated. At least I feel we am working with the grid, not against it, and we make a small net profit (before depreciation).

> relationship between users' reward/punishment and the grid's health seems wildly disproportionate.

It's still much closer to the real costs for the grid operator than $/kWh. The fundamental problem that rooftop solar has revealed is that people think they are paying for the electricity, but they are not. Electricity is dirt cheap. Most of what they are paying for is the maintenance of the grid, and simple usage based billing crushes the system because of freeloader problem once rooftop solar is added.

Long term, the likely thing you pay for will be the size of the main fuse that connects you to the grid. Because that's the thing that scales with the costs you impose on the operator.

  • Actually the local cost is not the fuse size, but how much smaller the first transformer after you could be if you weren't there. Though it's often more fair to determine such for each user; then take those as a relative scale, then split the transformer's actual TCO by the determined share sizes between the users. Because the first user needs the transformer to it's peak size; the second only by the instantaneous-added peak size, which is lower as they won't use it peak at the same time.

    • > the first user needs the transformer to it's peak size; the second only by the instantaneous-added peak size

      Of course, how does the electricity company determine which user was first in this situation. A tariff that depends on the order of connection may not be practical for domestic situations, although it may be OK for very large users, e.g. factories, data-centres.

      Using fuse size seems a more reasonable and fair proxy for cost, assuming the same load patterns as the rest of the users. Then again, consumers with EVs might argue that their load pattern is different to the average user (e.g. filling up with off-peak electricity). Also consumers with air conditioning might argue for special treatment given their usage correlates with solar output (except where it does not).

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This is how it works in Japan for the newer rate plans for consumers now (replacing the previous method of charging you based on the size of your main breaker), but checked in 30 minute increments rather than 15.

The steps are pretty coarse - on my rate plan there are just 3 steps: 0-10 kW, 11-15 kW, 15 kW+. You're not going to surpass peak 10 kW in an apartment anyway.

It's legacy tactics; against the hacking the comparable thing for internet connections has historically been iirc 5 minute chunks and then taking the 95th percentile (like, charging not the highest, but the one 5% away from the highest). Not sure about the 5 min aggregation tbh.

The 15 minute chunks are due to the German and much of the European grid market being in that chunk size.

> Wouldn't even a very cheap and small battery (definitely small enough to keep inside an appartment)

Like namibj mentioned, this does not apply for residential contracts.

  • I don't think it's necessarily impossible to get that billing model as a household; it's just not an interesting one to have as it's not competitive for the usage patterns of a household.