Comment by avianlyric | Hacker News Reader

Comment by avianlyric | Hacker News Reader

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You’re making the assumption that the loss is large enough to warrant the hardware improvements.

Getting high quality data about an electricity grid is extremely expensive and difficult. A big part of that in the U.K. is driven by the fact that most of our distribution networks are underground, which means that a lot of equipment is located below ground level.

This gives you one big problem, the place where you want to install your fancy new sensors are all located in places that most telecom systems don’t/can’t serve (4G doesn’t work very well in a hole). Plus to make your life even harder, power distribution equipment puts of plenty of EM interference, making radio comms even harder. So you can put the hardware in, you just can’t communicate with it. Making it kinda useless.

Obviously there are plenty of place were this isn’t true, but they’re in the minority. End result is that lots of fancy equipment doesn’t get deployed.

Counter - How do you know the level of loss if you don't have visibility into it?

(Power put on lines - expected transmission losses) * billed cost of power - customer payments.

I hope for the sake of their billing department they're using a database and some customized software for the data, but could just as likely be in a large and painful excel spreadsheet.

Power theft is not particularly interesting to the power company unless they're not getting paid for it. If it's just the wrong person paying, that's their problem.

I reckon you can chuck some machine learning at the problem. Sum of all meter readings on the sub network and then measure the power going in. Other variables might be ambient temperature, underground temp, etc.

You can measure power movements at a macro scale. So you can see how much energy is being produced by power stations, and how that’s being fed into distribution networks, plus you can sum all the power usage going through end user meters.

All that together give you enough data to pretty accurately estimate stolen power. But not enough data to figure out with any precision where it being stolen. You might know that certain parts of a city are worse that others, but you couldn’t identify the house or even road where it’s happening.

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