I've been pondering a idea: why not let my car sell electricity to the grid during peak usage times and recharge when prices are low?
Here's the scenario. After work, I pull into a charging station, but I’m not in a rush to charge. 7 PM is peak electricity demand, and prices are sky-high. I set my requirements—must charge to 90% before leaving tomorrow morning—and then I wait.
The key point is this. My electric vehicle can discharge back to the grid. The process works like this: the charging station connects with the vehicle’s BMS (Battery Management System), and an intermediary reads the current battery level and electricity prices. I input a time constraint (e.g., must have 90% charge by 7 AM), and the system starts working—during peak hours, it instructs the charger to discharge back to the grid, sending 10kWh of power and earning about 5 dollars.
But there's a critical issue: how to ensure that the electricity I send out truly comes from the battery and not from some sneaky diesel generator? This requires zero-knowledge proofs for verification. By analyzing the voltage drop curve of the BMS, the system can prove that the power was indeed discharged from the battery, with no cheating possible.
At 3 AM, electricity prices drop to 1 dollar per kWh, and the charger begins replenishing. Charging 20 kWh costs only 2 dollars, and the battery is full again. Doing the math: I net a profit of 3 dollars, and the car is fully charged.
It sounds perfect, but there's a real-world issue we must face—frequent charge and discharge cycles can impact battery lifespan. Therefore, this system’s algorithm must factor in the actual depreciation cost of the battery. Only when the price difference is large enough to cover the depreciation will the system execute discharging. In other words, arbitrage isn’t possible every peak; you have to wait for truly profitable opportunities.
This approach offers opportunities for Tesla owners, charging station operators, and even professional arbitrage traders. The key is to seamlessly connect on-chain verification with real-world charge/discharge processes, making every kilowatt-hour provable and traceable.
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MetaverseLandlord
· 10h ago
Zero-knowledge proofs prevent diesel engine cheating, this idea is really brilliant haha
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Basically, it's like doing financial management with batteries, quite interesting
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Including depreciation costs is truly clever, otherwise arbitrage could lead to the car being scrapped
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Wait, who will maintain this system? Will the charging station providers cooperate?
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Tesla owners are about to make a profit again, but I don't think the arbitrage space is that big
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On-chain verification of electricity consumption... sounds like energy futures trading
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The key question is whether the State Grid dares to open up this channel
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Can the battery cycle life really cover those few dollars in profit?
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I just want to ask, how long will it take for this to truly land?
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ForumLurker
· 10h ago
Hmm… I didn't quite get the zero-knowledge proof part, but I do understand the arbitrage logic.
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Wait, can the depreciation cost of the battery really be calculated? Feels a bit mysterious.
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Basically, it's a disguised virtual power plant, but the scale is ridiculously small. What can you do with 3 yuan?
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How to prevent hackers from messing with the BMS integration?
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I just want to know if operators would really be willing to adopt this system… Isn't the cost just added unnecessarily?
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MEV_Whisperer
· 10h ago
Zero-knowledge proof anti-cheating is indeed impressive, but the real bottleneck is still battery degradation.
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MetaverseMigrant
· 10h ago
Speaking of which, this logic is indeed interesting, but to be honest, it just turns car owners into small electricity traders. I think the zero-knowledge proof anti-cheating mechanism is a bit over the top; it seems to be adding costs to the transactions.
I've been pondering a idea: why not let my car sell electricity to the grid during peak usage times and recharge when prices are low?
Here's the scenario. After work, I pull into a charging station, but I’m not in a rush to charge. 7 PM is peak electricity demand, and prices are sky-high. I set my requirements—must charge to 90% before leaving tomorrow morning—and then I wait.
The key point is this. My electric vehicle can discharge back to the grid. The process works like this: the charging station connects with the vehicle’s BMS (Battery Management System), and an intermediary reads the current battery level and electricity prices. I input a time constraint (e.g., must have 90% charge by 7 AM), and the system starts working—during peak hours, it instructs the charger to discharge back to the grid, sending 10kWh of power and earning about 5 dollars.
But there's a critical issue: how to ensure that the electricity I send out truly comes from the battery and not from some sneaky diesel generator? This requires zero-knowledge proofs for verification. By analyzing the voltage drop curve of the BMS, the system can prove that the power was indeed discharged from the battery, with no cheating possible.
At 3 AM, electricity prices drop to 1 dollar per kWh, and the charger begins replenishing. Charging 20 kWh costs only 2 dollars, and the battery is full again. Doing the math: I net a profit of 3 dollars, and the car is fully charged.
It sounds perfect, but there's a real-world issue we must face—frequent charge and discharge cycles can impact battery lifespan. Therefore, this system’s algorithm must factor in the actual depreciation cost of the battery. Only when the price difference is large enough to cover the depreciation will the system execute discharging. In other words, arbitrage isn’t possible every peak; you have to wait for truly profitable opportunities.
This approach offers opportunities for Tesla owners, charging station operators, and even professional arbitrage traders. The key is to seamlessly connect on-chain verification with real-world charge/discharge processes, making every kilowatt-hour provable and traceable.