Recently, I saw something interesting: Tesla is building a trading team to trade energy (electricity) in the future – the Autobidder platform. It allows real-time trading and control of energy, such as Tesla’s Powerpacks, Powerwalls, and Megapacks. The assets are optimized through machine learning to better utilize assets and monetize them more directly. Currently, the platform manages more than 1.2 GWh of stored energy.
Tesla’s Virtual Power Plant
Essentially, Tesla is integrating the energy system by creating a Virtual Power Plant. The background is that California’s high temperatures have increased demand for the power grid, while drought has affected hydroelectric power output. Tesla’s solution is to use its own system to aggregate the Powerwall user group in California and release some of the energy from the energy storage battery system when needed to assist the power grid.
Note: Tesla’s Virtual Power Plant is currently a public welfare program that supports the California power grid and does not provide user incentives, but there may be in the future.
From a large-scale perspective, Tesla is gradually integrating vehicle batteries (not yet connected), Powerpacks, Powerwalls, and Megapacks into a comprehensive energy storage station and dispatching energy (electricity) through an energy trading model when the power grid is needed. We can understand that as Tesla couples with power grids overseas, it uses classical statistics, AI machine learning, and numerical optimization to predict electricity prices, electricity load, and power generation, and then realize smart bidding. In the future, this system will activate energy storage resources through the trading system to increase the prospects of energy storage systems.
From a logical perspective, countries like China, with strong power capacities, have relatively narrow trading spaces (although, with the increasing amount of renewable energy on the grid, trading is also possible). However, in places like Europe and America, transient price fluctuations can recover the asset costs of batteries.
This system coordinates the demand and deployment of power and is further applied in daily, real-time, and continuous trading. Looking ahead, it will promote energy transformation, and future electricity trading will become feasible.## Outlook of China’s Energy Storage and Power Prices
In China, the electricity transaction is dominated by the state, and the electricity transaction institutions include regional electricity transaction centers and regional electricity transaction centers. China has built 32 regional electricity transaction centers and 2 regional electricity transaction centers (Beijing Electricity Trading Center and Guangzhou Electricity Trading Center). The electricity trading center is mainly established jointly by the power grid company, local major power generation enterprises, and electricity users. At present, electricity trading centers are controlled by power grid companies.
Looking into the future, there is a possibility of a certain amount of transaction in the area of charging in the current residential area. On the one hand, it is the matching of the entire rechargeable capacity and the local electricity consumption capacity in the residential area. On the other hand, after the residential area adds energy storage in the future, it will be adjusted after connecting to the electric vehicle. Personally, I think there is such a game here: the adjustment of AC intelligent charging sockets. In this way, by configuring the charging ports that the residential area can install in the regions that can be installed in the residential area, and the overall dry capacity is pulled from the residential area, and then connected to the APP through the AC intelligent charging sockets, the total charging time is set through the bidding mode Segment. That is, through digitalization, the backend realizes the scheduling between each residential area and charging interface, so as to achieve the bidding game between users under the coverage of the entire residential area. The most meaningful part here is that under the condition of realizing V2G, this energy system can trade the total power load of the residential area.
Note: The total charging capacity of the residential area is limited.
Summary: I think that with the spread of electric vehicles, the impact on the power grid is not a one-sided increase in load. With the introduction of intelligent systems, there are many new ways to play.
This article is a translation by ChatGPT of a Chinese report from 42HOW. If you have any questions about it, please email bd@42how.com.