What happens after you plug in your electric car? A big underlying problem of the energy transition is this: who should charge when?
This game challenges you to find the best schedule. Can you beat the score of your friends?
Remember: The smartest charge is doing it for him/herself, but also for a balanced grid and for clean energy!
In this game you are the operator of several EV charging stations. EV owners will come to one of your stations and want to charge their cars. When they leave, the car should be charged (you get 50 per energy token). But if you let the car leave empty, you will have to pay a penalty (100).
On the other hand, you must buy the energy that you charge with from the grid.
You pay a variable price, depending on the supply in the system at the moment.
Note: You'll always buy or sell the next cheapest token. Exactly like in a market.
When there is little energy (negative imbalance, i.e. more demand than supply), you pay a higher price than when there is a lot of energy available (imbalance is positive, i.e. more supply than demand).
You can also use this to your advantage, by using the stationed cars as batteries. Charge when energy is cheap and discharge when energy is expensive. But be careful not to let the cars leave empty!
By balancing your import and export to the grid while having all the cars leave fully charged will give you the greatest profit. All the while you are helping balance the grid and charging cars for users. Win-win-win!!!
Each turn you have several options available. For each car currently at one of your stations you can decide to:
When you're happy with the changes in all your chargers, you can commit them by clicking 'next turn'. Shortcut: [Enter] The transactions are now included in the game grid and the active turn-line now moves down one.
Your score will increase or decrease with each turn you play. At the start, you will have to make investments to buy energy for the charging EV owners. Soon though you may start seeing your money back in rewards.
Finished (or screwed up beyond repair)? Better reset the game. Shortcut: [Shift+r]
Balance and charge to the max to max your score.
Below we explain the game dynamics and show some of the underlying data. This data can easily be changed with data fitting a specific real-world case. One of our main design challenges for the hackathon was to use realistic data that still fits the game into an 8 by 8 matrix (where the dimensions represent time and market quantities) and is fun to play.
The supply data represents solar production in Castricum, Noord-Holland on March 9, 2018 (9am to 16pm). We got the data from the iCarus API, and downsampled and divided it until it could be represented by eight tokens.
The demand data represents two well-known peaks in energy markets in the morning and evening when people get up or come home. The peaks are shifted to improve game play.
The liquidity of our in-game market has a fixed range, meaning there is only a limited number of energy tokens. When demand and supply are equal, the in-game market has 4 tokens. This represents that there is ample opportunity to both buy and sell. When demand exceeds supply by 4, there are no tokens to buy. When supply exceeds demand by 4, there are 8 tokens on the market. The market is then full, meaning there is no possibility to sell.
The in-game market is a generic function representing pricing dynamics on real energy markets: supply and demand that change throughout the day, and prices that increase non-linearly with scarcity. The highlighted number of tokens shows the price for supply and demand being in balance. It's cheap to buy tokens to the right of it, but expensive to sell to the left of it. This market motivates players to 1) make most of their purchases when the market has the most abundant supply, and 2) to feed back energy to the grid when the market is coming up way short.
Probabilities bring an element of chance (and luck) into games. In this game, cars arrive at charging stations throughout the day with a certain probability of arrival and duration. For each new game the board is initialised using random draws from the shown probability distribution for car arrivals. The time that each car spends at a charging station is also randomised. They can remain at a charging station for up to 8 hours, but 4 hours of parking is the most common. The probabilities used here are based on data from office parking stations, but it's easy to set up the game for other situations, such as parking on public streets or at houses.