Inspiration
We were inspired by Challenge #1, and the belief that customer's decisions and priorities will need to be effectively accounted for in order to scale the adoption of assets like EVs and other flexible electrical appliances. We want to provide an interface that is easy for the user and creates less friction in setting up smart / automated schedules for flexible electrical loads.
What it does
Grove helps customers set up new flexible load devices easily, and allows them to track their operation and performance in terms they can understand.
Grove is made up of a quick and simple configuration wizard, and a straightforward dashboard which together allow for a customer to set up and utilize flexible load products effortlessly. What makes Grove stand out is its ability to incorporate customer priorities in the decision making process for scheduling the operation of appliances. Rather than simply assuming that the user wants the lowest cost, or forcing the user to adapt to a schedule set around grid services, Grove lets the user dictate what their priorities are to align their experience with the product to their own personal preferences.
After configuration, Grove makes it easy to check in on the performance of these products. Customers can quickly see what the planned operation times for the upcoming day are, and the expected savings and emissions mitigations associated with their optimized operation schedule. They can check back to confirm the results of the previous day's operation, and they can even look further back n
Emissions can be complicated to understand. Grove converts the technical units associated with marginal emissions intensity of energy produced by the electrical grid and presents them with the concept of "trees". A customers "trees" indicate how many mature trees, living in a typical forest, would soak up the same amount of carbon dioxide over the course of a day as were offset that day by the flexible operation of the customer's electrified product. Each day the customer can see their "trees" increase or decrease as their choices help reduce emissions by scheduling operation at times when the grid is producing cleaner energy.
As uptake of flexible electrical products increases, customers can see their own contribution in the context of the "forest" created by the combined impact of all users in their community.
This simple tool can be integrated into manufacturers' applications so that the set up process is streamlined and customers do not need to download extra applications to ensure they get a good experience with their electrified assets.
How we built it
We built a mobile app front-end using the Ionic hybrid framework, and connected it to a Flask backend API. Our backend makes use of integrations with Genability, SVCE / Utility API customer data, and WattTime's SGIP GHG Signal API in order to analyze both the cost as well as the forecasted emission intensity of grid electricity and optimize the schedule of assets to align with the priorities of the customer.
Challenges we ran into
So many ideas, so little time!
Accomplishments that I'm proud of
What I learned
What's next for GROVE
Built With
- flask
- genability
- ionic
- sgipsignal
- utilityapi

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