QuantomEco is a groundbreaking platform designed to optimize charging stations for electric vehicles, revolutionizing the management of energy and money costs.
The project's goal was highly ambitious and implied options of maximizing energy and cost efficiency. To achieve it, we had to implement sophisticated machine learning techniques and algorithms for data analysis.
As a result, users can access compelling and accurate insights into charging station optimization and are empowered to make informed decisions that drive sustainability and cost savings.
We covered a large part of the project, including multiple complex tasks such as project planning, software development, optimization, and administration.
During our team engagement, we managed to implement advanced optimization algorithms within the app engine, integrated different components and microservices to ensure seamless platform performance, created multi-role admin functionality, as well as ensured the platform's reliability and performance.
High energy costs during peak grid hours
prioritization to reduce reliance on peak-time electricity.
Inconsistent charging speeds due to grid fluctuations
that adjust power delivery based on grid conditions and battery needs.
Difficulties in setting optimal charging rates based on energy costs
that adjust costs based on electricity rates, demand, and time of day.
Users can easily create projects, providing all necessary information for optimization. The platform offers a streamlined overview of ongoing projects, allowing users to track optimization status and manage project details.
The system enables users to delve into project details and fine-tune parameters to optimize energy and cost efficiency. The optimization engine utilizes advanced algorithms to maximize performance and savings.
Administrators have access to a broader functional scope, including viewing and editing projects across all users. They can also manage user accounts, ensuring smooth platform operation.
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