Prabhawatt
Illuminate your savings with a Time-Of-Use Tariff Solar and Grid energy management platform
Demo
About
The problem it solves 1. Consumers with solar installations struggle to optimize electricity costs due to complex time-based pricing. 2. No automated way to balance grid vs solar power usage based on dynamic tariffs. 3. Manual scheduling of appliances during low-tariff periods is inefficient & impractical. 4. Limited visibility into real-time energy costs and potential savings. 5. Lack of smart integration between solar production, storage, and consumption patterns. **Target Impact** : Enable users to reduce electricity costs by intelligently managing their energy usage and solar resources through automated, data-driven decisions.
How it's made
Challenges we ran into **Limited to no data** Since the platform is focused on India, there is little to no information on this as solar adoption is in very early stages in India. I had to simulate a lot of information, like real-time fetching of TOU tariff based on future predictions of feather, peak, and off-peak average rates, etc. **Hallucinations By AI** AI was utilized for forecasting a lot of data produced, but AI being AI led to a lot of misclassification of data, and I had to use libraries like Instructor and Better for prompting for the ideal outputs. **Web3 integration** Being my first time working with web3 technologies, I had a tough time writing smart contracts in solidity. Also, the website is not fully based on web3, it's a mixture of web2 as it uses Firebase authentication. So it was a challenge to bridge the two technologies together.