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GridSmart Energy

Decentralized Energy Trading & Smart Grid Management

GridSmart Energy preview

Grid Overload & Inefficient Energy Distribution

Traditional power grids face critical transformer overload during peak hours, leading to blackouts and energy waste. Consumers lack visibility into grid status and have no mechanisms to participate in load balancing or trade excess energy with neighbors.

1

Transformer Overload Risk - Power transformers frequently exceed 85% capacity during peak hours (6-9 AM, 6-9 PM), risking blackouts and infrastructure damage

2

Wasted Renewable Energy - Households with solar panels cannot easily sell excess energy generation to neighbors, leading to wasted clean energy

3

No Consumer Incentives - Users have no financial motivation to reduce consumption during critical grid stress periods

4

Lack of Predictive Intelligence - Grid operators and consumers lack AI-powered forecasting to anticipate and prevent overload events

BlockDAG-Powered Smart Grid Ecosystem

GridSmartEnergy combines real-time blockchain grid monitoring, P2P energy marketplace, and AI predictions to create a transparent, incentivized ecosystem where consumers actively participate in grid stability while earning BDAG tokens.

1

Real-Time Transformer Monitoring - Live grid load tracking connected directly to BlockDAG blockchain, displaying current capacity (0-100%) with critical/warning/normal status indicators

2

Transparent Outage Tracking - Immutable blockchain records of every power outage by location, creating accountability and preventing discriminatory load shedding practices through verifiable data

3

P2P Energy Trading Marketplace - Decentralized marketplace enabling neighbors to trade energy within their transformer zone, with dynamic pricing (R10-15/kWh) and location-based matching. Enabled by Raspberry Pi-based energy monitors (~R6,700 per unit) installed at each household

4

Blockchain Incentive Rewards - Users commit to energy reduction during peak hours and earn BDAG tokens (2.5 BDAG/kWh base rate, 1.5x multiplier during peaks) recorded immutably on-chain

5

AI Predictive Intelligence - XGBoost machine learning forecasts grid overload events 1-48 hours in advance with 99.2% accuracy, enabling proactive load balancing and alerting users to upcoming incentive opportunities

6

Integrated BDAG Wallet - Built-in cryptocurrency wallet for managing earnings, viewing transaction history, tracking energy savings (kWh), and monitoring blockchain connection status

Key Features

More Features

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Impact & Achievements

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2025 BlockDAG Hackathon

Built With

Frontend

React Native
React
Expo
TypeScript
React Navigation
Reanimated

Backend

BlockDAG
Ethers.js
Smart Contracts
XGBoost
Python

Infrastructure

Raspberry Pi

Tools

Babel
Expo CLI

Experience GridSmart Energy

Explore the project and see it in action