NETI–HyOptima is a decision intelligence platform for Nigeria's energy transition—not an academic model, not a dashboard, but a computational policy environment that converts the Nigeria Energy Transition Plan into actionable, bankable investment decisions.
# NETI-HyOptima
**Nigeria Energy Transition Intelligence Platform**
NETI-HyOptima is a decision intelligence platform for Nigeria's energy transition—not an academic model, not a dashboard, but a **computational policy environment** that converts the Nigeria Energy Transition Plan into actionable, bankable investment decisions.
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## Overview
NETI-HyOptima integrates machine learning, operations research, and simulation to provide:
- **Hybrid Energy Optimization**: Optimal sizing and dispatch of solar, gas, and battery systems
- **Policy Alignment**: Constraints aligned with Nigeria's Energy Transition Plan (ETP)
- **Decision Intelligence**: Explainable optimization results for policymakers and investors
- **Scenario Analysis**: Compare locations, costs, and policy scenarios
### Core Components
| Component | Description |
|-----------|-------------|
| **HyOptima Engine** | MILP optimization for hybrid energy systems |
| **NEXUS Layer** | Agentic execution interface (Phase 2) |
| **Policy Intelligence** | ETP alignment and transition tracking |
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## Quick Start
### Installation
```bash
# Clone the repository
git clone
github.com
cd neti-hyoptima
# Create virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
```
### Basic Usage
```python
from hyoptima import (
HyOptimaModel, HyOptimaSolver,
LoadProfile, SolarProfile,
EconomicParameters, TechnicalParameters
)
# Generate synthetic profiles for a Nigerian community
load = LoadProfile.generate_synthetic(peak_demand=300, profile_type="mixed")
solar = SolarProfile.from_capacity_factor(capacity_factor=0.20)
# Configure parameters
economic = EconomicParameters(solar_capex=800, gas_fuel_cost=0.08)
technical = TechnicalParameters(target_reliability=0.99)
# Build and solve optimization model
model = HyOptimaModel(load, solar, economic, technical)
solver = HyOptimaSolver(s …