Power System Load Flow Analysis Using Python

Overview

This project demonstrates the implementation of power system load flow analysis using Python for steady-state power system studies.

The repository includes:

• Y-Bus matrix construction
• Gauss-Seidel load flow analysis
• Newton-Raphson load flow analysis
• Power flow calculations
• Transmission loss estimation
• Automated testing with PyTest
• Engineering report generation
• Data visualization
• Jupyter Notebook analysis workflow

The project is designed as a practical electrical engineering portfolio showcasing numerical methods, power system modeling, and Python-based engineering computation.

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System Diagram

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Project Workflow

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Methodology

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Engineering Concepts Covered

Load Flow Analysis

Load flow analysis determines the operating condition of an electrical power system under steady-state conditions.

Key outputs:

• Bus Voltage Magnitudes
• Voltage Angles
• Active Power Flow
• Reactive Power Flow
• Transmission Losses

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Bus Classification

Slack Bus

Reference bus with specified:

• Voltage Magnitude
• Voltage Angle

PQ Bus

Specified:

• Active Power (P)
• Reactive Power (Q)

Calculated:

• Voltage Magnitude
• Voltage Angle

PV Bus

Specified:

• Active Power (P)
• Voltage Magnitude (V)

Calculated:

• Reactive Power (Q)
• Voltage Angle

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Y-Bus Matrix

The Bus Admittance Matrix (Y-Bus) represents the electrical network connectivity and admittance characteristics.

General form:

[Ybus][V] = [I]

The Y-Bus matrix serves as the foundation for load flow calculations.

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Numerical Methods

Gauss-Seidel Method

Advantages:

• Simple implementation
• Low memory requirement
• Suitable for educational studies

Limitations:

• Slow convergence
• Sensitive to initial conditions

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Newton-Raphson Method

Advantages:

• Fast convergence
• High numerical accuracy
• Industry-standard solution technique

Limitations:

• More computational complexity
• Jacobian matrix construction required

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Repository Structure

power-system-load-flow-analysis/

├── data/
│   ├── sample_bus_data.csv
│   ├── sample_line_data.csv
│   └── ieee_5bus_system.csv
│
├── src/
│   ├── ybus_builder.py
│   ├── gauss_seidel.py
│   ├── newton_raphson.py
│   ├── power_flow.py
│   ├── transmission_losses.py
│   └── load_flow_solver.py
│
├── notebooks/
│   ├── 01_data_exploration.ipynb
│   ├── 02_ybus_construction.ipynb
│   ├── 03_gauss_seidel_analysis.ipynb
│   ├── 04_newton_raphson_analysis.ipynb
│   └── 05_result_comparison.ipynb
│
├── visualizations/
│   ├── voltage_profile.png
│   ├── transmission_losses.png
│   ├── convergence_curve.png
│   ├── bus_angle_profile.png
│   └── power_flow_results.png
│
├── reports/
│   ├── load_flow_report.pdf
│   └── generate_report.py
│
├── tests/
│   ├── test_ybus_builder.py
│   ├── test_gauss_seidel.py
│   ├── test_newton_raphson.py
│   ├── test_power_flow.py
│   └── test_transmission_losses.py
│
├── assets/
│   ├── project_workflow_and_system_methodology_diagrams.png
│   
│ 
│
├── examples/
│   ├── run_gauss_seidel.py
│   └── run_newton_raphson.py
│
├── requirements.txt
├── .gitignore
├── LICENSE
└── README.md

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Dataset Description

sample_bus_data.csv

Contains bus information:

• Bus Number
• Bus Type
• Voltage Magnitude
• Active Power
• Reactive Power

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sample_line_data.csv

Contains transmission line parameters:

• From Bus
• To Bus
• Resistance (p.u.)
• Reactance (p.u.)
• Line Charging Susceptance (p.u.)

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ieee_5bus_system.csv

Sample IEEE-inspired 5-Bus system used for load flow studies.

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Visualizations

Voltage Profile

Shows bus voltage magnitudes throughout the system.

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Transmission Losses

Displays estimated transmission losses.

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Convergence Curve

Illustrates convergence behavior of numerical methods.

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Bus Angle Profile

Displays voltage angle distribution.

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Power Flow Results

Summarizes calculated power flow values.

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Example Results

Bus Voltage Magnitudes

Bus 1 : 1.050 p.u.
Bus 2 : 1.020 p.u.
Bus 3 : 1.010 p.u.
Bus 4 : 0.990 p.u.
Bus 5 : 0.975 p.u.

Total Transmission Loss

2.13 MW

Newton-Raphson Convergence

Converged in 4 iterations

Gauss-Seidel Convergence

Converged in 18 iterations

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Installation

Clone repository:

git clone https://github.com/koswadi/power-system-load-flow-analysis.git

Move to project directory:

cd power-system-load-flow-analysis

Create virtual environment:

python -m venv venv

Activate virtual environment:

Windows

venv\Scripts\activate

Linux / macOS

source venv/bin/activate

Install dependencies:

pip install -r requirements.txt

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Running Examples

Gauss-Seidel

python examples/run_gauss_seidel.py

Newton-Raphson

python examples/run_newton_raphson.py

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Running Tests

Run all tests:

pytest tests/

Expected output:

5 passed

Covered Components:

• Y-Bus Builder
• Gauss-Seidel Solver
• Newton-Raphson Solver
• Power Flow Calculation
• Transmission Loss Estimation

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Engineering Report Generation

Generate report:

python reports/generate_report.py

Output:

reports/load_flow_report.pdf

Report Contents:

• Load Flow Results
• Bus Voltages
• Power Flow Summary
• Transmission Losses
• Method Comparison
• Engineering Conclusions

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Educational Objectives

This project demonstrates:

• Power System Analysis
• Numerical Methods
• Scientific Computing with Python
• Engineering Data Visualization
• Automated Testing
• Technical Report Generation
• Reproducible Engineering Workflows

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Future Improvements

Planned enhancements include:

• IEEE 14-Bus System
• IEEE 30-Bus System
• Fast Decoupled Load Flow
• Optimal Power Flow (OPF)
• Contingency Analysis
• Interactive Dashboard
• Power System State Estimation
• Renewable Energy Integration Studies

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Author

Agoes Koswadi

Electrical Engineering Portfolio Project

Focused on:

• Power Systems
• Electrical Engineering
• Python Programming
• Engineering Computation
• AI Evaluation and Data Annotation

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License

This project is distributed under the MIT License.