Project Structure

The codebase is organized into different modules, each focusing on a specific aspect of the reliability evaluation process. Below is an overview of the project structure and its components:

1. Data Preparation Purpose: Load and preprocess the input data for the system, including information about buses, lines, generators, and loads. Files: data_processing.py: Handles data import from CSV files and prepares it for simulation. DADOS/: Contains input files such as: D_GEN.csv: Generator characteristics (capacity, failure rates, repair times). D_LIN.csv: Transmission line data (capacity, failure rates, reactivity, etc.). D_LOAD.csv: Load data (location, magnitude).

2. Sequential Monte Carlo Simulation (SMC) Purpose: Simulate the system operation over time using random sampling to account for the stochastic behavior of components. Includes the chronological order of events to assess reliability indices. Key Features: Time-dependent failure and repair modeling. Assessment of energy supply under different operational scenarios. Files: monte_carlo_Seq.py: Implements the SMC methodology, simulating failures, repairs, and demand fulfillment over time.

3. Non-Sequential Monte Carlo Simulation (SMC NC) Purpose: Evaluate reliability without chronological modeling, focusing on probabilistic combinations of component states (up/down). Key Features: Simplifies computation by removing time-dependency. Useful for quick reliability estimates. Files: monte_carlo_NS.py: Implements the SMC NC methodology using random sampling of states.

4. State Enumeration Method Purpose: Enumerate all possible system states (combinations of operational and failed components) to calculate exact reliability indices. Key Features: Computationally exhaustive but highly accurate for small systems. Serves as a benchmark for comparing the Monte Carlo results. Files: states_enumeration.py: Implements state enumeration to calculate reliability indices.

5. Utility Functions Purpose: Shared utilities used across different methodologies. Files: calcula_fpo.py: Models optimal power flow equations and constraints using pyomo

6. How to Run the Project Prerequisites Install Python 3.8+. Install dependencies from the requirements.txt file: pip install -r requirements.txt 'GLPK' solver instalation: video reference https://www.youtube.com/watch?v=GaSEZ0kzOkA