This repository presents an innovative adaptation in the methodology for the technical planning of electric energy distribution systems. The primary objective is to incorporate stochastic profiles of generation and consumption of electric energy into the planning process. Through this study, the loading on the buses was accurately calculated, addressing all relevant magnitudes associated with the problem. The methodology allows for the estimation and replacement of conductors with loading exceeding 66%.
- OPENDSS Integration: Utilizes resources provided by OPENDSS for calculating IEEE123 and MATLAB network power flow.
- Data Management: Implements effective data management techniques for handling diverse aspects of the network, including noise filtering and manipulation.
- Cost Estimation: Calculates the cost associated with repowering the entire network following simulations of efficiency flow and permutations of generation and consumption points.
For a detailed understanding of the methodology and findings, please refer to the associated article.
- GitHub Username: fernandocalenzani
- Repository Name: evolutionary-computing-minlp
To access the PESDEE_MINLP repository and contribute to its development, follow these steps:
- Clone the Repository: Use the following command to clone the repository to your local machine:
git clone https://github.com/fernandocalenzani/evolutionary-computing-minlp.git - Explore and Contribute: Delve into the repository to understand its structure and explore opportunities for contribution.
- Fork and Pull Request: If you wish to contribute, fork the repository, create a new branch, make your changes, and submit a pull request detailing your modifications.
This project is licensed under the MIT License, providing flexibility for modification and distribution.
We appreciate the support and collaboration received throughout this research endeavor. Special thanks to the authors and contributors mentioned in the associated article.