Commit dd495ff5 authored by Steffen Vogel's avatar Steffen Vogel 🎅🏼

initial data from Alberto

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This repository contains the following material:
- Python code "RBO_Service Restoration_offline_1.0" of rule-based optimization algorithm for service restoration (RBOSR).
- Python code "dsse_functions_FLISR" that includes the distribution system state estimator functions
- Excel file "Networkdata_MV_FLISR_use_case_1" that includes all the necessary grid data to run the service restoration process.
- PDF file "networkdata_MV_FLISR_use_case" that summarizes the relevant grid data.
Instructions to use the service restoration algorithm:
1- The two Python codes and the excel file must be located in the same folder.
2- Configure the excel sheet, providing information about grid topology, loads, switches and fault location (set the tripped circuit breakers).
3- If changed, set the excel file name in the RBOSR Python code (in line 1726).
4- Set the weighting factors u1, u2, u3 and u4 according to the desired restoration target in the RBOSR Python code (in line 1714). Additional information are found in the paper "Rule-Based Optimization Algorithm for Service Restoration of Active Distribution Grids", authors: A. Dognini, A. Sadu, A. Angioni, F. Ponci, A. Monti, currently under revision.
5- Set the information about the PostgreSQL database in the RBOSR Python code (in line 1679)
Considerations about the RBOSR Python code:
- The code has been developed with Python 3.6
- It needs, among others, the installation of the following libraries:
- pandas
- networkx
- psycopg2
- It needs to interface a PostgreSQL database, from/to which the data are retrieved/published.
- It generates an Excel sheets (line 1703) with information about the elapsed computation time.
Documentation about the distribution system state estimator can be found in the following website:
For additional information, refer to the following articles:
C. Muscas, S. Sulis, A. Angioni, F. Ponci, and A. Monti, “Impact of Different Uncertainty Sources on a Three-Phase State Estimator for Distribution Networks”, IEEE Transactions on Instrumentation and Measurement, vol. 63, no. 9, pp. 2200–2209, Sep. 2014.
A. Angioni, A. Kulmala, D. D. Giustina, M. Mirz, A. Mutanen, A. Ded,F. Ponci, L. Shengye, G. Massa, S. Repo, and A. Monti, “Design andimplementation of a substation automation unit”, IEEE Transactions on Power Delivery, vol. 32, no. 2, pp. 1133–1142, April 2017.
P. Jamborsalamati, A. Sadu, F. Ponci, A. Monti and M. J. Hossain,“Improvement of supply restoration in multi-spare-feeder active distri-bution grids using iec 61850”, in 2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), Dec 2017, pp. 1–5.
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