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صفحه اصلی
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هشتمین کنفرانس بین المللی فناوری و مدیریت انرژی
Assessment of Cyber Security in the Renewable Electricity Market Considering System Reliability Using Machine Learning
نویسندگان :
Daryoush Tavangar Rizi
1
Mohammad Hassan Nazari
2
Maryam Fani
3
Seyed Hossein Hosseinian
4
1- Amirkabir University of Technology
2- Amirkabir University of Technology
3- Amirkabir University of Technology
4- Amirkabir University of Technology
کلمات کلیدی :
Cyber security،reliability،data science،electricity market،machine learning
چکیده :
Abstract—The role of cyber security in facing risks and damages is an essential task. The aim of this research is first to the impact of a sabotage model with possible cyber-attacks on the electricity market, which is the unavailability of the production unit or the transmission line. This network is a three-bus system consisting of three wind power generation units. This is achieved by running several scenarios in the system. The operator intends to have the minimum cost after attacking the system. The CPLEX solver solves the mixed integer linear programming (MILP) model. Also, the data obtained from the output of the GAMS software is used as the input data of the Python software to use data science such as histogram chart analysis and machine learning algorithms for proper prediction and isolation in different attack situations. As a result, the peak load point shifts after the attack, and also between the used machine learning algorithms, the two-layer neural network has significant accuracy for the presented model. The results of this research show that by using this machine learning algorithm, the system's security level has improved in the face of these damages.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 44.5.0