Smart management system for improving the reliability and availability of substations in smart grid with distributed generation

Refaat, Shady S.; Mohamed, Amira

doi:10.1049/joe.2018.8215

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…Therefore, the smart grid is used to solve the issues as mentioned above, then the SG enables manage and distributed power flow and information by two-way direction by using Information and communications technologies (ICT) [2]. Smart grid has flexibility via distributed generation, reliability via self-healing, and efficiency through load balancing and use intelligent devices [3]. The SG can be combination of renewable energy resources such as solar cell photovoltaic and wind and have many major components are household appliances, renewable energy resources, smart meter and devices, and utility centers [4].…”

Section: Introductionmentioning

confidence: 99%

Identification scheme of false data injection attack based on deep learning algorithms for smart grids

Merza

Hussein

Ali

2023

IJEECS

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This paper presents the artificial intelligence (AI) techniques based on the deep learning algorithms to diagnose false data injection (FDI) attacks to smart grids with the measurement data in real-time. The power and data flow between end-user consumers and all components of the advanced metering infrastructure (AMI) and supervisory control and data acquisition (SCADA) system in the SG is bidirectional flow by advanced communication networks. For all the advantages of the SG come with, they remain at risk to a series of many potential threats and ongoing attacks. The conditional-deep-belief-network (CDBN) architecture is employed to un-observable FDI attacks which pass the state-vector-estimator (SVE) mechanisms. The IEEE 118 bus, and IEEE 300 bus power system have been used to evaluate our detection scheme. Finally, the suggested CDBN scheme is compared with other detection such as artificial neural network (ANN) and support vector machine (SVM). It is observed that the simulation result shows that suggested detection methods can attain a high accuracy of unobservable FDI attacks.

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Section: Introductionmentioning

confidence: 99%

Identification scheme of false data injection attack based on deep learning algorithms for smart grids

Merza

Hussein

Ali

2023

IJEECS

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“…With the emergence of environmental problems and the consumption of non-renewable energy, the application of renewable energy such as wind and solar energy is more and more important [4]. Shady et al highlight in [5] that the establishment of SGs is very important to improve the efficiency and security of energy supply. SGs would help in reducing energy consumption during peak load, and in reducing emissions of pollutants.…”

Section: Introductionmentioning

confidence: 99%

A Novel Sparse Attack Vector Construction Method for False Data Injection in Smart Grids

Xia

Fei

et al. 2020

Energies

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To improve the security of smart grids (SGs) by finding the system vulnerability, this paper investigates the sparse attack vectors’ construction method for malicious false data injection attack (FDIA). The drawbacks of the existing attack vector construction methods include avoiding discussing the feasible region and validity of the attack vector. For the above drawbacks, this paper has three main contributions: (1) To construct the appropriate attack evading bad data detection (BDD), the feasible region of the attack vector is proved by projection transformation theory. The acquisition of the feasible region can help the defender to formulate the defense strategy; (2) an effective attack is proposed and the constraint of effectiveness is obtained using norm theory; (3) the domain of the state variations caused by the attack vector in the feasible region is calculated, while the singular value decomposition method is adopted. Finally, an attack vector is constructed based on l 0 -norm using OMP algorithms in the feasible domain. Simulation results confirm the feasibility and effectiveness of the proposed technique.

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Analysis of reactive power loadability and management of flexible alternating current transmission system devices in a distribution grid using whale optimization algorithm

Baby

Jayakumar

Mathew

et al. 2022

IET Renewable Power Gen

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The optimal injection of reactive power to minimize power loss and manage voltage profiles is a difficult task that must be addressed and managed effectively for the power system's reliability. The distribution network indices like voltage stability, loss minimization, and power quality enhancement can be improved by the effective management of reactive power regulation. Aside from its interaction with reactive power management, the best location and sizing in a cost‐effective strategy have an impact on overall performance. As a broadly accepted swarm intelligence method in various engineering fields due to its simple assembly, less entails operator constraints, wild convergence speed, and better harmonizing ability between exploration and exploitation faces, the Whale Optimization Algorithm (WOA) is used in conjunction with a Flexible Alternating Current Transmission System (FACTS) device in this paper to manage reactive power effectively. The WOA was implemented and compared with Differential Evolution (DE), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) at 100%, 150%, and 200% load in the IEEE 30 test system. The results reveal that the suggested WOA produces a greater impact on cost management, power loss, and reactive power balance than any previous evolutionary algorithm.

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Smart management system for improving the reliability and availability of substations in smart grid with distributed generation

Cited by 4 publications

References 10 publications

Identification scheme of false data injection attack based on deep learning algorithms for smart grids

Identification scheme of false data injection attack based on deep learning algorithms for smart grids

A Novel Sparse Attack Vector Construction Method for False Data Injection in Smart Grids

Analysis of reactive power loadability and management of flexible alternating current transmission system devices in a distribution grid using whale optimization algorithm

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