Time-Varying Sliding Mode Control Strategy for Multibus Low-Voltage Microgrids with Parallel Connected Renewable Power Sources in Islanding Mode

Dehghani, Moslem; Khooban, Mohammad Hassan; Niknam, Taher; Rafiei, S.M.R.

doi:10.1061/(asce)ey.1943-7897.0000344

Cited by 44 publications

(32 citation statements)

References 25 publications

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“…Figure 3 depicts the islanded MG by m-th distributed production units in the mode of parallel connection. Other units are working in load sharing mode and current control state [36,37]. Some units in this MG are in the voltage frequency mode.…”

Section: E Proposed Fdias Detection Schemementioning

confidence: 99%

“…The block diagram of used single-phase inverter is displayed in Figure 5 [36,37]. The LC output filter was used to reduce the harmonic components of the output voltage generated by the Pulse Width Modulation (PWM) inverter.…”

Section: A Smart Island Modelmentioning

confidence: 99%

“…and define the filter output current and the capacitor current, respectively. Based on sliding mode controller, the index of cyber-attack detection for FDIA in voltage and current parameters is defined in equation 17and (18) [36,37]. =̇−̃ , ̃= − (17) = − (18) Where S V and S I (switching surface of voltage and current) is the voltage index and current index for cyber-attack detection, respectively, which are applied as a input of Huilbert-Huang transform.…”

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confidence: 99%

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False Data Injection Attack Detection based on Hilbert-Huang Transform in AC Smart Islands

et al. 2020

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In Smart Island (SI) systems, the operators of power distribution system usually utilize actual-time measurement information as the Advanced Metering Infrastructure (AMI) to have accurate, efficient, advanced control and monitoring. SI system can be vulnerable to complicated information integrity attacks such as False Data Injection Attack (FDIA) on some equipment including sensors and controllers, which can generate misleading operational decision in the system. Today, lack of detailed research in the evaluation of power system that links the FDIAs with system stability is felt, and it will be important for both assessment of the effect of cyber-attack and taking preventive protection measures. In this regards, time-frequency-based differential approach is proposed for SI cyber-attack detection according to non-stationary signal assessment. In this paper, non-stationary signal processing approach of Hilbert-Huang Transform (HHT) is performed for the FDIA detection in several case studies. Since various critical case studies with a small FDIA in data where accurate and efficient detection can be a challenge, the simulation results confirm the efficiency of HHT approach. In this research, the configuration of the SI test case is developed in the MATLAB software with several Distributed Generations (DGs). As a result, it is found that the HHT approach is completely efficient and reliable for FDIA detection target in AC-SI. The simulation results verify that the proposed model is able to achieve accuracy rate of 93.17%.

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Section: E Proposed Fdias Detection Schemementioning

confidence: 99%

Section: A Smart Island Modelmentioning

confidence: 99%

mentioning

confidence: 99%

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False Data Injection Attack Detection based on Hilbert-Huang Transform in AC Smart Islands

et al. 2020

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“…This approach is based on the power system theory, for example, when the load increases, the frequency is reduced. To this end, the frequency and voltage droop characteristics for microgrids are expressed as (6) where and are the set point for active and reactive power, and the set point for frequency and inverter voltage magnitude, and g and h the droop curve slopes. Fig.…”

Section: A Droop Based Active and Reactive Power Flow Controlmentioning

confidence: 99%

“…The droop control technique is a conventional control scheme for controlling the parallel inverters in different applications for example DGs and microgrids [6][7][8]. This distinguished control method comprises of measuring active and reactive powers, regulating locally and proportionally the output voltage magnitude of each inverter and frequency so as to track the reference values of a system.…”

Section: Introductionmentioning

confidence: 99%

A model predictive control of parallel inverters for distributed generations in microgrids

Aghdam

Zhu

2016

2016 IEEE International Conference on Power System Technology (POWERCON)

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Nowadays, microgrid concept has been counted as an effective approach to incorporating distributed renewable resources in distribution networks. Though, the power flow control to share the loads among distributed generations is still an essential focus, specifically under peak demands. This paper focuses on a predictive power flow control method for parallel inverters of distributed generations in microgrids. The microgrid under this case study will operate in the grid-tied mode with appropriate power sharing capability among parallel distributed generations and the main grid. In comparison to the conventional voltage and frequency droop control, the proposed model predictive control approach has shown the better performance, which is verified by the Matlab/Simulink simulation.

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A Detailed Analysis of the Barriers of Using Renewable Energies and Their Roles in Sustainable Development in Iran

Ghiasi

Dehghani

Niknam

et al. 2021

Handbook of Smart Energy Systems

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Time-Varying Sliding Mode Control Strategy for Multibus Low-Voltage Microgrids with Parallel Connected Renewable Power Sources in Islanding Mode

Cited by 44 publications

References 25 publications

False Data Injection Attack Detection based on Hilbert-Huang Transform in AC Smart Islands

False Data Injection Attack Detection based on Hilbert-Huang Transform in AC Smart Islands

A model predictive control of parallel inverters for distributed generations in microgrids

A Detailed Analysis of the Barriers of Using Renewable Energies and Their Roles in Sustainable Development in Iran

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