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Moslem Dehghani
Department of Electrical and Electronic Engineering, Shiraz University of Technology, Shiraz 7155713876, Iran

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Journal article
Published: 09 August 2021 in Electronics
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Nowadays, the role of cyber-physical systems (CPSs) is of paramount importance in power system security since they are more vulnerable to different cyber-attacks. Detection of cyber-attacks on a direct current microgrid (DC-MG) has become a pivotal issue due to the increasing use of them in various electrical engineering applications, from renewable power generations to the distribution of electricity and power system of public transportation and subway electric network. In this study, a novel strategy was provided to diagnose possible false data injection attacks (FDIA) in DC-MGs to enhance the cyber-security of electrical systems. Accordingly, to diagnose cyber-attacks in DC-MG and to identify the FDIA to distributed energy resource (DER) unit, a new procedure of wavelet transform (WT) and singular value decomposition (SVD) based on deep machine learning was proposed. Additionally, this paper presents a developed selective ensemble deep learning (DL) approach using the gray wolf optimization (GWO) algorithm to identify the FDIA in DC-MG. In the first stage, in the paper, to gather sufficient data within the ordinary performance required for the training of the DL network, a DC-MG was operated and controlled with no FDIAs. In the information generation procedure, load changing was considered to have diagnosing datasets for cyber-attack and load variation schemes. The obtained simulation results were compared with the new Shallow model and Hilbert Huang Transform methods, and the results confirmed that the presented approach could more precisely and robustly identify multiple forms of FDIAs with more than 95% precision.

ACS Style

Moslem Dehghani; Taher Niknam; Mohammad Ghiasi; Navid Bayati; Mehdi Savaghebi. Cyber-Attack Detection in DC Microgrids Based on Deep Machine Learning and Wavelet Singular Values Approach. Electronics 2021, 10, 1914 .

AMA Style

Moslem Dehghani, Taher Niknam, Mohammad Ghiasi, Navid Bayati, Mehdi Savaghebi. Cyber-Attack Detection in DC Microgrids Based on Deep Machine Learning and Wavelet Singular Values Approach. Electronics. 2021; 10 (16):1914.

Chicago/Turabian Style

Moslem Dehghani; Taher Niknam; Mohammad Ghiasi; Navid Bayati; Mehdi Savaghebi. 2021. "Cyber-Attack Detection in DC Microgrids Based on Deep Machine Learning and Wavelet Singular Values Approach." Electronics 10, no. 16: 1914.

Journal article
Published: 20 June 2021 in Applied Sciences
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Cyber-physical threats as false data injection attacks (FDIAs) in islanded smart microgrids (ISMGs) are typical accretion attacks, which need urgent consideration. In this regard, this paper proposes a novel cyber-attack detection model to detect FDIAs based on singular value decomposition (SVD) and fast Fourier transform (FFT). Since new research are mostly focusing on FDIAs detection in DC systems, paying attention to AC systems attack detection is also necessary; hence, AC state estimation (SE) have been used in SI analysis and in considering renewable energy sources effect. Whenever malicious data are added into the system state vectors, vectors’ temporal and spatial datum relations might drift from usual operating conditions. In this approach, switching surface based on sliding mode controllers is dialyzed to regulate detailed FFT’s coefficients to calculate singular values. Indexes are determined according to the composition of FFT and SVD in voltage/current switching surface to distinguish the potential cyber-attack. This protection layout is presented for cyber-attack detection and is studied in various types of FDIA forms like amplitude and vector derivation of signals, which exchanged between agents such as smart sensor, control units, smart loads, etc. The prominent advantage of the proposed detection layout is to reduce the time (less than 10 milliseconds from the attack outset) in several kinds of case studies. The proposed method can detect more than 96% accuracy from 2967 sample tests. The performances of the method are carried out on AC-ISMG in MATLAB/Simulink environment.

ACS Style

Moslem Dehghani; Taher Niknam; Mohammad Ghiasi; Pierluigi Siano; Hassan Haes Alhelou; Amer Al-Hinai. Fourier Singular Values-Based False Data Injection Attack Detection in AC Smart-Grids. Applied Sciences 2021, 11, 5706 .

AMA Style

Moslem Dehghani, Taher Niknam, Mohammad Ghiasi, Pierluigi Siano, Hassan Haes Alhelou, Amer Al-Hinai. Fourier Singular Values-Based False Data Injection Attack Detection in AC Smart-Grids. Applied Sciences. 2021; 11 (12):5706.

Chicago/Turabian Style

Moslem Dehghani; Taher Niknam; Mohammad Ghiasi; Pierluigi Siano; Hassan Haes Alhelou; Amer Al-Hinai. 2021. "Fourier Singular Values-Based False Data Injection Attack Detection in AC Smart-Grids." Applied Sciences 11, no. 12: 5706.

Journal article
Published: 19 April 2021 in Applied Sciences
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Today, in various leading power utilities in developing countries, achieving optimal operational energy management and planning, taking into account the costs reduction of generation, transmission and distribution of electricity, and also reducing the emission of an environmental pollutant becomes more and more important. Optimal use of renewable energy sources (RESs) is an effective way to achieve these goals. In this regard, in this research article, an improved multi-objective differential evolutionary (IMODE) optimization algorithm is suggested and performed to dispatch electricity generations in a smart microgrid (MG) system, taking into account economy and emission as competitive issues. In this paper, a nonlinear equation of multi-objective optimization issue with various equality and inequality limitations is formulated in order to lower the total operational costs of the MG considering environmental pollution effects simultaneously. In order to address the issue of optimal operation of the MG in single-objective and multi-objective forms, an intelligent method according to the improved differential evolutionary (IDE) optimization is utilized and performed and the proposed algorithm is implemented on different problems. First, it is assumed that there is no limit to the exchange of power overhead, and secondly, the limitation of power exchange with the upstream grid is considered. In multi-objective mode, these two modes are also considered. In order to show the impact of renewable energy on the cost, in the third part of the simulations, the operation is solved with maximum participation of renewable energy sources. In the final section, the sensitivity analysis on the number of populations in this problem is performed. The obtained results of the simulation are compared to differential evolutionary (DE) and particle swarm optimization (PSO) techniques. The effectiveness of the suggested multi-operational energy management method is confirmed by applying a study case system.

ACS Style

Mohammad Ghiasi; Taher Niknam; Moslem Dehghani; Pierluigi Siano; Hassan Haes Alhelou; Amer Al-Hinai. Optimal Multi-Operation Energy Management in Smart Microgrids in the Presence of RESs Based on Multi-Objective Improved DE Algorithm: Cost-Emission Based Optimization. Applied Sciences 2021, 11, 3661 .

AMA Style

Mohammad Ghiasi, Taher Niknam, Moslem Dehghani, Pierluigi Siano, Hassan Haes Alhelou, Amer Al-Hinai. Optimal Multi-Operation Energy Management in Smart Microgrids in the Presence of RESs Based on Multi-Objective Improved DE Algorithm: Cost-Emission Based Optimization. Applied Sciences. 2021; 11 (8):3661.

Chicago/Turabian Style

Mohammad Ghiasi; Taher Niknam; Moslem Dehghani; Pierluigi Siano; Hassan Haes Alhelou; Amer Al-Hinai. 2021. "Optimal Multi-Operation Energy Management in Smart Microgrids in the Presence of RESs Based on Multi-Objective Improved DE Algorithm: Cost-Emission Based Optimization." Applied Sciences 11, no. 8: 3661.

Journal article
Published: 14 April 2021 in Sustainable Cities and Society
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This study proposes a novel secured management method for renewable microgrids considering the policies required for diagnosing cyber-attacks happening in the communication networks, usually applied in the secondary control layer of microgrids (MGs). Due to the so long stochastic and bad information entering the systems in order to make malicious attacks, their location and time data links have the ability of straying of those acting in normal conditions that attempt to have an effect on the precise voltage regulation and current dividing via influencing sensors of current and voltage. The ability to extract high-level features due to the usage of fast fourier transform (FFT) and deep learning (DL) for attack detection in cyberspace has made them to be considered as a strong technique in the face of small mutations or new attacks. These self-educated and compaction abilities of DL architectures have been considered as basic techniques for hidden scheme detection from the training datum for this reason attacks have been distinguished from benign traffic. A novel method, deep learning and FFT, for cyber-security has been used in the following paper with the aim of enabling the attacks detection in DC smart MG. The deep model and traditional machine learning way are evaluated in terms of performance, and distributed attack detection has been compared to the centralized diagnosing procedure. The tests proved that the distributed attack detection system studied can be more advanced in comparison with centralized detection systems applying FFT in the role of the input index of the DL model. This suggested distributed method enables for scalable monitoring of a MG and has the ability of detecting the existence of cyber-attacks in the communications between distributed generation agents (DGAs) controlled via a control on the basis of consensus and isolating the communication link over that the attack has been injected. Any local attack detection needs restricted information about its neighbor’s dynamics. The most important factor of the proposed detection plan can be that has the ability of detecting cyber-attacks with great precision and distinguishing cyber-attack from load changes.in addition, this has been shown that the suggested model can be further useful in the detection of the attack.

ACS Style

Qianqian Chang; Xiaolin Ma; Ming Chen; Xinwei Gao; Moslem Dehghani. A deep learning based secured energy management framework within a smart island. Sustainable Cities and Society 2021, 70, 102938 .

AMA Style

Qianqian Chang, Xiaolin Ma, Ming Chen, Xinwei Gao, Moslem Dehghani. A deep learning based secured energy management framework within a smart island. Sustainable Cities and Society. 2021; 70 ():102938.

Chicago/Turabian Style

Qianqian Chang; Xiaolin Ma; Ming Chen; Xinwei Gao; Moslem Dehghani. 2021. "A deep learning based secured energy management framework within a smart island." Sustainable Cities and Society 70, no. : 102938.

Journal article
Published: 17 March 2021 in IEEE Access
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Unexpected natural disasters or physical attacks can have various consequences, including extensive and prolonged blackouts on power systems. Energy systems should be resistant to unwanted events, and their performance is not easily affected by such conditions. The power system should also have sufficient flexibility to adapt to severe disturbances without losing its full version; it should restore itself immediately after resolving the disturbance. This critical feature of the behavior of infrastructure systems in power grids is called resilience. In this paper, the concepts related to resilience in the power system against severe disturbance are explained. The resilience and evaluation process components are introduced; then, an optimal design of resilient substations in the Noorabad city distribution grid against physical attack is presented. This research proposes an optimal solution for simultaneously allocating the feeder routing issue and substation facilities and finding the models of installed conductors and economic hardening of power lines due to unexpected physical attacks on vital urban operational infrastructure. The values of distribution networks are calculated using the grey wolf optimization (GWO) algorithm to solve the problem of designing an optimal distribution network scheme (ODNS) and optimal resilient distribution network scheme (ORDNS). Obtained results confirm the effectiveness of the proposed resiliency-cost-based optimization approach.

ACS Style

Mohammad Ghiasi; Moslem Dehghani; Taher Niknam; Hamid Reza Baghaee; Sanjeevikumar Padmanaban; Gevork B. Gharehpetian; Hamdulah Aliev. Resiliency/Cost-Based Optimal Design of Distribution Network to Maintain Power System Stability Against Physical Attacks: A Practical Study Case. IEEE Access 2021, 9, 43862 -43875.

AMA Style

Mohammad Ghiasi, Moslem Dehghani, Taher Niknam, Hamid Reza Baghaee, Sanjeevikumar Padmanaban, Gevork B. Gharehpetian, Hamdulah Aliev. Resiliency/Cost-Based Optimal Design of Distribution Network to Maintain Power System Stability Against Physical Attacks: A Practical Study Case. IEEE Access. 2021; 9 ():43862-43875.

Chicago/Turabian Style

Mohammad Ghiasi; Moslem Dehghani; Taher Niknam; Hamid Reza Baghaee; Sanjeevikumar Padmanaban; Gevork B. Gharehpetian; Hamdulah Aliev. 2021. "Resiliency/Cost-Based Optimal Design of Distribution Network to Maintain Power System Stability Against Physical Attacks: A Practical Study Case." IEEE Access 9, no. : 43862-43875.

Journal article
Published: 12 February 2021 in IEEE Access
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Due to the simultaneous development of DC-microgrids (DC-MGs) and the use of intelligent control, monitoring and operation methods, as well as their structure, these networks can be threatened by various cyber-attacks. Overall, a typical smart DC-MG includes battery, supercapacitors and power electronic devices, fuel cell, solar Photovoltaic (PV) systems, and loads such as smart homes, plug-in hybrid electrical vehicle (PHEV), smart sensors and network communication like fiber cable or wireless to send and receive data. Given these issues, cyber-attack detection and securing data exchanged in smart DC-MGs like CPS has been considered by experts as a significant subject in recent years. In this study, in order to detect false data injection attacks (FDIAs) in a MG system, Hilbert-Huang transform methodology along with blockchain-based ledger technology is used for enhancing the security in the smart DC-MGs with analyzing the voltage and current signals in smart sensors and controllers by extracting the signal details. Results of simulation on the different cases are considered with the objective of verifying the efficacy of the proposed model. The results offer that the suggested model can provide a more precise and robust detection mechanism against FDIA and improve the security of data exchanging in a smart DC-MG.

ACS Style

Mohammad Ghiasi; Moslem Dehghani; Taher Niknam; Abdollah Kavousi-Fard; Pierluigi Siano; Hassan Haes Alhelou. Cyber-Attack Detection and Cyber-Security Enhancement in Smart DC-Microgrid Based on Blockchain Technology and Hilbert Huang Transform. IEEE Access 2021, 9, 29429 -29440.

AMA Style

Mohammad Ghiasi, Moslem Dehghani, Taher Niknam, Abdollah Kavousi-Fard, Pierluigi Siano, Hassan Haes Alhelou. Cyber-Attack Detection and Cyber-Security Enhancement in Smart DC-Microgrid Based on Blockchain Technology and Hilbert Huang Transform. IEEE Access. 2021; 9 ():29429-29440.

Chicago/Turabian Style

Mohammad Ghiasi; Moslem Dehghani; Taher Niknam; Abdollah Kavousi-Fard; Pierluigi Siano; Hassan Haes Alhelou. 2021. "Cyber-Attack Detection and Cyber-Security Enhancement in Smart DC-Microgrid Based on Blockchain Technology and Hilbert Huang Transform." IEEE Access 9, no. : 29429-29440.

Journal article
Published: 13 January 2021 in IEEE Access
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Since Smart-Islands (SIs) with advanced cyber-infrastructure are incredibly vulnerable to cyber-attacks, increasing attention needs to be applied to their cyber-security. False data injection attacks (FDIAs) by manipulating measurements may cause wrong state estimation (SE) solutions or interfere with the central control system performance. There is a possibility that conventional attack detection methods do not detect many cyber-attacks; hence, system operation can interfere. Research works are more focused on detecting cyber-attacks that target DC-SE; however, due to more widely uses of AC SIs, investigation on cyber-attack detection in AC systems is more crucial. In these regards, a new mechanism to detect injection of any false data in AC-SE based on signal processing technique is proposed in this paper. Malicious data injection in the state vectors may cause deviation of their temporal and spatial data correlations from their ordinary operation. The suggested detection method is based on analyzing temporally consecutive system states via wavelet singular entropy (WSE). In this method, to adjust singular value matrices and wavelet transforms’ detailed coefficients, switching surface based on sliding mode controller are decomposed; then, by applying the stochastic process, expected entropy values are calculated. Indices are characterized based on the WSE in switching level of current and voltage for cyber-attack detection. The proposed detection method is applied to different case studies to detect cyber-attacks with various types of false data injection, such as amplitude, and vector deviation signals. The simulation results confirm the high-performance capability of the proposed FDIA detection method. This detection method’s significant characteristic is its ability in fast detection (10 ms from the attack initiation); besides, this technique can achieve an accuracy rate of over 96.5%.

ACS Style

Moslem Dehghani; Mohammad Ghiasi; Taher Niknam; Abdollah Kavousi-Fard; Elham Tajik; Sanjeevikumar Padmanaban; Hamdulah Aliev. Cyber Attack Detection Based on Wavelet Singular Entropy in AC Smart Islands: False Data Injection Attack. IEEE Access 2021, 9, 16488 -16507.

AMA Style

Moslem Dehghani, Mohammad Ghiasi, Taher Niknam, Abdollah Kavousi-Fard, Elham Tajik, Sanjeevikumar Padmanaban, Hamdulah Aliev. Cyber Attack Detection Based on Wavelet Singular Entropy in AC Smart Islands: False Data Injection Attack. IEEE Access. 2021; 9 ():16488-16507.

Chicago/Turabian Style

Moslem Dehghani; Mohammad Ghiasi; Taher Niknam; Abdollah Kavousi-Fard; Elham Tajik; Sanjeevikumar Padmanaban; Hamdulah Aliev. 2021. "Cyber Attack Detection Based on Wavelet Singular Entropy in AC Smart Islands: False Data Injection Attack." IEEE Access 9, no. : 16488-16507.

Research article
Published: 11 January 2021 in SN Applied Sciences
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In this study, an auxiliary damping controller based on a robust controller considering the active and reactive power control loops for a doubly-fed induction generator for wind farms is proposed. The presented controller is able to improve the inter-area oscillation damping. In addition, the proposed controller applies only one accessible local signal as the input; however, it can improve the inter-area oscillation damping and, consequently the system stability for the various working conditions and uncertainties. The oscillatory modes of the system are appointed using the linear analysis. Then, the controller’s parameters are determined using the robust control approaches ($${H}_{\infty }/{H}_{2})$$ H ∞ / H 2 ) with the pole placement and linear matrix inequality method. The results of the modal analysis and time-domain simulations confirm that the controller develops the inter-area oscillation damping under the various working conditions and uncertainties.

ACS Style

Ali Goodarzi; Ali Mohammad Ranjbar; Moslem Dehghani; Mina GhasemiGarpachi; Mohammad Ghiasi. Doubly fed induction generators to enhance inter-area damping based on a Robust controller: $${{\varvec{H}}}_{2}/{{\varvec{H}}}_{\infty }$$ Control. SN Applied Sciences 2021, 3, 1 -14.

AMA Style

Ali Goodarzi, Ali Mohammad Ranjbar, Moslem Dehghani, Mina GhasemiGarpachi, Mohammad Ghiasi. Doubly fed induction generators to enhance inter-area damping based on a Robust controller: $${{\varvec{H}}}_{2}/{{\varvec{H}}}_{\infty }$$ Control. SN Applied Sciences. 2021; 3 (1):1-14.

Chicago/Turabian Style

Ali Goodarzi; Ali Mohammad Ranjbar; Moslem Dehghani; Mina GhasemiGarpachi; Mohammad Ghiasi. 2021. "Doubly fed induction generators to enhance inter-area damping based on a Robust controller: $${{\varvec{H}}}_{2}/{{\varvec{H}}}_{\infty }$$ Control." SN Applied Sciences 3, no. 1: 1-14.

Journal article
Published: 23 December 2020 in Sustainability
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Using blockchain technology as one of the new methods to enhance the cyber and physical security of power systems has grown in importance over the past few years. Blockchain can also be used to improve social welfare and provide sustainable energy for consumers. In this article, the effect of distributed generation (DG) resources on the transmission power lines and consequently fixing its conjunction and reaching the optimal goals and policies of this issue to exploit these resources is investigated. In order to evaluate the system security level, a false data injection attack (FDIA) is launched on the information exchanged between independent system operation (ISO) and under-operating agents. The results are analyzed based on the cyber-attack, wherein the loss of network stability as well as economic losses to the operator would be the outcomes. It is demonstrated that cyber-attacks can cause the operation of distributed production resources to not be carried out correctly and the network conjunction will fall to a large extent; with the elimination of social welfare, the main goals and policies of an independent system operator as an upstream entity are not fulfilled. Besides, the contracts between independent system operators with distributed production resources are not properly closed. In order to stop malicious attacks, a secured policy architecture based on blockchain is developed to keep the security of the data exchanged between ISO and under-operating agents. The obtained results of the simulation confirm the effectiveness of using blockchain to enhance the social welfare for power system users. Besides, it is demonstrated that ISO can modify its polices and use the potential and benefits of distributed generation units to increase social welfare and reduce line density by concluding contracts in accordance with the production values given.

ACS Style

Moslem Dehghani; Mohammad Ghiasi; Taher Niknam; Abdollah Kavousi-Fard; Mokhtar Shasadeghi; Noradin Ghadimi; Farhad Taghizadeh-Hesary. Blockchain-Based Securing of Data Exchange in a Power Transmission System Considering Congestion Management and Social Welfare. Sustainability 2020, 13, 90 .

AMA Style

Moslem Dehghani, Mohammad Ghiasi, Taher Niknam, Abdollah Kavousi-Fard, Mokhtar Shasadeghi, Noradin Ghadimi, Farhad Taghizadeh-Hesary. Blockchain-Based Securing of Data Exchange in a Power Transmission System Considering Congestion Management and Social Welfare. Sustainability. 2020; 13 (1):90.

Chicago/Turabian Style

Moslem Dehghani; Mohammad Ghiasi; Taher Niknam; Abdollah Kavousi-Fard; Mokhtar Shasadeghi; Noradin Ghadimi; Farhad Taghizadeh-Hesary. 2020. "Blockchain-Based Securing of Data Exchange in a Power Transmission System Considering Congestion Management and Social Welfare." Sustainability 13, no. 1: 90.

Journal article
Published: 01 December 2020 in IEEE Access
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Due to the widespread use of electric motors in various industries, it is very important to have optimally designed motors in that they have high efficiency and lower negative effects on the quality of the power grid. Therefore, in this paper, the effects of winding type (wide and concentrated) on ripple torque in internal permanent magnet motor (IPMM) are investigated. In order to reduce the ripple torque and to increase the average torque, by making optimal holes in the rotor surface and using the sensitivity analysis method, the structure of the IPMM is improved. In this method, the number, dimensions and location of holes are optimized using the sensitivity analysis approach, which reduces the ripple torque of the motor. Using a concentrated winding instead of a wide winding, the toothed ripple torque is reduced by approximately 75% while maintaining the average torque value. Also, by making holes in the rotor surface and optimizing them using the finite element technique and sensitivity analysis, it is demonstrated that the amount of ripple torque by 20%. In the proposed approach, it is proved that in the concentrated winding, in addition to reducing the spatial harmonics, the average amount of torque can also be improved. Obtained results of the simulation confirm the effectiveness of the proposed method.

ACS Style

Alireza Ramezani; Mohammad Ghiasi; Moslem Dehghani; Taher Niknam; Pierluigi Siano; Hassan Haes Alhelou. Reduction of Ripple Toothed Torque in the Internal Permanent Magnet Electric Motor by Creating Optimal Combination of Holes in the Rotor Surface Considering Harmonic Effects. IEEE Access 2020, 8, 215107 -215124.

AMA Style

Alireza Ramezani, Mohammad Ghiasi, Moslem Dehghani, Taher Niknam, Pierluigi Siano, Hassan Haes Alhelou. Reduction of Ripple Toothed Torque in the Internal Permanent Magnet Electric Motor by Creating Optimal Combination of Holes in the Rotor Surface Considering Harmonic Effects. IEEE Access. 2020; 8 (99):215107-215124.

Chicago/Turabian Style

Alireza Ramezani; Mohammad Ghiasi; Moslem Dehghani; Taher Niknam; Pierluigi Siano; Hassan Haes Alhelou. 2020. "Reduction of Ripple Toothed Torque in the Internal Permanent Magnet Electric Motor by Creating Optimal Combination of Holes in the Rotor Surface Considering Harmonic Effects." IEEE Access 8, no. 99: 215107-215124.

Journal article
Published: 01 January 2018 in International Journal of Computer Applications in Technology
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Generally, the power of a solar photovoltaic panel is strongly related to climate conditions. Hence, a grid-connected system should have a good response over variations in the solar radiation and temperature. Consequently, this work describes the application of the control based general type-II fuzzy system for the grid-connected solar power generation system. In this study, general type-2 fuzzy logic sets (GT2FLS) and the Modified Backtracking Search Algorithm (MBSA) techniques for the adaptive tuning of the most popular existing proportional-integral (PI) controller is integrated in order to tackle these uncertainties. The achieved results are compared with conventional PI controller and Optimal Fuzzy PI (OFPI) controller results, which are the most recent researches into in the present issue to evaluate the proficiency of the proposed controller. Finally, the extensive studies and hardware-in-the-loop simulations are presented to show the effectiveness of the proposed controller.

ACS Style

Tomislav Dragičević; Moslem Dehghani; Mohammad Hassan Khooban. Hardware-in-the-loop simulation for the testing of smart control in grid-connected solar power generation systems. International Journal of Computer Applications in Technology 2018, 58, 116 .

AMA Style

Tomislav Dragičević, Moslem Dehghani, Mohammad Hassan Khooban. Hardware-in-the-loop simulation for the testing of smart control in grid-connected solar power generation systems. International Journal of Computer Applications in Technology. 2018; 58 (2):116.

Chicago/Turabian Style

Tomislav Dragičević; Moslem Dehghani; Mohammad Hassan Khooban. 2018. "Hardware-in-the-loop simulation for the testing of smart control in grid-connected solar power generation systems." International Journal of Computer Applications in Technology 58, no. 2: 116.

Journal article
Published: 01 January 2018 in International Journal of Computer Applications in Technology
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Generally, the power of a solar photovoltaic panel is strongly related to climate conditions. Hence, a grid-connected system should have a good response over variations in the solar radiation and temperature. Consequently, this work describes the application of the control based general type-II fuzzy system for the grid-connected solar power generation system. In this study, general type-2 fuzzy logic sets (GT2FLS) and the Modified Backtracking Search Algorithm (MBSA) techniques for the adaptive tuning of the most popular existing proportional-integral (PI) controller is integrated in order to tackle these uncertainties. The achieved results are compared with conventional PI controller and Optimal Fuzzy PI (OFPI) controller results, which are the most recent researches into in the present issue to evaluate the proficiency of the proposed controller. Finally, the extensive studies and hardware-in-the-loop simulations are presented to show the effectiveness of the proposed controller.

ACS Style

Mohammad Hassan Khooban; Moslem Dehghani; Tomislav Dragičević. Hardware-in-the-loop simulation for the testing of smart control in grid-connected solar power generation systems. International Journal of Computer Applications in Technology 2018, 58, 116 .

AMA Style

Mohammad Hassan Khooban, Moslem Dehghani, Tomislav Dragičević. Hardware-in-the-loop simulation for the testing of smart control in grid-connected solar power generation systems. International Journal of Computer Applications in Technology. 2018; 58 (2):116.

Chicago/Turabian Style

Mohammad Hassan Khooban; Moslem Dehghani; Tomislav Dragičević. 2018. "Hardware-in-the-loop simulation for the testing of smart control in grid-connected solar power generation systems." International Journal of Computer Applications in Technology 58, no. 2: 116.

Journal article
Published: 01 August 2017 in Journal of Energy Engineering
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ACS Style

Moslem Dehghani; Mohammad Hassan Khooban; Taher Niknam; S. M. R. Rafiei. Erratum for “Time-Varying Sliding Mode Control Strategy for Multibus Low-Voltage Microgrids with Parallel Connected Renewable Power Sources in Islanding Mode” by Moslem Dehghani, Mohammad Hassan Khooban, Taher Niknam, and S. M. R. Rafiei. Journal of Energy Engineering 2017, 143, 08217001 .

AMA Style

Moslem Dehghani, Mohammad Hassan Khooban, Taher Niknam, S. M. R. Rafiei. Erratum for “Time-Varying Sliding Mode Control Strategy for Multibus Low-Voltage Microgrids with Parallel Connected Renewable Power Sources in Islanding Mode” by Moslem Dehghani, Mohammad Hassan Khooban, Taher Niknam, and S. M. R. Rafiei. Journal of Energy Engineering. 2017; 143 (4):08217001.

Chicago/Turabian Style

Moslem Dehghani; Mohammad Hassan Khooban; Taher Niknam; S. M. R. Rafiei. 2017. "Erratum for “Time-Varying Sliding Mode Control Strategy for Multibus Low-Voltage Microgrids with Parallel Connected Renewable Power Sources in Islanding Mode” by Moslem Dehghani, Mohammad Hassan Khooban, Taher Niknam, and S. M. R. Rafiei." Journal of Energy Engineering 143, no. 4: 08217001.

Journal article
Published: 01 December 2016 in Journal of Energy Engineering
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In islanding microgrids (MGs), distributed generation units are in charge of controlling voltage, frequency, and current of the grid on their own without any assistance from the main grid. Therefore, it is of utmost importance to select and design a controller that is robust against disturbances and load variations. In this study, a new sliding mode controller with a rotating reference voltage algorithm is proposed that improves the load sharing between distributed generators (DGs) in an islanded mode MG. In the proposed algorithm, in order to improve the performance and convergence rate of the controller, the amplitude of the reference voltage signal of the controller is adaptively modified. As a case study, the proposed strategy is studied based on the assumption that there are three DGs in the grid. One of the DGs is in charge of regulating voltage and frequency based on a reference signal, and the two other DGs are responsible for load sharing and loads the current control mode. The MG under study consists of three low-voltage distributed generation units operating in parallel mode. In order to have a realistic case study, it is assumed that the MG consists of different types of loads such as balanced/unbalanced resistive, inductive, and nonlinear loads. The extensive simulations are applied to indicate that the proposed framework is able to provide more desirable total harmonic distortion (THD), lower steady-state error, and faster response compared with classic sliding mode controllers.

ACS Style

Moslem Dehghani; Mohammad Hassan Khooban; Taher Niknam; Seyed Mohammadreza Rafiei. Time-Varying Sliding Mode Control Strategy for Multibus Low-Voltage Microgrids with Parallel Connected Renewable Power Sources in Islanding Mode. Journal of Energy Engineering 2016, 142, 05016002 .

AMA Style

Moslem Dehghani, Mohammad Hassan Khooban, Taher Niknam, Seyed Mohammadreza Rafiei. Time-Varying Sliding Mode Control Strategy for Multibus Low-Voltage Microgrids with Parallel Connected Renewable Power Sources in Islanding Mode. Journal of Energy Engineering. 2016; 142 (4):05016002.

Chicago/Turabian Style

Moslem Dehghani; Mohammad Hassan Khooban; Taher Niknam; Seyed Mohammadreza Rafiei. 2016. "Time-Varying Sliding Mode Control Strategy for Multibus Low-Voltage Microgrids with Parallel Connected Renewable Power Sources in Islanding Mode." Journal of Energy Engineering 142, no. 4: 05016002.