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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.
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 StyleMoslem 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 StyleMoslem 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.
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.
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 StyleMoslem 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 StyleMoslem 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.
A group of distributed generators (DGs) systems including wind, solar, diesel, energy storage (ES), etc., that are under a central management and control is often considered as virtual power plant (VPP) concept. One of the components of a VPP is ES, whose presence and participation in the electricity market can create business opportunities. In this paper, a new mathematical-based strategy for identifying different types of trading situations considering VPPs effects is proposed in the electricity market to obtain maximum benefit. Also VPP trading between energy and ancillary services is considered and analysed. The presented model considers all limitations of the VPP including network constrains and the structure of VPPs. The optimal management of distributed energy units determines the state of charge (SoC) or discharge of ES resources and the amount of intermittent load for the day ahead electricity market. By implementing the proposed model on the microgrid (MG), two different modes of trading for VPPs are examined and the changes of efficiency related to energy storages are analysed. In order to solve the issue of optimal operation strategy, an intelligent approach based on differential evolution (DE) algorithm is used. The obtained simulation results of both modes are compared with those VPP without energy storage. The results show notable profits in both modes.
Bo Li; Mohammad Ghiasi. A New Strategy for Economic Virtual Power Plant Utilization in Electricity Market Considering Energy Storage Effects and Ancillary Services. Journal of Electrical Engineering & Technology 2021, 1 -12.
AMA StyleBo Li, Mohammad Ghiasi. A New Strategy for Economic Virtual Power Plant Utilization in Electricity Market Considering Energy Storage Effects and Ancillary Services. Journal of Electrical Engineering & Technology. 2021; ():1-12.
Chicago/Turabian StyleBo Li; Mohammad Ghiasi. 2021. "A New Strategy for Economic Virtual Power Plant Utilization in Electricity Market Considering Energy Storage Effects and Ancillary Services." Journal of Electrical Engineering & Technology , no. : 1-12.
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.
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 StyleMohammad 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 StyleMohammad 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.
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.
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 StyleMohammad 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 StyleMohammad 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.
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.
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 StyleMohammad 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 StyleMohammad 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.
Today, due to the several benefits of using the subway as a clean transportation system and also its expansion in many cities around the world, electrification to urban and suburban railway systems is experiencing a very important development procedure. Optimal power supply and management of energy that is economically viable is one of the important issues in the design of such systems. In this paper, in order to provide an optimal energy management and to determine the location of rectifier substations (RSs), and also to calculate power supply capacity (PSC) of the traction units, an optimal design and simulation of a DC railway traction power supply system (RTPSS) in urban area is proposed. In this regard, first, the structure of power system of RSs used in urban area is presented and analyzed in detail. Then, considering the importance of the standard criteria in designing the dynamics of a city’s RTPSS, an equivalent circuit for the desired network is provided. After defining the governing equations of the network and using the dogleg optimization method, to ensure convergence, the speed of solving equations is improved. In this study, in order to verify the performance of the presented method, the cost-based convergence characteristic curve for Dogleg optimization method is compared to the particle swarm optimization (PSO) approach. In order to confirm the robustness, applicability, and superiority of the proposed approach for optimal design and energy management in a city railway power system, the presented method is applied to a real study case. The obtained results through the simulation approve the effectiveness of using the Dogleg optimization method in power consumption by approximately 255 kWh in reducing energy compared to the practical energy consumption for one train during the trip in normal condition.
Xiaojuan Hu; Shan Zhou; Tie Chen; Mohammad Ghiasi. Optimal energy management of a DC power traction system in an urban electric railway network with dogleg method. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 2021, 1 -23.
AMA StyleXiaojuan Hu, Shan Zhou, Tie Chen, Mohammad Ghiasi. Optimal energy management of a DC power traction system in an urban electric railway network with dogleg method. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. 2021; ():1-23.
Chicago/Turabian StyleXiaojuan Hu; Shan Zhou; Tie Chen; Mohammad Ghiasi. 2021. "Optimal energy management of a DC power traction system in an urban electric railway network with dogleg method." Energy Sources, Part A: Recovery, Utilization, and Environmental Effects , no. : 1-23.
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%.
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 StyleMoslem 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 StyleMoslem 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.
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.
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 StyleMoslem 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 StyleMoslem 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.
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.
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 StyleAlireza 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 StyleAlireza 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.
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%.
Moslem Dehghani; Mohammad Ghiasi; Taher Niknam; Abdollah Kavousi-Fard; Sanjeevikumar Padmanaban. False Data Injection Attack Detection based on Hilbert-Huang Transform in AC Smart Islands. IEEE Access 2020, 8, 179002 -179017.
AMA StyleMoslem Dehghani, Mohammad Ghiasi, Taher Niknam, Abdollah Kavousi-Fard, Sanjeevikumar Padmanaban. False Data Injection Attack Detection based on Hilbert-Huang Transform in AC Smart Islands. IEEE Access. 2020; 8 (99):179002-179017.
Chicago/Turabian StyleMoslem Dehghani; Mohammad Ghiasi; Taher Niknam; Abdollah Kavousi-Fard; Sanjeevikumar Padmanaban. 2020. "False Data Injection Attack Detection based on Hilbert-Huang Transform in AC Smart Islands." IEEE Access 8, no. 99: 179002-179017.
Due to the growing use of Renewable Energy Sources (RES) in many countries, the need for an accurate and detailed analysis from the technical and economic view point seems to be necessary. Power Quality (PQ) can also be another considerable matter that needs to be carefully evaluated. In this regards, in this article, an analytical and detailed approach is presented to evaluate the technical and economic performance of the strategy for PQ changes. In addition, an optimization-based PQ change strategy is presented to provide a distinct PQ in integrated grids with renewable generations. The proposed strategy is based on the assessment of financial losses due to changes in the quality of power and the cost estimation of various reduction approaches and repayment solutions. This approach presents various customer requirements and various levels of PQ in the power grid. In order to evaluate the performance of the proposed method, the effectiveness of the presented model has been utilised in an actual case study, and the results have been obtained and analysed. The results of the simulation provide both technical and financial advantages to obtain optimal change strategy.
Mohammad Ghiasi; Sheyda Esmaeilnamazi; Ramin Ghiasi; Mohammadreza Fathi. Role of Renewable Energy Sources in Evaluating Technical and Economic Efficiency of Power Quality. Technology and Economics of Smart Grids and Sustainable Energy 2019, 5, 1 .
AMA StyleMohammad Ghiasi, Sheyda Esmaeilnamazi, Ramin Ghiasi, Mohammadreza Fathi. Role of Renewable Energy Sources in Evaluating Technical and Economic Efficiency of Power Quality. Technology and Economics of Smart Grids and Sustainable Energy. 2019; 5 (1):1.
Chicago/Turabian StyleMohammad Ghiasi; Sheyda Esmaeilnamazi; Ramin Ghiasi; Mohammadreza Fathi. 2019. "Role of Renewable Energy Sources in Evaluating Technical and Economic Efficiency of Power Quality." Technology and Economics of Smart Grids and Sustainable Energy 5, no. 1: 1.
: Distributed Generations (DGs) have a productive capacity of tens of kilowatts to several megawatts, which are used to produce electrical energy at close proximity to consumers, which of the types of DGs can be named solar cells and Photovoltaics (PVs), fuel cells, micro turbines, wind power plants, and etc. If such kinds of power plants are connected to the network in optimal places, they will have several positive effects on the system, such as reducing network losses, improving the voltage profile, and increasing network reliability. The lack of optimal placement of DGs in the network will increase the costs of energy production and losses in transmission lines. Therefore, it is necessary to optimize the location of such DGs in the network so that the number of DGs, installation locations, and their capacity are determined to which the maximum reduction in network losses occurs. Besides, by applying an appropriate objective function, the evolutionary algorithm can find the optimal location of renewable units with respect to the constraints of the issue. In this paper, the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm are used to address the placement of wind and photovoltaic generators simultaneously in two states: With and without considering the effects of greenhouse gas emission. In this regard, first, an analytical method for optimal DG (wind and PV) placement is presented, then, the proposed approach is applied over a real study case, and the simulation carried out using the MATLAB program; hence, the placement problem was solved using GA and PSO and implemented in the IEEE 33-bus radial distribution system. The obtained results were compared and analyzed. The results of the simulation show the improvement of the voltage profile and the reduction of losses in the network.
Mohammadreza Fathi; Mohammad Ghiasi. Optimal DG Placement to Find Optimal Voltage Profile Considering Minimum DG Investment Cost in Smart Neighborhood. Smart Cities 2019, 2, 328 -344.
AMA StyleMohammadreza Fathi, Mohammad Ghiasi. Optimal DG Placement to Find Optimal Voltage Profile Considering Minimum DG Investment Cost in Smart Neighborhood. Smart Cities. 2019; 2 (2):328-344.
Chicago/Turabian StyleMohammadreza Fathi; Mohammad Ghiasi. 2019. "Optimal DG Placement to Find Optimal Voltage Profile Considering Minimum DG Investment Cost in Smart Neighborhood." Smart Cities 2, no. 2: 328-344.
Renewable energy is investigated as a solution for environmental pollution and mitigating energy tension. Overall, there are two basic subjects in technical and economic evaluation of Renewable Energy Sources (RES) including lack of a general indicator for multi-criteria assessment and difficult to quantify analysis indicators. In this paper, an analytical approach for assessing the technical and economic performance of Power Quality (PQ) changes strategy using Flexible AC Transmission System (FACTS) devices is presented. In addition, an optimisation-based power quality change method for delivering differentiated power quality in grids integrated with renewable generations is proposed. The suggested method is based on the evaluation of financial losses due to several critical power quality phenomena, the cost of different mitigation solutions, and the payback owing to the adoption of particular solution. Furthermore, this accounts for different customers’ requirements and provides differentiated levels of power quality across the grid. In order to verify the functionality of the suggested method, effectiveness of proposed model is applied to the IEEE 118-bus test case, and compared with achieved outcomes. The simulation results present both the financial and technical benefits of the optimal mitigation plan. The developed assessment model could provide a reference for investment decision making and subsidy policy optimizing.
Mohammad Ghiasi. Technical and economic evaluation of power quality performance using FACTS devices considering renewable generations. Renewable Energy Focus 2019, 29, 49 -62.
AMA StyleMohammad Ghiasi. Technical and economic evaluation of power quality performance using FACTS devices considering renewable generations. Renewable Energy Focus. 2019; 29 ():49-62.
Chicago/Turabian StyleMohammad Ghiasi. 2019. "Technical and economic evaluation of power quality performance using FACTS devices considering renewable generations." Renewable Energy Focus 29, no. : 49-62.
Hybrid renewable system is a particular type of energy systems which can be used as Distributed Generation (DG) resources to reduce network losses and increase its efficiency. Overall, at design phase, there are two major constraints: first, availability, and second, the cost of equipment. In this paper, considering these constraints and using DGs as Renewable Energy Sources (RES) including wind turbines and photovoltaics, an intelligent method based on multi-objective particle swarm optimization is utilized. Besides, battery bank has been used as a backup unit and energy storage of the hybrid system to reduce the volatility of RESs. The purposes of this paper are: to provide a comprehensive analysis on new structures of AC and DC systems, and then, to determine the capacity and optimal design with hybrid RESs in a smart microgrid to increase the availability and reduce network costs. In order to demonstrate the possibility of proposed approach, an optimized method is designed and implemented in two scenarios (Basic, and Maximum Renewable). Effectiveness of the proposed approach is applied over a real study case. By comparing the proposed method with multi-objective genetic algorithm, simulation results show that the proposed method has effective performance in reducing costs and improving availability.
Mohammad Ghiasi. Detailed study, multi-objective optimization, and design of an AC-DC smart microgrid with hybrid renewable energy resources. Energy 2018, 169, 496 -507.
AMA StyleMohammad Ghiasi. Detailed study, multi-objective optimization, and design of an AC-DC smart microgrid with hybrid renewable energy resources. Energy. 2018; 169 ():496-507.
Chicago/Turabian StyleMohammad Ghiasi. 2018. "Detailed study, multi-objective optimization, and design of an AC-DC smart microgrid with hybrid renewable energy resources." Energy 169, no. : 496-507.
Overall, a power-flow study is a steady-state assessment whose goal is to specify the currents, voltages, and real and reactive flows in a power system under a given load conditions. This paper presents a comparison of common power flow techniques in the Tehran metro power distribution system at the presence of non-linear loads. Moreover, a modelling, simulation and analysis of this power distribution system is implemented with the Electrical Transient Analyser Program (ETAP) software. In this assessment, common power flow techniques including the Newton-Raphson (NR), Fast Decoupled (FD), and Accelerated Gauss-Seidel (AGS) techniques are provided and compared. The obtained results (total generation, loading, demand, system losses, and critical report of the power flow) are analysed. In this paper, we focus on the detailed assessment and monitoring by using the most modern ETAP software, which performs numerical calculations of a large integrated power system with fabulous speed and also generates output reports. The capability and effectiveness of the power flow analysis are demonstrated according to the simulation results obtained with ETAP by applying it to the power distribution system of the Tehran metro. In developing countries such as Iran, off-line modelling and simulation of power grids by a powerful software are beneficial and helpful for the best usage of the electrical energy.
Mohammad Ghiasi. A comparative study on common power flow techniques in the power distribution system of the Tehran metro. Tehnički glasnik 2018, 12, 244 -250.
AMA StyleMohammad Ghiasi. A comparative study on common power flow techniques in the power distribution system of the Tehran metro. Tehnički glasnik. 2018; 12 (4):244-250.
Chicago/Turabian StyleMohammad Ghiasi. 2018. "A comparative study on common power flow techniques in the power distribution system of the Tehran metro." Tehnički glasnik 12, no. 4: 244-250.
Minimizing total system failure could improve the reliability of power network in order to optimize power system operation. In this way, reliability analysis has been proposed by researchers to tackle the mentioned problem. This paper investigates an analytical methodology for reliability assessment and failure analysis techniques in an actual distributed power system. We use reliability analysis to evaluate system design and gathering outage data in this paper. Modelling and simulation of our assumed system are implemented in electrical transient analyzer program (ETAP) software. The results of theoretical/practical reliability and failure analysis including mean time between failure, mean time to repair, availability, system average interruption frequency index, system average interruption duration index, consumer average interruption duration index, average service availability index, average service unavailability index, expected energy not supplied, expected interruption costs, and interrupted energy assessment rate are compared with the summary of reliability assessment simulation. The capability and effectiveness of reliability evaluation are demonstrated according to the simulation results through ETAP which obtained by applying it to this power system.
Mohammad Ghiasi; Noradin Ghadimi; Esmaeil Ahmadinia. An analytical methodology for reliability assessment and failure analysis in distributed power system. SN Applied Sciences 2018, 1, 44 .
AMA StyleMohammad Ghiasi, Noradin Ghadimi, Esmaeil Ahmadinia. An analytical methodology for reliability assessment and failure analysis in distributed power system. SN Applied Sciences. 2018; 1 (1):44.
Chicago/Turabian StyleMohammad Ghiasi; Noradin Ghadimi; Esmaeil Ahmadinia. 2018. "An analytical methodology for reliability assessment and failure analysis in distributed power system." SN Applied Sciences 1, no. 1: 44.
Ancillary services is used to refer to a variety of operations beyond generation and transmission which are requested to maintain grid stability, security and reliability of power system. These services generally consist, frequency control, Spinning Reserves (SR) and operating reserves. Accordingly, an accurate day ahead forecast of SR requirement helps the Independent System Operator to manage a reliable and economic operation of the power system. This prediction model needs strong and accurate method to tackle the complexity, non-stationary and volatility of this signal. Hence, a new hybrid forecasting model is proposed in this paper, to solve the SR requirement. The proposed structure consists of three stage Neural Network (NN) based forecast engine with different learning algorithms. Also, the input signal of this forecast engine is filtered by a new feature selection model to find the high relevancy and low redundancy of features. The proposed strategy is implemented and tested on real data of Pennsylvania–New Jersey–Maryland (PJM) through the comparison with other techniques. Obtained numerical results demonstrate the validity of proposed method.
Mohammad Ghiasi; Esmaeil Ahmadinia; MiladJanghorban Lariche; Houman Zarrabi; Rolando Simoes. A New Spinning Reserve Requirement Prediction with Hybrid Model. Smart Science 2018, 1 -10.
AMA StyleMohammad Ghiasi, Esmaeil Ahmadinia, MiladJanghorban Lariche, Houman Zarrabi, Rolando Simoes. A New Spinning Reserve Requirement Prediction with Hybrid Model. Smart Science. 2018; ():1-10.
Chicago/Turabian StyleMohammad Ghiasi; Esmaeil Ahmadinia; MiladJanghorban Lariche; Houman Zarrabi; Rolando Simoes. 2018. "A New Spinning Reserve Requirement Prediction with Hybrid Model." Smart Science , no. : 1-10.
In this paper, a new prediction model is introduced based on hybrid forecast engine and new feature selection. In this model, the load signal is filtered by feature selection to filter out the best candidates. Then, the proposed forecast engine is predicted the output of feature selection. In this model, the weights of proposed forecast engine are optimised by an intelligent algorithm to increase its accuracy. Effectiveness of the proposed method is applied over real-world engineering test case and compared with other different well-known methods. Obtained results proof the validity of the proposed method.
Mohammad Ghiasi; Majid Irani Jam; Milad Teimourian; Houman Zarrabi; Nasser Yousefi. A new prediction model of electricity load based on hybrid forecast engine. International Journal of Ambient Energy 2017, 40, 179 -186.
AMA StyleMohammad Ghiasi, Majid Irani Jam, Milad Teimourian, Houman Zarrabi, Nasser Yousefi. A new prediction model of electricity load based on hybrid forecast engine. International Journal of Ambient Energy. 2017; 40 (2):179-186.
Chicago/Turabian StyleMohammad Ghiasi; Majid Irani Jam; Milad Teimourian; Houman Zarrabi; Nasser Yousefi. 2017. "A new prediction model of electricity load based on hybrid forecast engine." International Journal of Ambient Energy 40, no. 2: 179-186.
This paper proposes a framework to extract appropriate locational marginal prices for each type of reserve (up-/down-going reserves at both generation- and demand-sides). The proposed reserve pricing scheme accounts for the lost opportunity of selling the convertible products (energy and reserve). The fair prices can be obtained for capacity reserves applying this framework, since this framework assigns the same prices to the same services provided at the same location. The proposed reserve pricing scheme provides all the market participants with the appropriate signals to modify their offers according to the system operator requirements. The pricing problem is decomposed to different hourly sub-problems considering the bounding constraints. To show the effectiveness of the proposed algorithm, it is applied to the IEEE reliability test system and the results are discussed.
Paria Akbary; Mohammad Ghiasi; Mohammad Reza Rezaie Pourkheranjani; Hamidreza Alipour; Noradin Ghadimi. Extracting Appropriate Nodal Marginal Prices for All Types of Committed Reserve. Computational Economics 2017, 53, 1 -26.
AMA StyleParia Akbary, Mohammad Ghiasi, Mohammad Reza Rezaie Pourkheranjani, Hamidreza Alipour, Noradin Ghadimi. Extracting Appropriate Nodal Marginal Prices for All Types of Committed Reserve. Computational Economics. 2017; 53 (1):1-26.
Chicago/Turabian StyleParia Akbary; Mohammad Ghiasi; Mohammad Reza Rezaie Pourkheranjani; Hamidreza Alipour; Noradin Ghadimi. 2017. "Extracting Appropriate Nodal Marginal Prices for All Types of Committed Reserve." Computational Economics 53, no. 1: 1-26.