Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- BWR nuclear power plant (2)
- Bagging (2)
- Classification (2)
- Deep neural network (2)
- Ensemble (2)
-
- Fault diagnosis (2)
- Generative adversarial networks (2)
- Machine learning (2)
- Power systems operation (2)
- Power systems optimization (2)
- Power systems planning (2)
- Power systems protection (2)
- Transient identification (2)
- 3D vision (1)
- 802.11 (1)
- AC voltage control (1)
- Ac/Dc microgrids (1)
- Active distribution network (ADN) (1)
- Attack-resilient control (1)
- Authentication (1)
- Battery management systems (1)
- Battery model parameter estimation (1)
- Bidirectional power flow (1)
- Boost converter (1)
- Brushless doubly-fed machine (BDFM) (1)
- Brushless doubly-fed reluctance machine (BDFRM) (1)
- Brushless machines (1)
- Calibration (1)
- Camera network (1)
- Cancer (1)
- Publication Year
Articles 1 - 30 of 45
Full-Text Articles in Engineering
Explainable Artificial Intelligence Approach For Diagnosing Faults In An Induction Furnace, Sajad Moosavi, Roozbeh Razavi-Far, Vasile Palade, Mehrdad Saif
Explainable Artificial Intelligence Approach For Diagnosing Faults In An Induction Furnace, Sajad Moosavi, Roozbeh Razavi-Far, Vasile Palade, Mehrdad Saif
Electrical and Computer Engineering Publications
For over a century, induction furnaces have been used in the core of foundries for metal melting and heating. They provide high melting/heating rates with optimal efficiency. The occurrence of faults not only imposes safety risks but also reduces productivity due to unscheduled shutdowns. The problem of diagnosing faults in induction furnaces has not yet been studied, and this work is the first to propose a data-driven framework for diagnosing faults in this application. This paper presents a deep neural network framework for diagnosing electrical faults by measuring real-time electrical parameters at the supply side. Experimental and sensory measurements are …
Trading Electricity With Blockchain Systems, David Bowker, Anant Venkateswaran, Fazel Mohammadi, Abdulraheem Al Garni, Marko Vukobratovic, Claudio Lima, Farrokh Rahimi, Igor Ferreira, Davor Bosnjak, Hannes Agabus, Praveen Agarwal, Santosh Jain, Simon Mikulich, Victor Francisco, Toshiyuki Sawa, Umit Cali, Vladislav Berezovsky, Hannah Davis, Subhendu Subhendu, Gregor Karlovsek, Alex Barakat, Vivek Bhandari, Ivan Ostheimer, Jemma Green
Trading Electricity With Blockchain Systems, David Bowker, Anant Venkateswaran, Fazel Mohammadi, Abdulraheem Al Garni, Marko Vukobratovic, Claudio Lima, Farrokh Rahimi, Igor Ferreira, Davor Bosnjak, Hannes Agabus, Praveen Agarwal, Santosh Jain, Simon Mikulich, Victor Francisco, Toshiyuki Sawa, Umit Cali, Vladislav Berezovsky, Hannah Davis, Subhendu Subhendu, Gregor Karlovsek, Alex Barakat, Vivek Bhandari, Ivan Ostheimer, Jemma Green
Electrical and Computer Engineering Publications
On the wave of the development of new ICT technologies and renewable energy, the power system will certainly experience great changes to its outdated architecture over the next several decades. One of the key drivers of change in the power system is distributed energy resources. They are completely changing the paradigm of the power system as a system with a centralized hierarchy and one-way power flows from generation to customer and from high voltage to low voltage. Because the goals of net zero greenhouse gas emissions are gathering pace and are being accepted by countries around the world, slowdown in …
Event-Based Robust Control Techniques For Wheel-Based Robots Under Cyber-Attack And Dynamic Quantizer, Mobin Saeedi, Jafar Zarei, Mehrdad Saif, Allahyar Montazeri
Event-Based Robust Control Techniques For Wheel-Based Robots Under Cyber-Attack And Dynamic Quantizer, Mobin Saeedi, Jafar Zarei, Mehrdad Saif, Allahyar Montazeri
Electrical and Computer Engineering Publications
Nowadays, mobile robots are becoming an increasingly significant part of daily human life. Humanoid robots, wheeled mobile robots, aerial vehicles, mobile manipulators, and more are examples of mobile robots. As opposed to other robots, they are capable of moving autonomously, with sufficient intelligence to make decisions in response to the perceptions they receive from their environment. In today’s world, cooperative tasks and the ability to control robots via networks make them a component of cyber-physical systems (CPSs). In this study, mobile robots that are acting as a part of CPSs are examined. Data-network burden, signal quantizers, cyber security, delayed transition, …
A New Economic Dispatch For Coupled Transmission And Active Distribution Networks Via Hierarchical Communication Structure, Wael T. El-Sayed, Ahmad Sa Awad, Maher Azzouz, Mostafa F. Shaaban
A New Economic Dispatch For Coupled Transmission And Active Distribution Networks Via Hierarchical Communication Structure, Wael T. El-Sayed, Ahmad Sa Awad, Maher Azzouz, Mostafa F. Shaaban
Electrical and Computer Engineering Publications
Traditionally, the economic dispatch problem (EDP) of the bulk generators connected to transmission networks (TNs) is solved in a centralized dispatching center (CDC) while modeling distribution networks as passive loads. With the increasing penetration levels of distributed generation, coordinating the economic dispatch between TNs and active distribution networks (ADNs) became vital to maximizing system efficiency. This article proposes a hierarchical communication structure, which requires minimal upgrades to the CDC, for solving the EDP of coupled TNs and ADNs. Based on the minimal data transfer between the CDC and distribution network operators, the problem is formulated and solved while considering the …
Open-Circuit Voltage Models For Battery Management Systems: A Review, Prarthana Pillai, Sneha Sundaresan, Pradeep Kumar, Krishna R. Pattipati, Balakumar Balasingam
Open-Circuit Voltage Models For Battery Management Systems: A Review, Prarthana Pillai, Sneha Sundaresan, Pradeep Kumar, Krishna R. Pattipati, Balakumar Balasingam
Mechanical, Automotive & Materials Engineering Publications
A battery management system (BMS) plays a crucial role to ensure the safety, efficiency, and reliability of a rechargeable Li-ion battery pack. State of charge (SOC) estimation is an important operation within a BMS. Estimated SOC is required in several BMS operations, such as remaining power and mileage estimation, battery capacity estimation, charge termination, and cell balancing. The open-circuit voltage (OCV) look-up-based SOC estimation approach is widely used in battery management systems. For OCV lookup, the OCV–SOC characteristic is empirically measured and parameterized a priori. The literature shows numerous OCV–SOC models and approaches to characterize them and use them in …
The Applications Of Blockchain Technologies To Electricity Markets, David Bowker, Vladislav Berezovsky, Marko Vukobratović, Santosh Jain, Subhendu Mukherjee, Fazel Mohammadi, Hannes Agabus
The Applications Of Blockchain Technologies To Electricity Markets, David Bowker, Vladislav Berezovsky, Marko Vukobratović, Santosh Jain, Subhendu Mukherjee, Fazel Mohammadi, Hannes Agabus
Electrical and Computer Engineering Publications
This paper is a summary of the CIGRE Technical Brochure 824 The Role of Blockchain Technologies in Power Markets [17]. The work of the contributors to the Technical Brochure is recognised. It is proposed to follow up this work in a new working group with a more in-depth look at the potential applications for blockchain in the area of energy trading.
Resilient Consensus Control Design For Dc Microgrids Against False Data Injection Attacks Using A Distributed Bank Of Sliding Mode Observers, Yousof Barzegari, Jafar Zarei, Roozbeh Razavi-Far, Mehrdad Saif, Vasile Palade
Resilient Consensus Control Design For Dc Microgrids Against False Data Injection Attacks Using A Distributed Bank Of Sliding Mode Observers, Yousof Barzegari, Jafar Zarei, Roozbeh Razavi-Far, Mehrdad Saif, Vasile Palade
Electrical and Computer Engineering Publications
This paper investigates the problem of false data injection attack (FDIA) detection in microgrids. The grid under study is a DC microgrid with distributed boost converters, where the false data are injected into the voltage data so as to investigate the effect of attacks. The proposed algorithm uses a bank of sliding mode observers that estimates the states of the neighbor agents. Each agent estimates the neighboring states and, according to the estimation and communication data, the detection mechanism reveals the presence of FDIA. The proposed control scheme provides resiliency to the system by replacing the conventional consensus rule with …
Multi-Agent Based Protection Scheme Using Current-Only Directional Overcurrent Relays For Looped/Meshed Distribution Systems, Mohammad Ali Ataei, Mohsen Gitizadeh, Matti Lehtonen, Roozbeh Razavi-Far
Multi-Agent Based Protection Scheme Using Current-Only Directional Overcurrent Relays For Looped/Meshed Distribution Systems, Mohammad Ali Ataei, Mohsen Gitizadeh, Matti Lehtonen, Roozbeh Razavi-Far
Electrical and Computer Engineering Publications
The complexity of the design of the protection system using directional over current relays, for modern power distribution systems has been increased due to the looped/meshed operation and the penetration of distributed generations. Finding a reliable and efficient protection scheme that can be easily implemented in these distribution systems is a major challenge. An efficient solution could be the use of artificial intelligent-based multi-agent systems. This paper proposes a novel distributed intelligent based multi-agent protection scheme, which makes use of current-only directional over current relays as agents for detecting and locating faults and isolating faulty areas (lines/busbars) in the distribution …
Case Study Of Tv Spectrum Sensing Model Based On Machine Learning Techniques, Abdalaziz Mohammad, Faroq Ali Awin, Esam Abdel-Raheem
Case Study Of Tv Spectrum Sensing Model Based On Machine Learning Techniques, Abdalaziz Mohammad, Faroq Ali Awin, Esam Abdel-Raheem
Electrical and Computer Engineering Publications
Spectrum sensing is an essential component in cognitive radios (CR). Machine learning (ML) algorithms are powerful techniques for designing a promising spectrum sensing model. In this work, the supervised ML algorithms, support vector machine (SVM), k-nearest neighbor (kNN), and decision tree (DT) are applied to detect the existence of primary users (PU) over the TV band. Moreover, the Principal Component Analysis (PCA) is incorporated to speed up the learning of the classifiers. Furthermore, the ensemble classification-based approach is employed to enhance the classifier predictivity and performance. Simulation results have shown that the highest performance is achieved by the ensemble classifier. …
Operating Room Scheduling Optimization Based On A Fuzzy Uncertainty Approach And Metaheuristic Algorithms, P Maghzi, M Mohammadi, S H.R Pasandideh, B Naderi
Operating Room Scheduling Optimization Based On A Fuzzy Uncertainty Approach And Metaheuristic Algorithms, P Maghzi, M Mohammadi, S H.R Pasandideh, B Naderi
Electrical and Computer Engineering Publications
Today, planning and scheduling problems are the most significant issues in the world and make a great impact on improving organizational productivity and serving systems such as medical and healthcare providers. Since operating room planning is a major problem in healthcare organizations, the optimization of medical staff and equipment plays an essential role. Thus, this study presents a multi-objective mathematical model with a new categorization (preoperative, intraoperative, and postoperative) to minimize operating room scheduling and the risk of using equipment. Time constraints in healthcare systems and medical equipment limited capacity are the most significant considered limitation in the present study. …
State Of Energy Estimation Of Li-Ion Batteries Using Deep Neural Network And Support Vector Regression, Pradeep Kumar, Yasser Rafat, Paolo Cicconi, Mohammad Saad Alam
State Of Energy Estimation Of Li-Ion Batteries Using Deep Neural Network And Support Vector Regression, Pradeep Kumar, Yasser Rafat, Paolo Cicconi, Mohammad Saad Alam
Mechanical, Automotive & Materials Engineering Publications
Efficient management of the power and energy output of a high voltage battery pack requires a precise estimation of the State of Energy (SOE). For the accurate estimation of SOE, this work presents two data-driven methods as Deep Neural Network (DNN) and a regression model, i.e. Support Vector Regression (SVR). The effectiveness of the SOE estimation was compared, analysed, and studied through these models under similar conditions. For performance enhancement of estimation, a modified algorithm based on the grid search of optimized hyperparameters was proposed and evaluated in both the models. For training of the model at subsequent thermal ranges, …
A Hybrid Framework For Detecting And Eliminating Cyber-Attacks In Power Grids, Arshia Aflaki, Mohsen Gitizadeh, Roozbeh Razavi-Far, Vasile Palade, Ali Akbar Ghasemi
A Hybrid Framework For Detecting And Eliminating Cyber-Attacks In Power Grids, Arshia Aflaki, Mohsen Gitizadeh, Roozbeh Razavi-Far, Vasile Palade, Ali Akbar Ghasemi
Electrical and Computer Engineering Publications
The work described in this paper aims to detect and eliminate cyber-attacks in smart grids that disrupt the process of dynamic state estimation. This work makes use of an unsupervised learning method, called hierarchical clustering, in an attempt to create an artificial sensor to detect two different cyber-sabotage cases, known as false data injection and denial-of-service, during the dynamic behavior of the power system. The detection process is conducted by using an unsupervised learning-enhanced approach, and a decision tree regressor is then employed for removing the threat. The dynamic state estimation of the power system is done by Kalman filters, …
Generative Adversarial Network-Based Scheme For Diagnosing Faults In Cyber-Physical Power Systems, Hossein Hassani, Roozbeh Razavi-Far, Mehrdad Saif, Vasile Palade
Generative Adversarial Network-Based Scheme For Diagnosing Faults In Cyber-Physical Power Systems, Hossein Hassani, Roozbeh Razavi-Far, Mehrdad Saif, Vasile Palade
Electrical and Computer Engineering Publications
This paper presents a novel diagnostic framework for distributed power systems that is based on using generative adversarial networks for generating artificial knockoffs in the power grid. The proposed framework makes use of the raw data measurements including voltage, frequency, and phase-angle that are collected from each bus in the cyber-physical power systems. The collected measurements are firstly fed into a feature selection module, where multiple state-of-the-art techniques have been used to extract the most informative features from the initial set of available features. The selected features are inputs to a knockoff generation module, where the generative adversarial networks are …
Hvdc Circuit Breakers: A Comprehensive Review, Fazel Mohammadi, Kumars Roubehi, Masood Hajian, Kaveh Niayesh, Gevork B. Gharehpetian, Hani Saas, Hasan Ali Mohd, Vijay K. Sood
Hvdc Circuit Breakers: A Comprehensive Review, Fazel Mohammadi, Kumars Roubehi, Masood Hajian, Kaveh Niayesh, Gevork B. Gharehpetian, Hani Saas, Hasan Ali Mohd, Vijay K. Sood
Electrical and Computer Engineering Publications
High Voltage Direct Current (HVDC) systems are now well-integrated into AC systems in many jurisdictions. The integration of Renewable Energy Sources (RESs) is a major focus and the role of HVDC systems is expanding. However, the protection of HVDC systems against DC faults is a challenging issue that can have negative impacts on the reliable and safe operation of power systems. Practical solutions to protect HVDC grids against DC faults without a widespread power outage include (1) using DC Circuit Breakers (CBs) to isolate the faulty DC-link, (2) using a proper converter topology to interrupt the DC fault current, and/or …
Cleaning Of Floating Photovoltaic Systems: A Critical Review On Approaches From Technical And Economic Perspectives, Rafi Zahedi, Parisa Ranjbaran, Gevork B. Gharehpetian, Fazel Mohammadi, Roya Ahmadiahangar
Cleaning Of Floating Photovoltaic Systems: A Critical Review On Approaches From Technical And Economic Perspectives, Rafi Zahedi, Parisa Ranjbaran, Gevork B. Gharehpetian, Fazel Mohammadi, Roya Ahmadiahangar
Electrical and Computer Engineering Publications
There are some environmental factors, such as ambient temperature, dust, etc., which cause a reduction in the efficiency of Photovoltaic (PV) systems. Installation of PV panels on the water surface, commonly known as Floating Photovoltaic (FPV) systems, is one solution to employ PV panels in a cooler environment, achieve higher efficiency, and reduce water evaporation. FPV systems open up new opportunities for scaling up solar generating capacity, especially in countries with high population density and valuable lands, as well as countries with high evaporation rates and water resources deficiency. Since the FPV system is an almost new concept, its cleaning …
A Novel Stochastic Predictive Stabilizer For Dc Microgrids Feeding Cpls, Elham Kowsari, Jafar Zarei, Roozbeh Razavi-Far, Mehrdad Saif, Tomislav Dragicevic, Mohammad Hassan Khooban
A Novel Stochastic Predictive Stabilizer For Dc Microgrids Feeding Cpls, Elham Kowsari, Jafar Zarei, Roozbeh Razavi-Far, Mehrdad Saif, Tomislav Dragicevic, Mohammad Hassan Khooban
Electrical and Computer Engineering Publications
In this work, a novel nonlinear approach is proposed for the stabilization of microgrids (MGs) with constant power loads (CPLs). The proposed method is constructed based on the incorporation of a pseudo-extended Kalman filter (EKF) into stochastic nonlinear model predictive control (MPC). In order to achieve high-performance and optimal control in dc MGs, estimating the instantaneous power flow of the uncertain CPLs and the available power units is essential. Thus, by utilizing the advantages of the stochastic MPC and the pseudo-EKF, an effective control solution for the stabilization of dc islanded MGs with CPLs is established. This technique develops a …
Emerging Challenges In Smart Grid Cybersecurity Enhancement: A Review, Fazel Mohammadi
Emerging Challenges In Smart Grid Cybersecurity Enhancement: A Review, Fazel Mohammadi
Electrical and Computer Engineering Publications
In this paper, a brief survey of measurable factors affecting the adoption of cybersecurity enhancement methods in the smart grid is provided. From a practical point of view, it is a key point to determine to what degree the cyber resilience of power systems can be improved using cost-effective resilience enhancement methods. Numerous attempts have been made to the vital resilience of the smart grid against cyber-attacks. The recently proposed cybersecurity methods are considered in this paper, and their accuracies, computational time, and robustness against external factors in detecting and identifying False Data Injection (FDI) attacks are evaluated. There is …
A Comprehensive Review On Brushless Doubly-Fed Reluctance Machine, Omid Sadeghian, Sajjad Tohidi, Behnam Mohammadi-Ivatloo, Fazel Mohammadi
A Comprehensive Review On Brushless Doubly-Fed Reluctance Machine, Omid Sadeghian, Sajjad Tohidi, Behnam Mohammadi-Ivatloo, Fazel Mohammadi
Electrical and Computer Engineering Publications
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. The Brushless Doubly-Fed Reluctance Machine (BDFRM) has been widely investigated in numerous research studies since it is brushless and cageless and there is no winding on the rotor of this emerging machine. This feature leads to several advantages for this machine in comparison with its induction counterpart, i.e., Brushless Doubly-Fed Induction Machine (BDFIM). Less maintenance, less power losses, and also more reliability are the major advantages of BDFRM compared to BDFIM. The design complexity of its reluctance rotor, as well as flux patterns for indirect connection between the two windings mounted …
Adversarial Learning On Incomplete And Imbalanced Medical Data For Robust Survival Prediction Of Liver Transplant Patients, Ehsan Hallaji, Roozbeh Razavi-Far, Vasile Palade, Mehrdad Saif
Adversarial Learning On Incomplete And Imbalanced Medical Data For Robust Survival Prediction Of Liver Transplant Patients, Ehsan Hallaji, Roozbeh Razavi-Far, Vasile Palade, Mehrdad Saif
Electrical and Computer Engineering Publications
The scarcity of liver transplants necessitates prioritizing patients based on their health condition to minimize deaths on the waiting list. Recently, machine learning methods have gained popularity for automatizing liver transplant allocation systems, which enables prompt and suitable selection of recipients. Nevertheless, raw medical data often contain complexities such as missing values and class imbalance that reduce the reliability of the constructed model. This paper aims at eliminating the respective challenges to ensure the reliability of the decision-making process. To this aim, we first propose a novel deep learning method to simultaneously eliminate these challenges and predict the patients' survival …
The Role Of Blockchain Technologies In Power Markets, David Bowker, Fazel Mohammadi, Abdulraheem Al Gami, Alex Bakakat, Andres Alonso, Bhawna Kapoor, Davor Bosnjak, Edileu Cardoso, Erik Cuadros, Gowri Rajappan, Greg Thorpe, Hannah Davis, Hannes Agabus, Hero Morales, Jelena Milosavljevic, Juan Duran Hernandez, Julian Betancur, Marcelo De Araujo, Nasser Al-Shahrani, Toshiyuki Sawa, Umit Cali, Victor Francisco, Victor Tan, Vijay Vadlamudi, Vladislav Berezovsky, Yousef Almarwan, Yulia Zhilkina
The Role Of Blockchain Technologies In Power Markets, David Bowker, Fazel Mohammadi, Abdulraheem Al Gami, Alex Bakakat, Andres Alonso, Bhawna Kapoor, Davor Bosnjak, Edileu Cardoso, Erik Cuadros, Gowri Rajappan, Greg Thorpe, Hannah Davis, Hannes Agabus, Hero Morales, Jelena Milosavljevic, Juan Duran Hernandez, Julian Betancur, Marcelo De Araujo, Nasser Al-Shahrani, Toshiyuki Sawa, Umit Cali, Victor Francisco, Victor Tan, Vijay Vadlamudi, Vladislav Berezovsky, Yousef Almarwan, Yulia Zhilkina
Electrical and Computer Engineering Publications
Blockchain technology offers some significant potential benefits for improving electricity markets. This TB reviews the potential applications for blockchain as energy markets transform. The WG also assessed 37 projects which have already implemented blockchain into energy markets to understand the current level of actual implementation and the benefits in the real world.
Short-Term Load Forecasting Of Microgrid Via Hybrid Support Vector Regression And Long Short-Term Memory Algorithms, Arash Moradzadeh, Sahar Zakeri, Maryam Shoaran, Behnam Mohammadi-Ivatloo, Fazel Mohammadi
Short-Term Load Forecasting Of Microgrid Via Hybrid Support Vector Regression And Long Short-Term Memory Algorithms, Arash Moradzadeh, Sahar Zakeri, Maryam Shoaran, Behnam Mohammadi-Ivatloo, Fazel Mohammadi
Electrical and Computer Engineering Publications
© 2020 by the authors. Short-Term Load Forecasting (STLF) is the most appropriate type of forecasting for both electricity consumers and generators. In this paper, STLF in a Microgrid (MG) is performed via the hybrid applications of machine learning. The proposed model is a modified Support Vector Regression (SVR) and Long Short-Term Memory (LSTM) called SVR-LSTM. In order to forecast the load, the proposed method is applied to the data related to a rural MG in Africa. Factors influencing the MG load, such as various household types and commercial entities, are selected as input variables and load profiles as target …
Optimal Power Flow Incorporating Facts Devices And Stochastic Wind Power Generation Using Krill Herd Algorithm, Arsalan Abdollahi, Ali Asghar Ghadimi, Mohammad Reza Miveh, Fazel Mohammadi, Francisco Jurado
Optimal Power Flow Incorporating Facts Devices And Stochastic Wind Power Generation Using Krill Herd Algorithm, Arsalan Abdollahi, Ali Asghar Ghadimi, Mohammad Reza Miveh, Fazel Mohammadi, Francisco Jurado
Electrical and Computer Engineering Publications
© 2020 by the authors. This paper deals with investigating the Optimal Power Flow (OPF) solution of power systems considering Flexible AC Transmission Systems (FACTS) devices and wind power generation under uncertainty. The Krill Herd Algorithm (KHA), as a new meta‐heuristic approach, is employed to cope with the OPF problem of power systems, incorporating FACTS devices and stochastic wind power generation. The wind power uncertainty is included in the optimization problem using Weibull probability density function modeling to determine the optimal values of decision variables. Various objective functions, including minimization of fuel cost, active power losses across transmission lines, emission, …
Integration Of High Voltage Ac/Dc Grids Into Modern Power Systems, Fazel Mohammadi
Integration Of High Voltage Ac/Dc Grids Into Modern Power Systems, Fazel Mohammadi
Electrical and Computer Engineering Publications
© 2020 by the author. The Special Issue on "Integration of High Voltage AC/DC Grids into Modern Power Systems" is published. A total of five qualified papers are published in this Special Issue. The topics of the papers are control, protection, operation, planning, and scheduling of high voltage AC/DC grids. Twenty-five researchers have participated in this Special Issue. We hope that this Special Issue is helpful for high voltage applications.
A Dual Approach For Positive T–S Fuzzy Controller Design And Its Application To Cancer Treatment Under Immunotherapy And Chemotherapy, Elham Ahmadi, Jafar Zarei, Roozbeh Razavi-Far, Mehrdad Saif
A Dual Approach For Positive T–S Fuzzy Controller Design And Its Application To Cancer Treatment Under Immunotherapy And Chemotherapy, Elham Ahmadi, Jafar Zarei, Roozbeh Razavi-Far, Mehrdad Saif
Electrical and Computer Engineering Publications
This study proposes an effective positive control design strategy for cancer treatment by resorting to the combination of immunotherapy and chemotherapy. The treatment objective is to transfer the initial number of tumor cells and immune–competent cells from the malignant region into the region of benign growth where the immune system can inhibit tumor growth. In order to achieve this goal, a new modeling strategy is used that is based on Takagi–Sugeno. A Takagi-Sugeno fuzzy model is derived based on the Stepanova nonlinear model that enables a systematic design of the controller. Then, a positive Parallel Distributed Compensation controller is proposed …
Integration Of Ac/Dc Microgrids Into Power Grids, Fazel Mohammadi
Integration Of Ac/Dc Microgrids Into Power Grids, Fazel Mohammadi
Electrical and Computer Engineering Publications
© 2020 by the authors. The Special Issue on "Integration of AC/DC Microgrids into Power Grids" is published. A total of six qualified papers are published in this Special Issue. The topics of the papers are the Optimal Power Flow (OPF), control, protection, and the operation of hybrid AC/DC microgrids. Nine researchers participated in this Special Issue. We hope that this Special Issue is helpful for sustainable energy applications.
Multi-Objective Optimal Reactive Power Planning Under Load Demand And Wind Power Generation Uncertainties Using Ε-Constraint Method, Amir Hossein Shojaei, Ali Asghar Ghadimi, Mohammad Reza Miveh, Fazel Mohammadi, Francisco Jurado
Multi-Objective Optimal Reactive Power Planning Under Load Demand And Wind Power Generation Uncertainties Using Ε-Constraint Method, Amir Hossein Shojaei, Ali Asghar Ghadimi, Mohammad Reza Miveh, Fazel Mohammadi, Francisco Jurado
Electrical and Computer Engineering Publications
© 2020 by the authors. This paper presents an improved multi-objective probabilistic Reactive Power Planning (RPP) in power systems considering uncertainties of load demand and wind power generation. The proposed method is capable of simultaneously (1) reducing the reactive power investment cost, (2) minimizing the total active power losses, (3) improving the voltage stability, and (4) enhancing the loadability factor. The generators' voltage magnitude, the transformer's tap settings, and the output reactive power of VAR sources are taken into account as the control variables. To solve the probabilistic multi-objective RPP problem, the "-constraint method is used. To test the effectiveness …
Optimal Placement Of Tcsc For Congestion Management And Power Loss Reduction Using Multi-Objective Genetic Algorithm, Thang Trung Nguyen, Fazel Mohammadi
Optimal Placement Of Tcsc For Congestion Management And Power Loss Reduction Using Multi-Objective Genetic Algorithm, Thang Trung Nguyen, Fazel Mohammadi
Electrical and Computer Engineering Publications
© 2020 by the authors. Electricity demand has been growing due to the increase in the world population and higher energy usage per capita as compared to the past. As a result, various methods have been proposed to increase the efficiency of power systems in terms of mitigating congestion and minimizing power losses. Power grids operating limitations result in congestion that specifies the final capacity of the system, which decreases the conventional power capabilities between coverage areas. Flexible AC Transmission Systems (FACTS) can help to decrease flows in heavily loaded lines and lead to lines loadability improvements and cost reduction. …
Optimal Scheduling Of Large-Scale Wind-Hydro-Thermal Systems With Fixed-Head Short-Term Model, Thang Trung Nguyen, Ly Huu Pham, Fazel Mohammadi, Le Chi Kien
Optimal Scheduling Of Large-Scale Wind-Hydro-Thermal Systems With Fixed-Head Short-Term Model, Thang Trung Nguyen, Ly Huu Pham, Fazel Mohammadi, Le Chi Kien
Electrical and Computer Engineering Publications
© 2020 by the authors. In this paper, a Modified Adaptive Selection Cuckoo Search Algorithm (MASCSA) is proposed for solving the Optimal Scheduling of Wind-Hydro-Thermal (OSWHT) systems problem. The main objective of the problem is to minimize the total fuel cost for generating the electricity of thermal power plants, where energy from hydropower plants and wind turbines is exploited absolutely. The fixed-head short-term model is taken into account, by supposing that the water head is constant during the operation time, while reservoir volume and water balance are constrained over the scheduled time period. The proposed MASCSA is compared to other …
An Improved Mixed Ac/Dc Power Flow Algorithm In Hybrid Ac/Dc Grids With Mt-Hvdc Systems, Fazel Mohammadi, Gholam Abbas Nazri, Mehrdad Saif
An Improved Mixed Ac/Dc Power Flow Algorithm In Hybrid Ac/Dc Grids With Mt-Hvdc Systems, Fazel Mohammadi, Gholam Abbas Nazri, Mehrdad Saif
Electrical and Computer Engineering Publications
© 2019 by the authors. One of the major challenges on large-scale Multi-Terminal High Voltage Direct Current (MT-HVDC) systems is the steady-state interaction of the hybrid AC/DC grids to achieve an accurate Power Flow (PF) solution. In PF control of MT-HVDC systems, different operational constraints, such as the voltage range, voltage operating region, Total Transfer Capability (TTC), transmission reliability margin, converter station power rating, etc. should be considered. Moreover, due to the nonlinear behavior of MT-HVDC systems, any changes (contingencies and/or faults) in the operating conditions lead to a significant change in the stability margin of the entire or several …
An Improved Droop-Based Control Strategy For Mt-Hvdc Systems, Fazel Mohammadi, Gholam Abbas Nazri, Mehrdad Saif
An Improved Droop-Based Control Strategy For Mt-Hvdc Systems, Fazel Mohammadi, Gholam Abbas Nazri, Mehrdad Saif
Electrical and Computer Engineering Publications
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This paper presents an improved droop-based control strategy for the active and reactive power-sharing on the large-scale Multi-Terminal High Voltage Direct Current (MT-HVDC) systems. As droop parameters enforce the stability of the DC grid, and allow the MT-HVDC systems to participate in the AC voltage and frequency regulation of the different AC systems interconnected by the DC grids, a communication-free control method to optimally select the droop parameters, consisting of AC voltage-droop, DC voltage-droop, and frequency-droop parameters, is investigated to balance the power in MT-HVDC systems and minimize AC voltage, DC …