This page has only limited features, please log in for full access.
Smart system and energy saving has become a topic of focus in current research in engineering, business, computer science, and social science with mathematical foundations. The wording “smart” itself has spread widely since 2007, from the revolutionary iPhone. It has changed the mobile business, user platform, data usage, and software/hardware as well. Social media, calling, text, and various applications are all in mobile phones with efficient energy expense afterward. There are also challenges in ubiquitous systems, city planning, and wireless friendly systems for control, management, and industrial application, as well as in unmanned factories [1]. Together with the development of WiFi infrastructure, recently Internet of Things (IoT) has had a lot of emphasis [2]. The recent development of smart devices, such as smart sensors and actuators, has greatly improved the performance of industrial processes such as smart factories, smart farms, and other related systems [3]. With the needs of developing technology, we aim to provide an open forum on this research idea, specifically in smart devices and their application, and related algorithms/applications. The proposed research outputs are becoming an important foundation for the implementation of smart systems with energy-efficient solutions.
Sanghyuk Lee; Mohamed Nayel; Van Huy Pham; Sang Bong Rhee. Algorithms and Devices for Smart Processing Technology for Energy Saving. Mathematical Problems in Engineering 2021, 2021, 1 -2.
AMA StyleSanghyuk Lee, Mohamed Nayel, Van Huy Pham, Sang Bong Rhee. Algorithms and Devices for Smart Processing Technology for Energy Saving. Mathematical Problems in Engineering. 2021; 2021 ():1-2.
Chicago/Turabian StyleSanghyuk Lee; Mohamed Nayel; Van Huy Pham; Sang Bong Rhee. 2021. "Algorithms and Devices for Smart Processing Technology for Energy Saving." Mathematical Problems in Engineering 2021, no. : 1-2.
The enhancement of photovoltaic (PV) energy systems relies on an accurate PV model. Researchers have made significant efforts to extract PV parameters due to their nonlinear characteristics of the PV system, and the lake information from the manufactures’ PV system datasheet. PV parameters estimation using optimization algorithms is a challenging problem in which a wide range of research has been conducted. The idea behind this challenge is the selection of a proper PV model and algorithm to estimate the accurate parameters of this model. In this paper, a new application of the improved gray wolf optimizer (I-GWO) is proposed to estimate the parameters’ values that achieve an accurate PV three diode model (TDM) in a perfect and robust manner. The PV TDM is developed to represent the effect of grain boundaries and large leakage current in the PV system. I-GWO is developed with the aim of improving population, exploration and exploitation balance and convergence of the original GWO. The performance of I-GWO is compared with other well-known optimization algorithms. I-GWO is evaluated through two different applications. In the first application, the real data from RTC furnace is applied and in the second one, the real data of PTW polycrystalline PV panel is applied. The results are compared with different evaluation factors (root mean square error (RMSE), current absolute error and statistical analysis for multiple independent runs). I-GWO achieved the lowest RMSE values in comparison with other algorithms. The RMSE values for the two applications are 0.00098331 and 0.0024276, respectively. Based on quantitative and qualitative performance evaluation, it can be concluded that the estimated parameters of TDM by I-GWO are more accurate than those obtained by other studied optimization algorithms.
Abd-Elhady Ramadan; Salah Kamel; Tahir Khurshaid; Seung-Ryle Oh; Sang-Bong Rhee. Parameter Extraction of Three Diode Solar Photovoltaic Model Using Improved Grey Wolf Optimizer. Sustainability 2021, 13, 6963 .
AMA StyleAbd-Elhady Ramadan, Salah Kamel, Tahir Khurshaid, Seung-Ryle Oh, Sang-Bong Rhee. Parameter Extraction of Three Diode Solar Photovoltaic Model Using Improved Grey Wolf Optimizer. Sustainability. 2021; 13 (12):6963.
Chicago/Turabian StyleAbd-Elhady Ramadan; Salah Kamel; Tahir Khurshaid; Seung-Ryle Oh; Sang-Bong Rhee. 2021. "Parameter Extraction of Three Diode Solar Photovoltaic Model Using Improved Grey Wolf Optimizer." Sustainability 13, no. 12: 6963.
The optimal location of renewable distributed generations (DGs) into a radial distribution system (RDS) has attracted major concerns from power system researchers in the present years. The main target of DG integration is to improve the overall system performance by minimizing power losses and improving the voltage profile. Hence, this paper proposed a hybrid approach between an analytical and metaheuristic optimization technique for the optimal allocation of DG in RDS, considering different types of load. A simple analytical technique was developed in order to determine the sizes of different and multiple DGs, and a new efficient metaheuristic technique known as the Salp Swarm Algorithm (SSA) was suggested in order to choose the best buses in the system, proportionate to the sizes determined by the analytical technique, in order to obtain the minimum losses and the best voltage profile. To verify the power of the proposed hybrid technique on the incorporation of the DGs in RDS, it was applied to different types of static loads; constant power (CP), constant impedance (CZ), and constant current (CI). The performance of the proposed algorithm was validated using two standards RDSs—IEEE 33-bus and IEEE 69-bus systems—and was compared with other optimization techniques.
Amal Mohamed; Salah Kamel; Ali Selim; Tahir Khurshaid; Sang-Bong Rhee. Developing a Hybrid Approach Based on Analytical and Metaheuristic Optimization Algorithms for the Optimization of Renewable DG Allocation Considering Various Types of Loads. Sustainability 2021, 13, 4447 .
AMA StyleAmal Mohamed, Salah Kamel, Ali Selim, Tahir Khurshaid, Sang-Bong Rhee. Developing a Hybrid Approach Based on Analytical and Metaheuristic Optimization Algorithms for the Optimization of Renewable DG Allocation Considering Various Types of Loads. Sustainability. 2021; 13 (8):4447.
Chicago/Turabian StyleAmal Mohamed; Salah Kamel; Ali Selim; Tahir Khurshaid; Sang-Bong Rhee. 2021. "Developing a Hybrid Approach Based on Analytical and Metaheuristic Optimization Algorithms for the Optimization of Renewable DG Allocation Considering Various Types of Loads." Sustainability 13, no. 8: 4447.
Due to increasing fuel prices, the world is moving towards the use of hybrid electric vehicles (HEVs) because they are environmentally friendly, require less maintenance, and are a green technology. The energy management system (EMS) plays an important role in HEVs for the efficient storage of energy and control of the power flow mechanism. This paper deals with the design, modeling, and result-oriented approach for the development of EMS for HEVs using a fuzzy logic controller (FLC). Batteries and supercapacitors (SCs) are used as primary and secondary energy storage systems (ESSs), respectively. EMS consists of the ultra-power transfer algorithm (UPTA) and FLC techniques, which are used to control the power flow. The UPTA technique is used to charge the battery with the help of a single-ended primary inductor converter (SEPIC) during regenerative braking mode. The proposed research examines and compares the performance of FLC with a proportional integral (PI) controller by using MATLAB (Simulink) software. Three scenarios are built to confirm the efficiency of the proposed design. The simulation results show that the proposed design with FLC has a better response as its rise time (2.6 m) and settling time (1.47 µs) are superior to the PI controller.
Muhammad Ishaque; Muhammad Khan; Muhammad Afzal; Abdul Wadood; Seung-Ryle Oh; Muhammad Talha; Sang-Bong Rhee. Fuzzy Logic-Based Duty Cycle Controller for the Energy Management System of Hybrid Electric Vehicles with Hybrid Energy Storage System. Applied Sciences 2021, 11, 3192 .
AMA StyleMuhammad Ishaque, Muhammad Khan, Muhammad Afzal, Abdul Wadood, Seung-Ryle Oh, Muhammad Talha, Sang-Bong Rhee. Fuzzy Logic-Based Duty Cycle Controller for the Energy Management System of Hybrid Electric Vehicles with Hybrid Energy Storage System. Applied Sciences. 2021; 11 (7):3192.
Chicago/Turabian StyleMuhammad Ishaque; Muhammad Khan; Muhammad Afzal; Abdul Wadood; Seung-Ryle Oh; Muhammad Talha; Sang-Bong Rhee. 2021. "Fuzzy Logic-Based Duty Cycle Controller for the Energy Management System of Hybrid Electric Vehicles with Hybrid Energy Storage System." Applied Sciences 11, no. 7: 3192.
Due to an increase in penetration of intermittent distributed energy resources (DERs) in conjunction with load demand escalation, the electric power system will confront more and more challenges in terms of stability and reliability. Furthermore, the adoption of electric vehicles (EVs) is increasing day by day in the personal automobile market. The sudden rise in load demand due to EV load might cause overloading of the potential transformer, undue circuit faults and feeder congestion. The objective of this paper is to develop a strategy for distribution feeder management to support the implementation of emergency demand response (EDR) during contingency and overload conditions. The proposed methodology focuses on management of smart home appliances along with EVs by considering demand rebound and consumer convenience indices, in order to reduce network stress, congestion and demand rebound. The developed scheme ensures that the load profile is retained below a certain level during a demand response event while mitigating demand rebound impacts. Simultaneously, the mitigation of consumers’ convenience level violation, information of smart loads and homeowners’ objective of serving critical loads are also considered during the event. The effectiveness of the developed approach is assessed by simulating a node of a distribution network of 300kW, consisting of 9 distribution transformers serving the associated homes. In this study, the smart loads such as an air conditioner/heater, an EV, a clothes dryer, and a water heater are also modeled and simulated. Furthermore, the simulation results are compared with an already developed de-centralized approach, and a simple fair distribution approach to evaluate and validate the effectiveness of the designed methodology. It is exhibited by the analysis of the results that the developed approach reduced the demand rebound following a demand response event and minimized the congestion at distribution transformer during overloading condition while maintaining the consumers’ comfort.
Zunaib Maqsood Haider; Khawaja Khalid Mehmood; Saad Ullah Khan; Muhammad Omer Khan; Abdul Wadood; Sang-Bong Rhee. Optimal Management of a Distribution Feeder During Contingency and Overload Conditions by Harnessing the Flexibility of Smart Loads. IEEE Access 2021, 9, 40124 -40139.
AMA StyleZunaib Maqsood Haider, Khawaja Khalid Mehmood, Saad Ullah Khan, Muhammad Omer Khan, Abdul Wadood, Sang-Bong Rhee. Optimal Management of a Distribution Feeder During Contingency and Overload Conditions by Harnessing the Flexibility of Smart Loads. IEEE Access. 2021; 9 ():40124-40139.
Chicago/Turabian StyleZunaib Maqsood Haider; Khawaja Khalid Mehmood; Saad Ullah Khan; Muhammad Omer Khan; Abdul Wadood; Sang-Bong Rhee. 2021. "Optimal Management of a Distribution Feeder During Contingency and Overload Conditions by Harnessing the Flexibility of Smart Loads." IEEE Access 9, no. : 40124-40139.
This paper introduces a transactive market design for a combined heat and power (CHP) based energy hub (hub). The proposed model allows a hub operator to supply the hub’s demands by participating in the day-ahead market and a transactive market with CHPs and also in the real-time market by using a recursive moving window algorithm. The proposed local energy market for a hub operator and CHPs is based on the double auction P2P trading mechanism. The model develops an optimal bidding and offering strategies for CHPs and hub operators, respectively, to achieve optimal transactions. The CHPs may be equipped with boiler unit and heat buffer tank (HBT) beside CHP units. The uncertain nature of the hub’s electrical load, real-time and day-ahead markets prices and wind speed is addressed by using robust optimization. The procedure aimed at minimizing the worst-case CHP-based hub’s demand procurement cost even though flexibly regulating the solution robustness. Further, case studies investigate the economic impact of robustness on the hub’s cost.
Manijeh Alipour; Mehdi Abapour; Sajjad Tohidi; Saeid Gholami Farkoush; Sang-Bong Rhee. Designing Transactive Market for Combined Heat and Power Management in Energy Hubs. IEEE Access 2021, 9, 31411 -31419.
AMA StyleManijeh Alipour, Mehdi Abapour, Sajjad Tohidi, Saeid Gholami Farkoush, Sang-Bong Rhee. Designing Transactive Market for Combined Heat and Power Management in Energy Hubs. IEEE Access. 2021; 9 (99):31411-31419.
Chicago/Turabian StyleManijeh Alipour; Mehdi Abapour; Sajjad Tohidi; Saeid Gholami Farkoush; Sang-Bong Rhee. 2021. "Designing Transactive Market for Combined Heat and Power Management in Energy Hubs." IEEE Access 9, no. 99: 31411-31419.
The Alternating Current-Direct Current (AC-DC) hybrid distribution network has received attention in recent years. Due to advancement in technologies such as the integration of renewable energy resources of DC–type output and usage of DC loads in the distribution network, the modern distribution system can meet the increasing energy demand with improved efficiency. In this paper, a new AC-DC hybrid distribution network architecture is analyzed that considers distributed energy resources (DER) in the network. A network reconfiguration scheme is proposed that uses the AC soft open point (AC-SOP) and the DC soft open point (DC-SOP) along with an SOP selection algorithm for minimizing the network power losses. Subsequently, the real-time data for DER and load/demand variation are considered for a day-a-head scenario for the verification of the effectiveness of the network reconfiguration scheme. The results show that the proposed network reconfiguration scheme using AC-SOP and DC-SOP can successfully minimize the network power losses by modifying the network configuration. Finally, the effectiveness of the proposed scheme in minimizing the network power losses by the upgraded network configuration is verified by constructing an AC-DC hybrid distribution network by combining two IEEE 33-bus distribution networks.
Muhammad Omer Khan; Abdul Wadood; Muhammad Irfan Abid; Tahir Khurshaid; Sang Bong Rhee. Minimization of Network Power Losses in the AC-DC Hybrid Distribution Network through Network Reconfiguration Using Soft Open Point. Electronics 2021, 10, 326 .
AMA StyleMuhammad Omer Khan, Abdul Wadood, Muhammad Irfan Abid, Tahir Khurshaid, Sang Bong Rhee. Minimization of Network Power Losses in the AC-DC Hybrid Distribution Network through Network Reconfiguration Using Soft Open Point. Electronics. 2021; 10 (3):326.
Chicago/Turabian StyleMuhammad Omer Khan; Abdul Wadood; Muhammad Irfan Abid; Tahir Khurshaid; Sang Bong Rhee. 2021. "Minimization of Network Power Losses in the AC-DC Hybrid Distribution Network through Network Reconfiguration Using Soft Open Point." Electronics 10, no. 3: 326.
In this paper, a new application of Equilibrium Optimizer (EO) is proposed for design hybrid microgrid to feed the electricity to Dakhla, Morocco, as an isolated area. EO is selected to design the microgrid system due to its high effectiveness in determining the optimal solution in very short time. EO is presented for selecting the optimal system design which can minimize the cost, improve the system stability, and cover the load at different climate conditions. Microgrid system consists of photovoltaic (PV), wind turbine (WT), battery, and diesel generator. The objective function treated in this paper is to minimize the net present cost (NPC), respecting several constraints such as the reliability, availability, and renewable fraction. The sensitivity analysis is conducted in two stages: Firstly, the impact of wind speed, solar radiation, interest rate, and diesel fuel on the NPC, and levelized cost of energy (LCOE) is analyzed. Secondly, the influence of size variation on loss of power supply probability (LPSP) is investigated. The results obtained by EO are compared with those obtained by recent metaheuristics optimization algorithms, namely, Harris Hawks Optimizer (HHO), Artificial Electric Field Algorithm (AEFA), Grey Wolf Optimizer (GWO), and Sooty Tern Optimization Algorithm (STOA). The results show that the optimal system design is achieved by the proposed EO, where renewable energy sources (PV and WT) represent 97% of the annual contribution and fast convergence characteristics are obtained by EO. The best NPC, LCOE, and LPSP are obtained via EO achieving 74327 $, 0.0917 $/kWh, and 0.0489, respectively.
Mohammed Kharrich; Salah Kamel; Mohamed Abdeen; Omar Hazem Mohammed; Mohammed Akherraz; Tahir Khurshaid; Sang-Bong Rhee. Developed Approach Based on Equilibrium Optimizer for Optimal Design of Hybrid PV/Wind/Diesel/Battery Microgrid in Dakhla, Morocco. IEEE Access 2021, 9, 13655 -13670.
AMA StyleMohammed Kharrich, Salah Kamel, Mohamed Abdeen, Omar Hazem Mohammed, Mohammed Akherraz, Tahir Khurshaid, Sang-Bong Rhee. Developed Approach Based on Equilibrium Optimizer for Optimal Design of Hybrid PV/Wind/Diesel/Battery Microgrid in Dakhla, Morocco. IEEE Access. 2021; 9 (99):13655-13670.
Chicago/Turabian StyleMohammed Kharrich; Salah Kamel; Mohamed Abdeen; Omar Hazem Mohammed; Mohammed Akherraz; Tahir Khurshaid; Sang-Bong Rhee. 2021. "Developed Approach Based on Equilibrium Optimizer for Optimal Design of Hybrid PV/Wind/Diesel/Battery Microgrid in Dakhla, Morocco." IEEE Access 9, no. 99: 13655-13670.
In recent years, the introduction of practical and useful solutions to solve the non-intrusive load monitoring (NILM) as one of the sub-sectors of energy management has posed many challenges. In this paper, an effective and applicable solution based on deep learning called convolutional neural network (CNN) is employed for this purpose. The proposed method with the layer-to-layer structure and extraction of features in the power consumption (PC) curves of each household appliances will be able to detect and distinguish the type of electrical appliances (EAs). Likewise, the load disaggregation for the total home PC will be based on identifying the PC patterns of each EA. To do this, experimental evaluation of reference energy data disaggregation dataset (REDD) related to real-world data and measurement at low frequency is used. The PC curves of each EA are used as input data for training and testing the network. After initial training and testing by the PC data of EAs, the total PC of building obtained from the smart meter are used as input for each network in order to load disaggregation. The trained networks prove to be able to disaggregate the total PC for REDD houses 1, 2, 3, and 4 with a 96.17% mean accuracy. The presented results show the precision and efficiency of the suggested technique for solving NILM problems compared to other used methods.
Arash Moradzadeh; Behnam Mohammadi-Ivatloo; Mehdi Abapour; Amjad Anvari-Moghaddam; Saeid Gholami Farkoush; Sang-Bong Rhee. A practical solution based on convolutional neural network for non-intrusive load monitoring. Journal of Ambient Intelligence and Humanized Computing 2021, 1 -15.
AMA StyleArash Moradzadeh, Behnam Mohammadi-Ivatloo, Mehdi Abapour, Amjad Anvari-Moghaddam, Saeid Gholami Farkoush, Sang-Bong Rhee. A practical solution based on convolutional neural network for non-intrusive load monitoring. Journal of Ambient Intelligence and Humanized Computing. 2021; ():1-15.
Chicago/Turabian StyleArash Moradzadeh; Behnam Mohammadi-Ivatloo; Mehdi Abapour; Amjad Anvari-Moghaddam; Saeid Gholami Farkoush; Sang-Bong Rhee. 2021. "A practical solution based on convolutional neural network for non-intrusive load monitoring." Journal of Ambient Intelligence and Humanized Computing , no. : 1-15.
The overall system stability of interconnected electrical and electronic systems is associated with the input and output impedances of each individual system, therefore, accurate AC impedance measurement for a linear and nonlinear systems are imperative. These impedances are normally measured using small-signal frequency injection techniques. However, the harmonic transfers from the output side to the input side and vice versa deteriorates the measured results, making them ambiguous. These harmonic transfers cause the problems of frequency aliasing as well as spectral leakages leading to inaccurate measurements of results. In order to achieve the precise and accurate results, there is a need to adopt such an impedance measuring technique which is the best among the available techniques. A new algorithm is proposed to modify the range of frequencies of interest and inject such small-signal frequencies which do not interfere with the system harmonics. The measurement of the AC impedance of the three-phase RL circuit utilizing three different small-signal injection techniques is performed. From the results displayed, it is clear that all the techniques perform well, therefore, the most simple, single phase line-current injection was selected for the AC impedance measurement of the nonlinear switching circuit such as six-pulse rectifier. The issues discussed above are more serious in nonlinear switching circuit because of the presence of higher order switching harmonics in the circuit. The proposed algorithm is applied to measure the output-impedance of the three-phase AC power supply as well as the AC input-impedance of the six-pulse rectifier. These results of the switch vs average model and that of average model vs. experimental prototype are displayed for comparison, and it is clear that the proposed algorithm offers much-improved results.
Muhammad Saad; Yongfeng Ju; Shahbaz Khan; Husan Ali; Abdul Wadood; Sang Bong Rhee. An Improved Algorithm for AC Impedance Extraction. Journal of Electrical Engineering & Technology 2020, 15, 2437 -2450.
AMA StyleMuhammad Saad, Yongfeng Ju, Shahbaz Khan, Husan Ali, Abdul Wadood, Sang Bong Rhee. An Improved Algorithm for AC Impedance Extraction. Journal of Electrical Engineering & Technology. 2020; 15 (6):2437-2450.
Chicago/Turabian StyleMuhammad Saad; Yongfeng Ju; Shahbaz Khan; Husan Ali; Abdul Wadood; Sang Bong Rhee. 2020. "An Improved Algorithm for AC Impedance Extraction." Journal of Electrical Engineering & Technology 15, no. 6: 2437-2450.
Renewable energy resources (RERs) play a vital role in reducing greenhouse gases, as well as balancing the power generation demand in daily life. Due to the high penetration of RERs and non-linear loads into utility power systems, various power quality issues arise, i.e., voltage drop, harmonic distortion, reactive power demand, etc. In order to handle these power quality issues, there is a need for smart flexible alternating current transmission system (FACTS) devices. In this paper, a super capacitor energy storage system (SCESS)-based static synchronous compensator (STATCOM) is designed in order for the grid-connected photovoltaic (PV) system to overcome the abovementioned power quality issues. A voltage controller and a d-q axis controller are used for the efficient performance of the STATCOM. In order to show the superiority of the supercapacitor, a detailed comparison is made between a battery energy storage system (BESS)-based STATCOM and a SCESS-based STATCOM. Four scenarios are studied to evaluate the performance of the proposed STATCOM design. The proposed SCESS-based STATCOM not only boosts the voltage but also stabilizes it from 368 V to 385 V (Ph-Phrms). The simulated results have confirmed that the proposed design is not only superior to a BESS-based STATCOM but also has the capability to overcome the power quality issues as well.
Muhammad Afzal; Muhammad Khan; Muhammad Hassan; Abdul Wadood; Waqar Uddin; S. Hussain; Sang Rhee. A Comparative Study of Supercapacitor-Based STATCOM in a Grid-Connected Photovoltaic System for Regulating Power Quality Issues. Sustainability 2020, 12, 6781 .
AMA StyleMuhammad Afzal, Muhammad Khan, Muhammad Hassan, Abdul Wadood, Waqar Uddin, S. Hussain, Sang Rhee. A Comparative Study of Supercapacitor-Based STATCOM in a Grid-Connected Photovoltaic System for Regulating Power Quality Issues. Sustainability. 2020; 12 (17):6781.
Chicago/Turabian StyleMuhammad Afzal; Muhammad Khan; Muhammad Hassan; Abdul Wadood; Waqar Uddin; S. Hussain; Sang Rhee. 2020. "A Comparative Study of Supercapacitor-Based STATCOM in a Grid-Connected Photovoltaic System for Regulating Power Quality Issues." Sustainability 12, no. 17: 6781.
In this paper, a clustering cuckoo search optimization (CCSO) is proposed. Different from the randomly generated step size in CSO, the step size in CCSO is generated by a clustering mechanism, and the value is updated according to the average fitness value difference between each cluster and the whole swarm, thereby improving the searching balance between exploration and exploitation of each solution. The effectiveness of CCSO has been validated by six typical benchmark functions and economic load dispatch problems with 6, 10, 13, 15 and 40 generators. The results of CSO and CCSO are displayed and compared in aspects of convergence rate, objective function value and robustness. Moreover, the influences of parameters as step size \(\delta \), solution number P, egg abandon fraction \(p_a\) and cluster number K are all analyzed comprehensively in this study. The conclusion is that, in all the tested cases, CCSO behaves much more competitive than CSO under the same parameter setting conditions.
Jiangtao Yu; Chang-Hwan Kim; Sang-Bong Rhee. Clustering cuckoo search optimization for economic load dispatch problem. Neural Computing and Applications 2020, 32, 16951 -16969.
AMA StyleJiangtao Yu, Chang-Hwan Kim, Sang-Bong Rhee. Clustering cuckoo search optimization for economic load dispatch problem. Neural Computing and Applications. 2020; 32 (22):16951-16969.
Chicago/Turabian StyleJiangtao Yu; Chang-Hwan Kim; Sang-Bong Rhee. 2020. "Clustering cuckoo search optimization for economic load dispatch problem." Neural Computing and Applications 32, no. 22: 16951-16969.
This paper proposes a novel high voltage conversion gain DC/DC boost converter for renewable energy applications and systems. The proposed converter utilizes a three-winding coupled inductor. The presented converter benefits from a unique advantage, as the actual turn ratio of the coupled inductor is decreased in the charging state of the coupled inductor. However, while the inductor is discharging, the actual turn ratio is increased. This feature leads to a very high voltage conversion gain. Furthermore, a passive clamp circuit is employed to recover the leakage current of the coupled inductor. The voltage stresses on the semiconductors are also reduced. In addition, the average current of the primary side of the coupled inductor is zero. This will reduce the total energy stored in the passive elements of the converter. The paper analyzes the Continuous Conduction Mode (CCM) and the operation principles of the presented converter are thoroughly derived. A 250 W laboratory hardware prototype is prepared to verify the proper operation of the presented converter. The obtained experimental results validate the feasibility of the presented converter.
Amir Farakhor; Mehdi Abapour; Mehran Sabahi; Saeid Gholami Farkoush; Seung-Ryle Oh; Sang-Bong Rhee. A Study on an Improved Three-Winding Coupled Inductor Based DC/DC Boost Converter with Continuous Input Current. Energies 2020, 13, 1780 .
AMA StyleAmir Farakhor, Mehdi Abapour, Mehran Sabahi, Saeid Gholami Farkoush, Seung-Ryle Oh, Sang-Bong Rhee. A Study on an Improved Three-Winding Coupled Inductor Based DC/DC Boost Converter with Continuous Input Current. Energies. 2020; 13 (7):1780.
Chicago/Turabian StyleAmir Farakhor; Mehdi Abapour; Mehran Sabahi; Saeid Gholami Farkoush; Seung-Ryle Oh; Sang-Bong Rhee. 2020. "A Study on an Improved Three-Winding Coupled Inductor Based DC/DC Boost Converter with Continuous Input Current." Energies 13, no. 7: 1780.
In this paper, a lately proposed Harris Hawks Optimizer (HHO) is used to solve the directional overcurrent relays (DOCRs) coordination problem. To the best of the authors’ knowledge, this is the first time HHO is being used in the DOCRs coordination problem. The main inspiration of HHO is the cooperative behavior and chasing style of Harris’ hawks from different directions, based on the dynamic nature of scenarios and escaping patterns of the prey. To test its performances in solving the DOCRs coordination problem, it is adopted in 3-bus, 4-bus, 8-bus, and 9-bus systems, which are formulated by three kinds of optimization models as linear programming (LP), nonlinear programming (NLP), and mixed integer nonlinear programming (MINLP), according to the nature of the design variables. Meanwhile, another lately proposed optimization algorithm named Jaya is also adopted to solve the same problem, and the results are compared with HHO in aspects of objective function value, convergence rate, robustness, and computation efficiency. The comparisons show that the robustness and consistency of HHO is relatively better than Jaya, while Jaya provides faster convergence rate with less CPU time and occasionally more competitive objective function value than HHO.
Jiangtao Yu; Chang-Hwan Kim; Sang-Bong Rhee. The Comparison of Lately Proposed Harris Hawks Optimization and Jaya Optimization in Solving Directional Overcurrent Relays Coordination Problem. Complexity 2020, 2020, 1 -22.
AMA StyleJiangtao Yu, Chang-Hwan Kim, Sang-Bong Rhee. The Comparison of Lately Proposed Harris Hawks Optimization and Jaya Optimization in Solving Directional Overcurrent Relays Coordination Problem. Complexity. 2020; 2020 ():1-22.
Chicago/Turabian StyleJiangtao Yu; Chang-Hwan Kim; Sang-Bong Rhee. 2020. "The Comparison of Lately Proposed Harris Hawks Optimization and Jaya Optimization in Solving Directional Overcurrent Relays Coordination Problem." Complexity 2020, no. : 1-22.
To ensure a safe and trustworthy pattern in contradiction to the possible faults, a precise, reliable, and fast relaying strategy is of high importance in an electrical power system. These challenges give the impression of being more refined in multi-loop distribution systems. More recently, overcurrent relays (OCRs) have evolved as proficient counteragents for such cases. In this way, inaugurating an optimal protection coordination strategy is accepted as the primary precondition in guaranteeing the safe protection of the coordination strategy. This study is aimed at lessening the overall operational time of the main relays in order to reduce the power outages. The coordination problem is conducted by adjusting only one parameter, namely the time multiplier setting (TMS). In electrical power relaying coordination, the objective function to be minimized is the sum of the overall operational time of the main relays. In the prescribed work, the coordination of the OCRs in the single- and multi-loop distribution network is realized as an optimization issue. The optimization is accomplished by means of JAYA algorithm. The suggested technique depends on the idea that the result acquired for a certain issue ought to pass near the finest result and avert the worst result. This technique involves only the common control factors and does not involve specific control factors. JAYA is adopted to OCR problem and run 20 times with the same initial condition for each case study, and it has been realized that for every run, the JAYA algorithm converges to the global optimum values requiring less number of iterations and computational time. The results obtained from JAYA algorithm are compared with other evolutionary and up-to-date algorithms, and it was determined that JAYA outperforms the other techniques.
Abdul Wadood; Saeid Gholami Farkoush; Tahir Khurshaid; Jiang-Tao Yu; Chang-Hwan Kim; Sang-Bong Rhee. Application of the JAYA Algorithm in Solving the Problem of the Optimal Coordination of Overcurrent Relays in Single- and Multi-Loop Distribution Systems. Complexity 2019, 2019, 1 -13.
AMA StyleAbdul Wadood, Saeid Gholami Farkoush, Tahir Khurshaid, Jiang-Tao Yu, Chang-Hwan Kim, Sang-Bong Rhee. Application of the JAYA Algorithm in Solving the Problem of the Optimal Coordination of Overcurrent Relays in Single- and Multi-Loop Distribution Systems. Complexity. 2019; 2019 ():1-13.
Chicago/Turabian StyleAbdul Wadood; Saeid Gholami Farkoush; Tahir Khurshaid; Jiang-Tao Yu; Chang-Hwan Kim; Sang-Bong Rhee. 2019. "Application of the JAYA Algorithm in Solving the Problem of the Optimal Coordination of Overcurrent Relays in Single- and Multi-Loop Distribution Systems." Complexity 2019, no. : 1-13.
In power systems protection, the optimal coordination of directional overcurrent relays (DOCRs) is of paramount importance. The coordination of DOCRs in a multi-loop power system is formulated as an optimization problem. The main objective of this paper is to develop the whale optimization algorithm (WOA) for the optimal coordination of DOCRs and minimize the sum of the operating times of all primary relays. The WOA is inspired by the bubble-net hunting strategy of humpback whales which leads toward global minima. The proposed algorithm has been applied to six IEEE test systems including the IEEE three-bus, eight-bus, nine-bus, 14-bus, 15-bus, and 30-bus test systems. Furthermore, the results obtained using the proposed WOA are compared with those obtained by other up-to-date algorithms. The obtained results show the effectiveness of the proposed WOA to minimize the relay operating time for the optimal coordination of DOCRs.
Abdul Wadood; Tahir Khurshaid; Saeid GholamiFarkoush; Jiangtao Yu; Chang-Hwan Kim; Sang-Bong Rhee. Nature-Inspired Whale Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays in Power Systems. Energies 2019, 12, 2297 .
AMA StyleAbdul Wadood, Tahir Khurshaid, Saeid GholamiFarkoush, Jiangtao Yu, Chang-Hwan Kim, Sang-Bong Rhee. Nature-Inspired Whale Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays in Power Systems. Energies. 2019; 12 (12):2297.
Chicago/Turabian StyleAbdul Wadood; Tahir Khurshaid; Saeid GholamiFarkoush; Jiangtao Yu; Chang-Hwan Kim; Sang-Bong Rhee. 2019. "Nature-Inspired Whale Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays in Power Systems." Energies 12, no. 12: 2297.
In an electrical power network linear and non-linear models are used for directional overcurrent relay (DOCR) coordination issue by applying different heuristic techniques. Nature inspired algorithms (NIA) have found great interest in power system optimization issues. This article proposes the recently developed meta-heuristic technique known as Firefly Algorithm (FA) that mimics the flashing behavior of fireflies. The implementation of the proposed algorithm has been utilized to solve the coordination of Directional Over-current Relay (DOCR) problems. The main aim of this work is to find out the optimum values of the Time Dial Setting (TDS) to minimize the relay operating time. The modifications to original FA has been implemented in this paper to solve the DOCR coordination issues. Self-adaptive weight and experience-based learning strategy are added in the original FA, named as improved firefly algorithm (IFA). In IFA, a self-adaptive weight is presented to change the propensity of moving the best solution and ignoring the worst solution. In addition, an experience-based learning system is created and utilized arbitrarily to keep up the populace-assorted variety and improve the exploration capacity. The IFA has been tested on IEEE 6 and 30-bus systems and tested on IEEE 9-bus system for numerical DOCRs and the results had been verified by a comparative study with other optimization techniques. The obtained results show that the IFA provides efficient and promising results compared to other meta-heuristic techniques mentioned in the literature. The IFA has been successfully implemented on MATLAB software programming.
Tahir Khurshaid; Abdul Wadood; Saeid Gholami Farkoush; Chang-Hwan Kim; Jiangtao Yu; Sang-Bong Rhee. Improved Firefly Algorithm for the Optimal Coordination of Directional Overcurrent Relays. IEEE Access 2019, 7, 78503 -78514.
AMA StyleTahir Khurshaid, Abdul Wadood, Saeid Gholami Farkoush, Chang-Hwan Kim, Jiangtao Yu, Sang-Bong Rhee. Improved Firefly Algorithm for the Optimal Coordination of Directional Overcurrent Relays. IEEE Access. 2019; 7 (99):78503-78514.
Chicago/Turabian StyleTahir Khurshaid; Abdul Wadood; Saeid Gholami Farkoush; Chang-Hwan Kim; Jiangtao Yu; Sang-Bong Rhee. 2019. "Improved Firefly Algorithm for the Optimal Coordination of Directional Overcurrent Relays." IEEE Access 7, no. 99: 78503-78514.
The Protective coordination or harmonization of overcurrent relays in power system shows a significant role in protecting the electrical distribution system with the help of primary and secondary protection system. The coordination among these relays must be retained at an optimal rate to reduce the overall operational time and assure that minimum power outages and damages are produced during the fault condition. It is also important to assure that the relay settings should not generate an unpremeditated action and uninterrupted sympathy excursions. This paper describes a New Rooted Tree optimization algorithm (RTO) for optimum coordination of overcurrent relays inspired by the random movement of roots for searching the global optimum. The suggested optimization technique intentions to reduce the time multiplier settings (TMS) of the relays which are the basis of the coordination survey. The performance of the suggested RTO algorithm is tested on different systems. The results achieved by the RTO algorithm are related by further evolutionary optimization methods and it has been originating that the RTO method offers the utmost satisfaction and better clarification. Matlab computer programming has been generated to see the efficiency of the suggested technique
Abdul Wadood; Tahir Khurshaid; Saeid Gholami Farkoush; Chang-Hwan Kim; Sang-Bong Rhee. A Bio-Inspired Rooted Tree Algorithm for Optimal Coordination of Overcurrent Relays. Communications in Computer and Information Science 2019, 188 -201.
AMA StyleAbdul Wadood, Tahir Khurshaid, Saeid Gholami Farkoush, Chang-Hwan Kim, Sang-Bong Rhee. A Bio-Inspired Rooted Tree Algorithm for Optimal Coordination of Overcurrent Relays. Communications in Computer and Information Science. 2019; ():188-201.
Chicago/Turabian StyleAbdul Wadood; Tahir Khurshaid; Saeid Gholami Farkoush; Chang-Hwan Kim; Sang-Bong Rhee. 2019. "A Bio-Inspired Rooted Tree Algorithm for Optimal Coordination of Overcurrent Relays." Communications in Computer and Information Science , no. : 188-201.
In this study, recently proposed JAYA algorithm is implemented on the economic load dispatch problmes (ELDPs). Different from most of the other meta-heuristics, JAYA algorithm needs no algorithm-specific parameters, and only two common parameters are required for effective execution, which makes the implementation simple and effective. Simultaneously, considering the non-convex, non-linear and non-smooth characteristics of the ELDPs, multi-population (MP) method is introduced to improve the population diversity. However, the introduction of MP method adds extra parameters to JAYA algorithm, hence a self-adaptive strategy (SAS) is used to cope with the tuning problem for extra parameters. Moreover, to avoid being trapped by local optima, Lévy flight distribution is incorporated into the population iteration phase. Finally, a self-adaptive multi-population JAYA algorithm with Lévy flights (AML-JAYA) is proposed, it is evaluated by ELDPs with different constraints including power balance constraints, generating capacity limits, ramp rate limits, prohibited operating zones (POZs), valve-point effects and multi-fuel options. The comparisons with state-of-the-art methods indicate that AML-JAYA algorithm can generate more competitive results for solving the ELDPs.
Jiang-Tao Yu; Chang-Hwan Kim; Abdul Wadood; Tahir Khurshaid; Sang-Bong Rhee. Jaya Algorithm With Self-Adaptive Multi-Population and Lévy Flights for Solving Economic Load Dispatch Problems. IEEE Access 2019, 7, 21372 -21384.
AMA StyleJiang-Tao Yu, Chang-Hwan Kim, Abdul Wadood, Tahir Khurshaid, Sang-Bong Rhee. Jaya Algorithm With Self-Adaptive Multi-Population and Lévy Flights for Solving Economic Load Dispatch Problems. IEEE Access. 2019; 7 (99):21372-21384.
Chicago/Turabian StyleJiang-Tao Yu; Chang-Hwan Kim; Abdul Wadood; Tahir Khurshaid; Sang-Bong Rhee. 2019. "Jaya Algorithm With Self-Adaptive Multi-Population and Lévy Flights for Solving Economic Load Dispatch Problems." IEEE Access 7, no. 99: 21372-21384.
The coordination of directional overcurrent relays (DOCR) plays a very important role for maintaining security and enhancing reliability in the electrical power system. This paper presents the coordination of directional overcurrent relay using the modified particle swarm optimization (MPSO) technique. In order to improve the quality of a solution a local search algorithm is embedded to the original particle swarm optimization (PSO). Time dial settings had been optimized for directional overcurrent relays. In PSO technique on implementing the DOCR, being a highly constrained optimization problem that takes into consideration the linear programming. To handle such constraints a modification to PSO algorithm has been introduced. MPSO has achieved a lot of relaxation to its easy implementation, modesty and robustness. The proposed algorithm had been tested on IEEE 6-bus, IEEE 15-bus system and IEEE 30-bus system using MATLAB computer programming.
Tahir Khurshaid; Abdul Wadood; Saeid Gholami Farkoush; Chang-Hwan Kim; Namhun Cho; Sang-Bong Rhee. Modified Particle Swarm Optimizer as Optimization of Time Dial Settings for Coordination of Directional Overcurrent Relay. Journal of Electrical Engineering & Technology 2019, 14, 55 -68.
AMA StyleTahir Khurshaid, Abdul Wadood, Saeid Gholami Farkoush, Chang-Hwan Kim, Namhun Cho, Sang-Bong Rhee. Modified Particle Swarm Optimizer as Optimization of Time Dial Settings for Coordination of Directional Overcurrent Relay. Journal of Electrical Engineering & Technology. 2019; 14 (1):55-68.
Chicago/Turabian StyleTahir Khurshaid; Abdul Wadood; Saeid Gholami Farkoush; Chang-Hwan Kim; Namhun Cho; Sang-Bong Rhee. 2019. "Modified Particle Swarm Optimizer as Optimization of Time Dial Settings for Coordination of Directional Overcurrent Relay." Journal of Electrical Engineering & Technology 14, no. 1: 55-68.