scholarly journals Parameter Identification of Optimized Fractional Maximum Power Point Tracking for Thermoelectric Generation Systems Using Manta Ray Foraging Optimization

Mathematics ◽  
2021 ◽  
Vol 9 (22) ◽  
pp. 2971
Author(s):  
Ahmed Fathy ◽  
Hegazy Rezk ◽  
Dalia Yousri ◽  
Essam H. Houssein ◽  
Rania M. Ghoniem
Keyword(s):  
Steady State ◽  
Optimization Algorithm ◽  
Research Work ◽  
Operating Conditions ◽  
Dynamic Responses ◽  
Basic Unit ◽  
Maximum Efficiency ◽  
Thermoelectric Generation ◽  
Whale Optimization ◽  
Manta Ray

Thermoelectric generation systems (TEGSs) are used to convert temperature difference and heat flow into DC power based on the Seebeck theorem. The basic unit of TEGS is the thermoelectric module (TEM). TEGSs have gained increasing interest in the research fields of sustainable energy. The output power from TEM is mostly reliant on differential temperature between the hot and cold sides of the TEM added to the value of the load. As such, a robust MPPT strategy (MPPTS) is required to ensure that the TEGS is operating near to the MPP while varying the operating conditions. Two main drawbacks may occur in the conventional MPPTSs: low dynamic response, such as in the incremental resistance (INR) method, and oscillations around MPP at steady state, such as in the hill climbing (HC) method. In the current research work, an optimized fractional MPPTS is developed to improve the tracking performance of the TEGS, and remove the two drawbacks of the conventional MPPTSs. The proposed strategy is based on fractional order control (FOC). The main advantage of FOC is that it offers extra flexible time and frequency responses of the control system consent for better and robust performance. The optimal parameters of the optimized fractional MPPTS are identified by a manta ray foraging optimization (MRFO). To verify the robustness of the MRFO, the obtained results are compared with ten other algorithms: particle swarm optimization; whale optimization algorithm; Harris hawks optimization; heap-based optimizer; gradient-based optimizer; grey wolf optimizer; slime mould algorithm; genetic algorithm; seagull optimization algorithm (SOA); and tunicate swarm algorithm. The maximum average cost function of 4.92934 kWh has been achieved by MRFO, followed by SOA (4.5721 kWh). The lowest STD of 0.04867 was also accomplished by MRFO. The maximum efficiency of 99.46% has been obtained by MRFO, whereas the lowest efficiency of 74.01% was obtained by GA. Finally, the main findings proved the superiority of optimized fractional MPPTS compared with conventional methods for both steady-state and dynamic responses.

A Novel Binary Whale Optimization Algorithm-Based Optimal Placement of Phasor Measurement Units

2018 ◽  
pp. 115-138 ◽  
Author(s):  
Tapan Prakash ◽  
Vinay Pratap Singh ◽  
Soumya Ranjan Mohanty
Keyword(s):  
Optimization Algorithm ◽  
Phasor Measurement Units ◽  
Operating Conditions ◽  
Whale Optimization Algorithm ◽  
Area Measurement ◽  
Optimal Placement ◽  
Wide Area Measurement System ◽  
Phasor Measurement ◽  
Whale Optimization ◽  
Measurement Units

Wide-area measurement system (WAMS) is an important part of present power system structure as it provides real-time synchronized measurements of the system with the aid of phasor measurement units (PMUs). Due to economic considerations, PMUs should be installed at optimal locations. The optimal placement of PMUs (OPP) is a problem of optimally placing PMUs at strategic locations maintaining the full observability of the system. In this chapter, a novel binary whale optimization algorithm (BWOA) is applied to solve OPP problem. The maximization of measurement redundancy is considered in the objective function. The proposed algorithm is examined on five different test systems operating under normal operating conditions with or without inclusion of zero-injection buses (ZIBs) and compared with the reports available in literature. The results show the effectiveness of the proposed algorithm in solving OPPP.

scholarly journals Optimal Capacitor Bank Allocation in Electricity Distribution Networks Using Metaheuristic Algorithms

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4239 ◽  
Author(s):  
Ivanov ◽  
Neagu ◽  
Grigoras ◽  
Gavrilas
Keyword(s):  
Optimization Algorithm ◽  
Smart Grids ◽  
Reactive Power ◽  
Distribution Networks ◽  
Operating Conditions ◽  
Metaheuristic Algorithms ◽  
System Level ◽  
Electricity Distribution ◽  
Capacitor Banks ◽  
Whale Optimization

Energy losses and bus voltage levels are key parameters in the operation of electricity distribution networks (EDN), in traditional operating conditions or in modern microgrids with renewable and distributed generation sources. Smart grids are set to bring hardware and software tools to improve the operation of electrical networks, using state-of the art demand management at home or system level and advanced network reconfiguration tools. However, for economic reasons, many network operators will still have to resort to low-cost management solutions, such as bus reactive power compensation using optimally placed capacitor banks. This paper approaches the problem of power and energy loss minimization by optimal allocation of capacitor banks (CB) in medium voltage (MV) EDN buses. A comparison is made between five metaheuristic algorithms used for this purpose: the well-established Genetic Algorithm (GA); Particle Swarm Optimization (PSO); and three newer metaheuristics, the Bat Optimization Algorithm (BOA), the Whale Optimization Algorithm (WOA) and the Sperm-Whale Algorithm (SWA). The algorithms are tested on the IEEE 33-bus system and on a real 215-bus EDN from Romania. The newest SWA algorithm gives the best results, for both test systems.

scholarly journals Optimally Tuned Interleaved Luo Converter for PV Array Fed BLDC Motor Driven Centrifugal Pumps Using Whale Optimization Algorithm—A Resilient Solution for Powering Agricultural Loads

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1445
Author(s):  
A. Darcy Gnana Jegha ◽  
M.S.P. Subathra ◽  
Nallapaneni Manoj Kumar ◽  
Aritra Ghosh
Keyword(s):  
Steady State ◽  
Optimization Algorithm ◽  
Phase 1 ◽  
Whale Optimization Algorithm ◽  
Bldc Motor ◽  
Solar Pv ◽  
Centrifugal Pumps ◽  
Pv Array ◽  
Switching Losses ◽  
Whale Optimization

The use of brushless direct current (BLDC) motors are gaining much prominence in water pumping systems (WPS), especially for agricultural purposes. In most cases, the BLDC based WPS is powered using electricity from the grid, which is vulnerable to disruptive events causing a resilience problem. However, to avoid the resilience issue, grid-interactive solar photovoltaics (PV) are being used, and this is due to the increased penetration of distributed generation sources into the grid. In these systems, based on the inherent nature of solar PV, power converters are preferred, and as a result, problems like switching losses and maintaining steady-state voltages are commonly seen. In this paper, a framework of PV powered WPS with scope for optimizing controller parameters is proposed to avoid the above-raised issues. Based on the proposed framework, the overall structure of the PV powered WPS is modeled, designed, and analyzed. In the proposed system, the power output from solar PV is fed to the BLDC motor and the grid. If any problem arises in obtaining the power from solar PV, grid-interaction helps to run the motor at required speeds making the WPS resilient to unexpected disruptions and vice versa. For retrieving the generated power from PV array, a positive interleaved Luo converter (I-Luo) is used, which boosts the output with minimum switching losses. To maintain the steady-state voltage at the output of the I-Luo converter, a proportional-integral (PI) controller whose parameters are tuned by whale optimization algorithm (WOA) is used. This voltage is fetched to the BLDC motor via a 3-phase (3-Ф) inverter and then to the grid via a single-phase (1-Ф) inverter. The overall system is simulated and experimentally validated, with a detailed analysis of the observed results. The results include the various performance characteristics of the solar PV, converter, and BLDC motor. Besides, by using the field-programmable gate array (FPGA) based SPARTAN6E controller, the performance of the I-Luo is examined experimentally.

scholarly journals Improved grey wolf algorithm for optimization problems

2021 ◽  
Vol 22 (3) ◽  
pp. 1573
Author(s):  
Hafiz Maaz Asgher ◽  
Yana Mazwin Mohmad Hassim ◽  
Rozaida Ghazali ◽  
Muhammad Aamir
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Research Work ◽  
Search Space ◽  
Whale Optimization Algorithm ◽  
Grey Wolf ◽  
Exploration And Exploitation ◽  
Grey Wolf Optimization ◽  
Whale Optimization

The grey wolf optimization (GWO) is a nature inspired and meta-heuristic algorithm, it has successfully solved many optimization problems and give better solution as compare to other algorithms. However, due to its poor exploration capability, it has imbalance relation between exploration and exploitation. Therefore, in this research work, the poor exploration part of GWO was improved through hybrid with whale optimization algorithm (WOA) exploration. The proposed grey wolf whale optimization algorithm (GWWOA) was evaluated on five unimodal and five multimodal benchmark functions. The results shows that GWWOA offered better exploration ability and able to solve the optimization problem and give better solution in search space. Additionally, GWWOA results were well balanced and gave the most optimal in search space as compare to the standard GWO and WOA algorithms.

An enhanced whale optimized fractional order piλ controller based power quality improvement for sensorless brushless dc motor under dynamic operating conditions

2021 ◽  
pp. 1-20
Author(s):  
R Prakash ◽  
K Ayyar
Keyword(s):  
Power Quality ◽  
Fractional Order ◽  
Optimization Algorithm ◽  
Speed Control ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
The Other ◽  
Brushless Dc ◽  
Whale Optimization ◽  
Dynamic Operating

This paper presents an Enhanced Whale Optimization Algorithm (EWO) approach for tuning to perfection of Fractional Order Proportional Integral and integral order Controller (FOPI λ ) is used to sensorless speed control of permanent magnet Brushless DC (PMBLDC) motor under the operating dynamic condition such as (i) speed change by set speed command signal (ii) varying load conditions, (iii) integrated conditions and (iv) controller parameters uncertainty. On the other hand, it deals with a reduced THD (Total Harmonic Distortion) under dynamic operating conditions to improve the power quality for the above control system. Here present are three optimization techniques, namely (i) Enhanced Whale Optimization (EWO), (ii) Invasive Weed Optimization (IWO), and (iii) Social Spider Optimization (SSO) for fine-tuning of the FOPI λ controller parameters with reduction of THD. The proposed optimization algorithm optimized FOPI λ controller are compared under various BLDC motor operating conditions. Based on the results of MATLAB/Simulink models, the proposed algorithms are evaluated. Here, both the simulation and the results of the experiments are validated for the proposed controller technique. It demonstrates that the effectiveness of the proposed controllers is completely validated by comparing the three intelligent optimization techniques mentioned above. The EWO optimized FOPI λ controller for speed control of sensorless PMBLDC motor clearly outperforms the other two intelligent controllers by minimizing the time domain parameters, THD, performance Indices error, convergence time, control efforts, cost function, mean and standard deviation.

Dynamic analysis of a helical gear reduction by experimental and numerical methods

2020 ◽  
Vol 68 (1) ◽  
pp. 48-58
Author(s):  
Chao Liu ◽  
Zongde Fang ◽  
Fang Guo ◽  
Long Xiang ◽  
Yabin Guan ◽  
...  
Keyword(s):  
Numerical Methods ◽  
Dynamic Analysis ◽  
Dynamic Behavior ◽  
Fourth Order ◽  
Numerical Models ◽  
Helical Gear ◽  
Operating Conditions ◽  
Dynamic Responses ◽  
Lumped Mass ◽  
Gear Mesh

Presented in this study is investigation of dynamic behavior of a helical gear reduction by experimental and numerical methods. A closed-loop test rig is designed to measure vibrations of the example system, and the basic principle as well as relevant signal processing method is introduced. A hybrid user-defined element model is established to predict relative vibration acceleration at the gear mesh in a direction normal to contact surfaces. The other two numerical models are also constructed by lumped mass method and contact FEM to compare with the previous model in terms of dynamic responses of the system. First, the experiment data demonstrate that the loaded transmission error calculated by LTCA method is generally acceptable and that the assumption ignoring the tooth backlash is valid under the conditions of large loads. Second, under the common operating conditions, the system vibrations obtained by the experimental and numerical methods primarily occur at the first fourth-order meshing frequencies and that the maximum vibration amplitude, for each method, appears on the fourth-order meshing frequency. Moreover, root-mean-square (RMS) value of the acceleration increases with the increasing loads. Finally, according to the comparison of the simulation results, the variation tendencies of the RMS value along with input rotational speed agree well and that the frequencies where the resonances occur keep coincident generally. With summaries of merit and demerit, application of each numerical method is suggested for dynamic analysis of cylindrical gear system, which aids designers for desirable dynamic behavior of the system and better solutions to engineering problems.

Validation of On-line Respiration Meter and its Applications by Computer Simulation

1992 ◽  
Vol 26 (5-6) ◽  
pp. 1355-1363 ◽  
Author(s):  
C-W. Kim ◽  
H. Spanjers ◽  
A. Klapwijk
Keyword(s):  
Steady State ◽  
Activated Sludge ◽  
Respiration Rate ◽  
Oxygen Demand ◽  
Operating Conditions ◽  
Mass Balances ◽  
Short Term ◽  
Respiration Rates ◽  
On Line ◽  
Made In

An on-line respiration meter is presented to monitor three types of respiration rates of activated sludge and to calculate effluent and influent short term biochemical oxygen demand (BODst) in the continuous activated sludge process. This work is to verify if the calculated BODst is reliable and the assumptions made in the course of developing the proposed procedure were acceptable. A mathematical model and a dynamic simulation program are written for an activated sludge model plant along with the respiration meter based on mass balances of BODst and DO. The simulation results show that the three types of respiration rate reach steady state within 15 minutes under reasonable operating conditions. As long as the respiration rate reaches steady state the proposed procedure calculates the respiration rate that is equal to the simulated. Under constant and dynamic BODst loading, the proposed procedure is capable of calculating the effluent and influent BODst with reasonable accuracy.

Steady-state Security Assessment Based on K-Means Clustering Algorithm and Phasor Measurement Units

2020 ◽  
Vol 13 (4) ◽  
pp. 559-570
Author(s):  
Bassam A. Hemade ◽  
Hamed A. Ibrahim ◽  
Hossam E.A. Talaat
Keyword(s):  
Steady State ◽  
Clustering Algorithm ◽  
System Security ◽  
Phasor Measurement Units ◽  
Operating Conditions ◽  
Security Assessment ◽  
State Security ◽  
Phasor Measurement ◽  
Measurement Units ◽  
Silhouette Analysis

Background: The security assessment plays a crucial role in the operation of the modern interconnected power system network. Methods: Hence, this paper addresses the application of k-means clustering algorithm equipped with Principal Component Analysis (PCA) and silhouette analysis for the classification of system security states. The proposed technique works on three principal axes; the first stage involves contingency quantification based on developed insecurity indices, the second stage includes dataset preparation to enhance the overall performance of the proposed method using PCA and silhouette analysis, and finally the application of the clustering algorithm over data. Results: The proposed composite insecurity index uses available synchronized measurements from Phasor Measurement Units (PMUs) to assess the development of cascading outages. Considering different operational scenarios and multiple levels of contingencies (up to N-3), Fast Decoupled Power Flow (FDPF) have been used for contingency replications. The developed technique applied to IEEE 14-bus and 57-bus standard test system for steady-state security evaluation. Conclusion: The obtained results ensure the robustness and effectiveness of the established procedure in the assessment of the system security irrespective of the network size or operating conditions.

Performance Evaluation of Fiber Wireless (FiWi) Access Network using Position Optimization of ONUs

2020 ◽  
Vol 10 ◽  
Author(s):  
Nitin Chouhan ◽  
Uma Rathore Bhatt ◽  
Raksha Upadhyay
Keyword(s):  
Power Consumption ◽  
Optimization Algorithm ◽  
Optical Network ◽  
Access Network ◽  
Whale Optimization Algorithm ◽  
Wireless Access ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
Whale Optimization ◽  
Wireless Access Network

: Fiber Wireless Access Network is the blend of passive optical network and wireless access network. This network provides higher capacity, better flexibility, more stability and improved reliability to the users at lower cost. Network component (such as Optical Network Unit (ONU)) placement is one of the major research issues which affects the network design, performance and cost. Considering all these concerns, we implement customized Whale Optimization Algorithm (WOA) for ONU placement. Initially whale optimization algorithm is applied to get optimized position of ONUs, which is followed by reduction of number of ONUs in the network. Reduction of ONUs is done such that with fewer number of ONUs all routers present in the network can communicate. In order to ensure the performance of the network we compute the network parameters such as Packet Delivery Ratio (PDR), Total Time for Delivering the Packets in the Network (TTDPN) and percentage reduction in power consumption for the proposed algorithm. The performance of the proposed work is compared with existing algorithms (deterministic and centrally placed ONUs with predefined hops) and has been analyzed through extensive simulation. The result shows that the proposed algorithm is superior to the other algorithms in terms of minimum required ONUs and reduced power consumption in the network with almost same packet delivery ratio and total time for delivering the packets in the network. Therefore, present work is suitable for developing cost-effective FiWi network with maintained network performance.

Mathematical modelling of salt purification by recrystallization. Countercurrent arrangement

1986 ◽  
Vol 51 (11) ◽  
pp. 2481-2488
Author(s):  
Benitto Mayrhofer ◽  
Jana Mayrhoferová ◽  
Lubomír Neužil ◽  
Jaroslav Nývlt
Keyword(s):  
Steady State ◽  
Simple Model ◽  
Mathematical Modelling ◽  
Distribution Coefficient ◽  
Mother Liquor ◽  
Equilibrium Temperature ◽  
Operating Conditions ◽  
Limiting Case

The paper presents a simple model of recrystallization with countercurrent flows of the solution and the crystals being purified. The model assumes steady-state operating conditions, an equilibrium between the outlet streams of each stage, and the same equilibrium temperature and distribution coefficient for all stages. With these assumptions, the model provides the basis for analyzing the variation in the degree of purity as a function of the number of recrystallization stages. The analysis is facilitated by the use of a diagram constructed for the limiting case of perfect removal of the mother liquor from the crystals between the stages.

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