scholarly journals Universal power converter for low power applications

2019 ◽  
Vol 10 (4) ◽  
pp. 2165
Author(s):  
M. Asna ◽  
H. Shareef ◽  
S. N. Khalid ◽  
A. O. Idris ◽  
A. N. Aldarmaki ◽  
...  
Keyword(s):  
Reference Frame ◽  
Output Voltage ◽  
Frequency Conversion ◽  
Search Algorithm ◽  
Frequency Converter ◽  
Optimization Technique ◽  
Power Converter ◽  
Experimental Result ◽  
Synchronous Reference Frame ◽  
Parameter Values

A novel power converter that can perform both voltage and frequency conversion was proposed. Inappropriate power supply can damage sensitive sub-components and render the connected device inoperable. Henceforth, the proposed voltage–frequency converter acts as an interface to plug any electrical device directly into an electrical socket and provide the voltage and frequency required. The converter used a synchronous reference frame proportional–integral (SRFPI) controller to regulate the instantaneous output voltage and to improve steady state performance. Because the PI controller works together with the synchronous reference frame controller, it is difficult to tune the PI control parameters. To overcome this issue, a new meta heuristic optimization technique called lightening search algorithm (LSA) optimization was used to identify the optimum PI parameter values. A detailed description of the system operation and control strategy was presented. Finally, the performance of the converter was analyzed and verified by simulation and experimental results. The experimental result has shown that the proposed system has satisfactory output voltage and frequency under different input voltages.

scholarly journals MF_CSA AI based Controlling Technique for Single Phase Converter Output Enhancement at Different Loading Conditions

2021 ◽  
pp. 20-28
Author(s):  
Manisha Patel ◽  
Kaustubh Kulkarni
Keyword(s):  
Alternative Energy ◽  
Search Algorithm ◽  
Optimization Technique ◽  
Power Converter ◽  
Solar Pv ◽  
Algorithm Optimization ◽  
Pv System ◽  
Energy Conversion Systems ◽  
Unbalanced Load ◽  
Phase Converter

Renewable and sustainable sources such as SPV systems and WT energy conversion systems are now seen as a promising and growing alternative energy source in view of global emissions and deterioration of the FP. the main objective of the study designing of a solar PV system with varying irradiation in MATLAB/SIMULINK and enhance its output capacity before its integration with the grid. Also, the system has to be made to drive an unbalanced load and dynamic load so that it is capable of handling the change in the power demand of the system. And to design a suitable controller for the multilevel power converter such that it produces better output results than the traditional converter. AI technique has to be incorporated in the converter designing. This work provides a comprehensive design and implementation of power regulatory per phase inverter with proposed MF-CSA (Multi-Function Crow Search Algorithm) optimization controller. The Inverter has been provided with a proposed optimization technique while integrating it with the grid. The voltage output of the system from the modeled solar system with varying irradiation and temperature control is being fed to the inverter for DC to AC conversion

FREQUENCY CONVERTER WITH THE REDUCED THD OF THE OUTPUT VOLTAGE

2016 ◽  
Vol 2016 (5) ◽  
pp. 14-16 ◽  
Author(s):  
G.V. Pavlov ◽  
◽  
I.L. Vinnichenko ◽  
A.V. Obrubov ◽  
◽  
...  
Keyword(s):  
Output Voltage ◽  
Frequency Converter

Study on the "Phase Hopping" AC-AC Frequency Conversion Method with Approximately Continuous Frequencies

2020 ◽  
Vol 13 (8) ◽  
pp. 1217-1226
Author(s):  
Zhengwang Xu ◽  
Guozhuang Jiang ◽  
Ke Kun ◽  
Yuchun Yi
Keyword(s):  
Output Voltage ◽  
Frequency Conversion ◽  
Frequency Control ◽  
Actual Application ◽  
Power Frequency ◽  
Voltage Frequency ◽  
The Law ◽  
Large Cycle ◽  
Selection Of ◽  
Conversion Technology

Background: The output voltage frequency for the previously proposed "phase hopping" AC-AC frequency conversion technology is determined by the law that the number of output voltage cycles is reduced by one relative to the power frequency in a large cycle containing six jumps. According to the law, only a limited number of output frequencies, such as 37.5 Hz, 42.86 Hz and 45 Hz are found. Due to the large spacing between the output frequencies, the "phase hopping" frequency conversion technology is difficult to put into practical use. Methods: In this paper, the law of the output frequency control is generalized so that the number of output cycles in a large cycle is reduced by n relative to the power frequency. The analysis shows that the appropriate selection of large cycles, including the number of power frequency cycles and the value of n, can find more frequencies to be used. Reducing the interval between the output frequencies within 1Hz. Results: The analysis results were verified in simulation by MATLAB, and the harmonics and the feasibility of the actual application were analyzed. Conclusion: Finally, an experimental platform was built and an experimental analysis was carried out. The experimental results show that the theoretical and simulation analyses are correct.

scholarly journals A support vector machine with the tabu search algorithm for freeway incident detection

2014 ◽  
Vol 24 (2) ◽  
pp. 397-404 ◽  
Author(s):  
Baozhen Yao ◽  
Ping Hu ◽  
Mingheng Zhang ◽  
Maoqing Jin
Keyword(s):  
Support Vector Machine ◽  
Tabu Search ◽  
Traffic Management ◽  
Search Algorithm ◽  
Detection System ◽  
Support Vector ◽  
Incident Detection ◽  
Tabu Search Algorithm ◽  
Proposed Model ◽  
Parameter Values

Abstract Automated Incident Detection (AID) is an important part of Advanced Traffic Management and Information Systems (ATMISs). An automated incident detection system can effectively provide information on an incident, which can help initiate the required measure to reduce the influence of the incident. To accurately detect incidents in expressways, a Support Vector Machine (SVM) is used in this paper. Since the selection of optimal parameters for the SVM can improve prediction accuracy, the tabu search algorithm is employed to optimize the SVM parameters. The proposed model is evaluated with data for two freeways in China. The results show that the tabu search algorithm can effectively provide better parameter values for the SVM, and SVM models outperform Artificial Neural Networks (ANNs) in freeway incident detection.

Optimizing the Learning Process of Feedforward Neural Networks Using Lightning Search Algorithm

2016 ◽  
Vol 25 (06) ◽  
pp. 1650033 ◽  
Author(s):  
Hossam Faris ◽  
Ibrahim Aljarah ◽  
Nailah Al-Madi ◽  
Seyedali Mirjalili
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Optimization Technique ◽  
Back Propagation ◽  
Feedforward Neural Networks ◽  
Training Algorithms ◽  
Local Optima ◽  
Local Solutions

Evolutionary Neural Networks are proven to be beneficial in solving challenging datasets mainly due to the high local optima avoidance. Stochastic operators in such techniques reduce the probability of stagnation in local solutions and assist them to supersede conventional training algorithms such as Back Propagation (BP) and Levenberg-Marquardt (LM). According to the No-Free-Lunch (NFL), however, there is no optimization technique for solving all optimization problems. This means that a Neural Network trained by a new algorithm has the potential to solve a new set of problems or outperform the current techniques in solving existing problems. This motivates our attempts to investigate the efficiency of the recently proposed Evolutionary Algorithm called Lightning Search Algorithm (LSA) in training Neural Network for the first time in the literature. The LSA-based trainer is benchmarked on 16 popular medical diagnosis problems and compared to BP, LM, and 6 other evolutionary trainers. The quantitative and qualitative results show that the LSA algorithm is able to show not only better local solutions avoidance but also faster convergence speed compared to the other algorithms employed. In addition, the statistical test conducted proves that the LSA-based trainer is significantly superior in comparison with the current algorithms on the majority of datasets.

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