An improved particle swarm optimization(PSO)algorithm based on dynamic inertia weight and adjustment coefficient is proposed in this paper.The expressions of inertia weight and adjustment coefficient are established b...An improved particle swarm optimization(PSO)algorithm based on dynamic inertia weight and adjustment coefficient is proposed in this paper.The expressions of inertia weight and adjustment coefficient are established based on inter-particle distance and iterations.The improved algorithm is applied to a novel two-stage photovoltaic(PV)converter.The later DC/AC circuit chooses a dual-DC-input multi-level dual-buck inverter.This converter has the advantages of no shoot-through problem and high efficiency.Finally,the validity and effectiveness of the algorithm and the converter are verified with experimental results.展开更多
Maximum Power Point Tracking (MPPT) algorithms are now widely used in PV systems independently of the weather conditions. In function of the application, a DC-DC converter topology is chosen without any previous perfo...Maximum Power Point Tracking (MPPT) algorithms are now widely used in PV systems independently of the weather conditions. In function of the application, a DC-DC converter topology is chosen without any previous performance test under normal weather conditions. This paper proposes an experimental evaluation of MPPT algorithms according to DC-DC converters topologies, under normal operation conditions. Four widely used MPPT algorithms <i><i><span>i.e.</span></i><span></span></i> Perturb and Observe (P & O), Hill Climbing (HC), Fixed step Increment of Conductance (INCF) and Variable step Increment of Conductance (INCV) are implemented using two topologies of DC-DC converters <i><span>i.e.</span></i><span> buck and boost converters. As input variables to the PV systems, recorded irradiance and temperature, and extracted photovoltaic parameters (ideality factor, series resistance and reverse saturation current) were used. The obtained results show that buck converter has a lot of power losses when controlled by each of the four MPPT algorithms. Meanwhile, boost converter presents a stable output power during the whole day. Once more, the results show that INCV algorithm has the best performance.</span>展开更多
This paper presents a genetic algorithm (GA) optimization technique to find the optimum switching angles of 11-level inverter with minimum number of dc sources and switches in comparison with the cascade multilevel in...This paper presents a genetic algorithm (GA) optimization technique to find the optimum switching angles of 11-level inverter with minimum number of dc sources and switches in comparison with the cascade multilevel inverter in order to minimize the total harmonic distortion (THD) of their output voltage waveform. Theoretical and simulation results for an 11-level converter show the efficiency of the proposed algorithm to determine the optimum angles in order to decrease the undesired harmonics and produce very high quality output voltage waveform.展开更多
This paper delineates a conventional buck converter controlled by optimized PID controller where Genetic Algorithm (GA) is employed with a view to enhancing the performance by analyzing the performance parameters. Gen...This paper delineates a conventional buck converter controlled by optimized PID controller where Genetic Algorithm (GA) is employed with a view to enhancing the performance by analyzing the performance parameters. Genetic Algorithm is a probabilistic search algorithm which is substantially used as an optimization technique in power electronics. A bunch of modifications have already been introduced to enhance the performance depending upon the applications. However, in this paper, modified genetic algorithm has been used in order to tune the key parameters in the converter. Hence, an analysis is carried out where the performance of the converter is illustrated in terms of rise time, settling time and percentage of overshoot by deploying GA based PID controller and the overall comparative study is presented. Responses of the overall system are accumulated through rigorous simulation in MATLAB environment.展开更多
This paper presents a simple and systematic approach to design second order sliding mode controller for buck converters.The second order sliding mode control(SOSMC)based on twisting algorithm has been implemented to c...This paper presents a simple and systematic approach to design second order sliding mode controller for buck converters.The second order sliding mode control(SOSMC)based on twisting algorithm has been implemented to control buck switch mode converter.The idea behind this strategy is to suppress chattering and maintain robustness and finite time convergence properties of the output voltage error to the equilibrium point under the load variations and parametric uncertainties.In addition,the influence of the twisting algorithm on the performance of closed-loop system is investigated and compared with other algorithms of first order sliding mode control such as adaptive sliding mode control(ASMC),nonsingular terminal sliding mode control(NTSMC).In comparative evaluation,the transient response of the output voltage with the step change in the load and the start-up response of the output voltage with the step change in the input voltage of buck converter were compared.Experimental results were obtained from a hardware setup constructed in laboratory.Finally,for all of the surveyed control methods,the theoretical considerations,numerical simulations,and experimental measurements from a laboratory prototype are compared for different operating points.It is shown that the proposed twisting method presents an improvement in steady state error and settling time of output voltage during load changes.展开更多
文摘An improved particle swarm optimization(PSO)algorithm based on dynamic inertia weight and adjustment coefficient is proposed in this paper.The expressions of inertia weight and adjustment coefficient are established based on inter-particle distance and iterations.The improved algorithm is applied to a novel two-stage photovoltaic(PV)converter.The later DC/AC circuit chooses a dual-DC-input multi-level dual-buck inverter.This converter has the advantages of no shoot-through problem and high efficiency.Finally,the validity and effectiveness of the algorithm and the converter are verified with experimental results.
文摘Maximum Power Point Tracking (MPPT) algorithms are now widely used in PV systems independently of the weather conditions. In function of the application, a DC-DC converter topology is chosen without any previous performance test under normal weather conditions. This paper proposes an experimental evaluation of MPPT algorithms according to DC-DC converters topologies, under normal operation conditions. Four widely used MPPT algorithms <i><i><span>i.e.</span></i><span></span></i> Perturb and Observe (P & O), Hill Climbing (HC), Fixed step Increment of Conductance (INCF) and Variable step Increment of Conductance (INCV) are implemented using two topologies of DC-DC converters <i><span>i.e.</span></i><span> buck and boost converters. As input variables to the PV systems, recorded irradiance and temperature, and extracted photovoltaic parameters (ideality factor, series resistance and reverse saturation current) were used. The obtained results show that buck converter has a lot of power losses when controlled by each of the four MPPT algorithms. Meanwhile, boost converter presents a stable output power during the whole day. Once more, the results show that INCV algorithm has the best performance.</span>
文摘This paper presents a genetic algorithm (GA) optimization technique to find the optimum switching angles of 11-level inverter with minimum number of dc sources and switches in comparison with the cascade multilevel inverter in order to minimize the total harmonic distortion (THD) of their output voltage waveform. Theoretical and simulation results for an 11-level converter show the efficiency of the proposed algorithm to determine the optimum angles in order to decrease the undesired harmonics and produce very high quality output voltage waveform.
文摘This paper delineates a conventional buck converter controlled by optimized PID controller where Genetic Algorithm (GA) is employed with a view to enhancing the performance by analyzing the performance parameters. Genetic Algorithm is a probabilistic search algorithm which is substantially used as an optimization technique in power electronics. A bunch of modifications have already been introduced to enhance the performance depending upon the applications. However, in this paper, modified genetic algorithm has been used in order to tune the key parameters in the converter. Hence, an analysis is carried out where the performance of the converter is illustrated in terms of rise time, settling time and percentage of overshoot by deploying GA based PID controller and the overall comparative study is presented. Responses of the overall system are accumulated through rigorous simulation in MATLAB environment.
文摘This paper presents a simple and systematic approach to design second order sliding mode controller for buck converters.The second order sliding mode control(SOSMC)based on twisting algorithm has been implemented to control buck switch mode converter.The idea behind this strategy is to suppress chattering and maintain robustness and finite time convergence properties of the output voltage error to the equilibrium point under the load variations and parametric uncertainties.In addition,the influence of the twisting algorithm on the performance of closed-loop system is investigated and compared with other algorithms of first order sliding mode control such as adaptive sliding mode control(ASMC),nonsingular terminal sliding mode control(NTSMC).In comparative evaluation,the transient response of the output voltage with the step change in the load and the start-up response of the output voltage with the step change in the input voltage of buck converter were compared.Experimental results were obtained from a hardware setup constructed in laboratory.Finally,for all of the surveyed control methods,the theoretical considerations,numerical simulations,and experimental measurements from a laboratory prototype are compared for different operating points.It is shown that the proposed twisting method presents an improvement in steady state error and settling time of output voltage during load changes.
