- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2019 Workshop on Recent Advances in Photonics (WRAP) - Guwahati, India (2019.12.13-2019.12.14)] 2019 Workshop on Recent Advances in Photonics (WRAP) - Lasing based on periodically patterned anisotropic thin film metamaterial
摘要： This paper proposes a novel bi-velocity discrete particle swarm optimization (BVDPSO) approach and extends its application to the nondeterministic polynomial (NP) complete multicast routing problem (MRP). The main contribution is the extension of particle swarm optimization (PSO) from the continuous domain to the binary or discrete domain. First, a novel bi-velocity strategy is developed to represent the possibilities of each dimension being 1 and 0. This strategy is suitable to describe the binary characteristic of the MRP, where 1 stands for a node being selected to construct the multicast tree, whereas 0 stands for being otherwise. Second, BVDPSO updates the velocity and position according to the learning mechanism of the original PSO in the continuous domain. This maintains the fast convergence speed and global search ability of the original PSO. Experiments are comprehensively conducted on all of the 58 instances with small, medium, and large scales in the Operation Research Library (OR-library). The results confirm that BVDPSO can obtain optimal or near-optimal solutions rapidly since it only needs to generate a few multicast trees. BVDPSO outperforms not only several state-of-the-art and recent heuristic algorithms for the MRP problems, but also algorithms based on genetic algorithms, ant colony optimization, and PSO.
关键词： Steiner tree problem (STP),particle swarm optimization (PSO),Communication networks,multicast routing problem (MRP)
更新于2025-09-16 10:30:52
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[IEEE 2019 3rd International Conference on Energy Conservation and Efficiency (ICECE) - Lahore, Pakistan (2019.10.23-2019.10.24)] 2019 3rd International Conference on Energy Conservation and Efficiency (ICECE) - Accelerated PSO-Scaled PI Controller for DC-DC Boost Converter in Photovoltaic Systems
摘要： In the following paper, the Proportional-Integral (PI) controller of the DC-DC boost converter are tuned with and without using the accelerated particle swarm optimization algorithm (APSO) and the performance of the converter is analyzed under the effect of the variable irradiation level of the photovoltaic (PV) module. The mathematical modeling of the photovoltaic module is implemented in the MATLAB/Simulink having two variable parameters, temperature and irradiation level to change the output of the module. The output of the PV module is fed to DC-DC boost converter having a particular value of the duty cycle ratio to increase the voltage to the desired constant value. A three phase sinusoidal pulse width modulation (SPWM) inverter having DC link voltage coming from the converter’s output is simulated in the MATLAB/Simulink and a three phase resistive load is connected across the output terminals of the inverter to get phase and line voltages of the inverter. The irradiation level is used as a variable parameter having a step change at regular intervals and the output voltage of the DC converter under the close feedback system is observed. A comparison is made between the tuning parameters of the PI controller calculated with and without using the Accelerated particle swarm optimization algorithm.
关键词： boost converter,photovoltaic (PV) system,PI controller,Accelerated Particle Swarm Optimization (APSO),SPWM inverter
更新于2025-09-12 10:27:22
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Co-Design of the PV Array and DC/AC Inverter for Maximizing the Energy Production in Grid-Connected Applications
摘要： Grid-connected Photovoltaic (PV) systems are currently developed by merging a PV array and a DC/AC inverter which are designed separately, without considering the impact of the PV array operational characteristics on the power losses of the DC/AC inverter. In this paper, a co-design technique is presented, where the optimal design parameters of the PV array and DC/AC inverter in a grid-connected PV system are calculated concurrently through a unified design process. The proposed technique enables to optimally match the PV array configuration and the DC/AC inverter structure. A study has been performed, where the PV systems synthesized by applying the proposed co-design technique are compared with PV system configurations comprising PV arrays and DC/AC inverters that have been designed separately, through distinct optimization processes based on various alternative optimization objectives. The design results for two installation sites, with different meteorological conditions during a year, demonstrated that only the proposed co-design optimization technique is capable to ensure the maximization of the annual energy production of the overall grid-connected PV system.
关键词： DC-AC power conversion,Optimization methods,Particle Swarm Optimization (PSO),Renewable Energy Sources (RES),Photovoltaic (PV) power systems
更新于2025-09-11 14:15:04
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An Improved Particle Swarm Optimization Algorithm Suitable for Photovoltaic Power Tracking Under Partial Shading Conditions
摘要： The partial shading of a photovoltaic array repeatedly occurs in the natural environment, which can cause a failure of a conventional maximum power point tracking (MPPT) algorithm. In this paper, the convergence conditions of the standard particle swarm optimization (PSO) algorithm are deduced by the functional analysis, and then the influence of the random variables and inertia factor of the algorithm on the trajectory in the particle swarm optimization is analyzed. Based on the analysis results, an improved particle swarm optimization (IPSO) algorithm, which adopts both global and local modes to locate the maximum power point, is proposed. Compared to the standard PSO algorithm, in the improved PSO algorithm, many random and interfered variables are removed, and the structure is optimized significantly. The proposed algorithm is first simulated in MATLAB to ensure its capability. The feasibility of the approach is validated through physical implementation and experimentation. Results demonstrate that the proposed algorithm has the capability to track the global maximum power point within 3.3 s with an accuracy of 99%. Compared with five recently developed Global MPPT algorithms, the proposed IPSO algorithm achieved better performance in the maximum power tracking in the partial shading conditions.
关键词： partial shade,particle swarm optimization,Maximum power point tracking,photovoltaic array
更新于2025-09-11 14:15:04
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Research on fundus image registration and fusion method based on nonsubsampled contourlet and adaptive pulse coupled neural network
摘要： We present a registration and fusion method of fluorescein fundus angiography image and color fundus image which combines Nonsubsampled Contourlet (NSCT) and adaptive Pulse Coupled Neural Network (PCNN). Firstly, we register two images by Speeded Up Robust Features (SURF) feature points, the nearest neighbor and the next nearest neighbor distance ratio method to eliminate the spatial difference between the source images. Secondly, we use Random Sample Consensus (RANSAC) algorithm to achieve precise matching of feature points. Then, according to the transformation parameters obtained by RANSAC algorithm, we perform spatial transformation on the floating image to complete the registration. Finally, we obtain the low-frequency sub-band and high-frequency sub-band of the image to be fused by NSCT decomposition. The low-frequency sub-band is fused by the regional energy. The high-frequency sub-bands are studied using a simplified-PCNN model and the Particle Swarm Optimization algorithm. The link strength of the simplified-PCNN is an improved Laplacian energy and the images are fused based on the number of times the pixels are ignited. The proposed method has higher average gradient (AG) value and information entropy (IE) value and lower relative global dimensional synthesis error (ERGAS) than the existing fusion methods of the fundus image. The fusion image can accurately synthesize the image information, clarify the performance of the details, and has better spectral quality in the spectral range. The image of fused provides an effective reference for the clinical diagnosis of fundus diseases.
关键词： Regional energy,Simplified-pulse coupled neural network,Nonsubsampled contourlet,Particle swarm optimization,Fundus fusion
更新于2025-09-11 14:15:04
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Performance Enhancement of Surface Plasmon Resonance Biosensors Based on Noble Metals-Graphene-WS2 at Visible and Near-Infrared Wavelengths
摘要： In this paper, some biological sensors based on surface plasmon resonance are proposed at visible and near-infrared wavelengths and their performance is improved. The structure of these sensors includes metals, graphene, and 2D transition metal dichalcogenides (TMDCs). Metals such as gold, silver, and copper and a different number of graphene and WS2 layers are investigated for improving the performance of this sensor. The sensitivity of this sensor is studied at the three wavelengths of 633 nm, 660 nm, and 785 nm. In addition, by using the particle swarm optimization (PSO) method, reflectivity is optimized in terms of structural parameters. The best absorption belongs to gold with a reflectivity of 1.3383 × 10?5 (a.u). The results show that this structure which includes metals, graphene, and WS2 has a better performance in near-infrared wavelengths than in visible wavelengths. In this paper, the angular sensitivity and the figure of merit can reach as high as 336 (Deg/RIU) and 48.27 (1/RIU), respectively, as obtained by the optimized structure.
关键词： Particle swarm optimization,Sensors,Surface plasmon resonance,Metals
更新于2025-09-11 14:15:04
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A systematic error modeling and separation method for the special cylindrical profile measurement based on 2-dimension laser displacement sensor
摘要： The aim of this study is to improve aeroengine multistage rotor performance and to reduce the incidence of failures. Measuring the form error of seam allowance connecting cylindrical surface accurately is critical to achieve rotor optimal stack assembly stage-by-stage. In this paper, compared to the traditional cylindrical profile measurement model, a more comprehensive measurement model was built based on a 2-dimensional line laser sensor measurement technique, a model in which the component eccentricity error e, the sensor lateral offset error d, the sensor forward tilt error θx, the sensor lateral tilt error θy, and the rotary table tilt error γ were gradually modeled and separated. The particle swarm optimization algorithm was adopted to solve the model error parameters. The residual error simulation was performed to observe the effect of different levels of offset errors on the measurement results. The aeroengine rotor seam allowance surface measurement experiment was performed to verify the validity of the method model. We can conclude that the sensor lateral offset error d was 3.214 μm, sensor forward tilt error θx was 12.754′′, sensor lateral tilt error θy was 10.365′′, and rotary table tilt error γ was 2.146′′. The cylindricity error value was 3.701 μm. Compared with the traditional cylindrical profile measurement method, the measurement accuracy of cylindricity error was improved by 1.768 μm. The proposed method can improve the measurement accuracy significantly of multistage rotors in the aeroengine measurement process; besides, it can also be extended to the measurement of other geometric form errors.
关键词： error separation,2-dimensional line laser sensor,error modeling,particle swarm optimization,cylindrical profile measurement
更新于2025-09-11 14:15:04
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Kalman filter variant intelligent control for power quality improvement in photovoltaic active power filter system
摘要： The increased usage of nonlinear loads in the distribution system network with deep integration of renewable energy sources imposes the need for advanced control to improve power quality. With the objective to attain desired sinusoidal voltage waveshape at the common utility point, unity power factor operation, and reduction in harmonics, a swarm intelligent enhanced dual extended Kalman filter (DEKF) control technique for improving the performance of shunt active power filter (SAPF) is proposed in this paper. A photovoltaic (PV) array is integrated at the DC‐bus which supplies the required load power thus reducing the grid power demand. A single sensor‐based control is used to track the maximum power from the two‐stage PV array. The enhancement of the SAPF performance requires proper tuning of parameters; constriction factor‐based particle swarm optimization (PSO) is adopted in this regard. The DEKF estimates both state and parameter from the nonlinear system for generating a reference signal. The performance of the proposed control algorithm is compared with the Extended Kalman filter (EKF)‐based PV‐SAPF system using MATLAB/Simulink. To verify the efficacy of the controller, an experimental PV‐SAPF prototype is developed in the laboratory and tested under balanced and unbalanced supply, dynamic load as well as varying irradiance conditions.
关键词： maximum power tracking,dual extended Kalman filter,particle swarm optimization,shunt active power filter,power quality,solar photovoltaic
更新于2025-09-11 14:15:04
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Classified perturbation mutation based particle swarm optimization algorithm for parameters extraction of photovoltaic models
摘要： With the increasing demand for solar energy, accurate, reliable, and efficient parameters extraction of photovoltaic models is becoming more significant and difficult. Accordingly, a more accurate and robust algorithm is continuously needed for this problem. To this end, a classified perturbation mutation based particle swarm optimization algorithm is proposed in this paper. During each generation of the proposed algorithm, the performance of each updated personal best position is evaluated and quantified to be a high-quality or low-quality. Then, for the high-quality personal best position, a mutation strategy with smaller perturbation is developed to enhance the local search ability within the promising search area. For the low-quality personal best position, a bigger perturbation mutation strategy is designed to explore different regions for improving the population diversity. Furthermore, the damping bound handling strategy is employed to mitigate the issue of falling into local optimal. The effectiveness of the proposed algorithm is evaluated by extracting parameters of five different photovoltaic models, and also tested on photovoltaic models under different conditions. Experiment results comprehensively demonstrate the superiority of the proposed algorithm compared with other well-established parameters extraction methods in terms of accuracy, stability, and rapidity.
关键词： Perturbation mutation,Photovoltaic models,Particle swarm optimization,Parameters extraction
更新于2025-09-11 14:15:04
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[IEEE 2018 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) - Kota Kinabalu (2018.10.7-2018.10.10)] 2018 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) - Optimal Operation of Photovoltaic-Pump Hydro Storage Hybrid System
摘要： The water resource is considerably abundant and is the penetration of photovoltaic (PV) power generation gradually increasing in some areas. Due to the fluctuation of PV-alone power generation, a hybrid system with energy storage is a promising solution to improve the reliability. In this paper, an optimal operation strategy based on particle swarm optimization (PSO) of the pumped hydro storage (PHS) in the PV-PHS hybrid system is proposed, which aims to achieve minimum all-day load loss in order to increase the reliability of the PV-PHS hybrid system. Two scenarios, a winter weekday and a summer weekday, are chosen to study the proposed optimal operation strategy based on PSO. The results demonstrate that the proposed optimal operation strategy is a feasible method to achieve minimum all-day load loss.
关键词： Pumped hydro storage,Reliability,Particle swarm optimization,Hybrid system
更新于2025-09-11 14:15:04