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Optimal parameter identification of triple-junction photovoltaic panel based on enhanced moth search algorithm
摘要： The paper proposes an enhanced moth search algorithm (EMSA) employed in identifying the optimal parameters of Triple-Junction (TJS) photovoltaic panel under different operating conditions. Disruptor operator (DO) is placed in the moth search algorithm (MSA) to improve its performance. The DO is used to improve the diversity of the MSA and avoid it from stuck in local point. The presented fitness function in this work is the integral time absolute error (ITAE) between the triple junction PV panel experimental and calculated currents. The panel is simulated in Simulink and tested under different solar radiation conditions. Additionally, the panel performance is investigated under the shadow effect; a comparative study is performed with other metaheuristic optimization approaches and with Hammerstein and wiener identification technique. The proposed EMSA operates with efficiencies around 99.66% and 99.89%for first and second patterns respectively. It is confirmed the superiority and reliability of the proposed EMSA in extracting the optimal parameters of TJS based module operated at different operating conditions.
关键词： Moth search algorithm,Disruptor operator,Triple-junction solar cell
更新于2025-09-16 10:30:52
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[IEEE 2019 IEEE Energy Conversion Congress and Exposition (ECCE) - Baltimore, MD, USA (2019.9.29-2019.10.3)] 2019 IEEE Energy Conversion Congress and Exposition (ECCE) - Multilevel-Boost-Converter-Neutral-Point-Clamped-Inverter Photovoltaic System with MPPT Based on Fibonacci Search
摘要： This paper deals with a system composed by a photovoltaic array feeding a Neutral-Point-Clamped inverter by a dc-dc multilevel boost converter. The system is able to adequately operate under partial shading condition. A current control allows for the boost converter to operate at high frequency while the Maximum Power Point Tracking (MPPT) with the help of Fibonacci search. System operation is explained as well as its model, control and PWM strategy. Simulation and experimental results validate the theoretical studies.
关键词： Fibonacci search,Photovoltaic systems,maximum power point tracking,NPC inverter,partial shading,boost multilevel
更新于2025-09-12 10:27:22
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Fault diagnosis method of photovoltaic array based on support vector machine
摘要： Photovoltaic (PV) arrays are prone to various faults due to the hostile working environment. This paper presents the fault diagnosis algorithm based on support vector machine (SVM) to detect short circuit, open circuit, and lack of irradiation faults that occurred in PV arrays. By analyzing these faults and I–V characteristic curves of PV arrays, the short-circuit current, open-circuit voltage, maximum-power current, and maximum-power voltage are chosen as input parameters of SVM-based fault diagnosis algorithm. The data pre-processing methods are used to improve the quality of fault data set considering the effects of the quality on the performance of SVM-based fault diagnosis algorithm. The grid search and k-fold cross-validation methods are proposed to optimize the parameters of the SVM-based fault diagnosis algorithm. It gets test accuracy of 97% by testing the trained SVM-based fault diagnosis algorithm with 400 data. The experimental results indicate that the SVM-based fault diagnosis algorithm has higher accuracy and generalization ability than other algorithm for fault diagnosis of PV arrays.
关键词： k-fold cross-validation,PV arrays,data preprocessing,grid search,SVM-based fault diagnosis algorithm
更新于2025-09-12 10:27:22
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Piezo-phototronic effect in InGaN/GaN semi-floating micro-disk LED arrays
摘要： Global interests in organic foods are of importance to researchers and the food industry. Traditional questionnaire-based methods do not provide a broad picture. To meet this need, worldwide interests in organic foods were studied by integrating query data from the Google search engine and deep learning methods. The results show that organic oil, organic milk, organic chicken, and organic apples are the most interested organic foods; people from Singapore, US, New Zealand, Australia, United Kingdom and Canada care about organic foods the most; consumers’ interest in organic foods has no correlation with GDP and life expectancy but has significant correlations with other dimensions of culture such as individualism, uncertainty avoidance, and long-term orientation. A recurrent neural network (RNN) model structure is useful in predicting people’s interests in major organic foods over time.
关键词： Organic food,consumer behavior,search interest,deep learning,search engine,neural network,data modeling
更新于2025-09-11 14:15:04
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[ACM Press the Genetic and Evolutionary Computation Conference Companion - Prague, Czech Republic (2019.07.13-2019.07.17)] Proceedings of the Genetic and Evolutionary Computation Conference Companion on - GECCO '19 - Immune and genetic hybrid optimization algorithm for data relay satellite with microwave and laser links
摘要： Aiming at the problem of oversubscription of data relay access request of user stars in future Space-Based Information System, the problem of resource scheduling optimization for data relay satellite system with microwave and laser hybrid links is studied. The characteristics of the hybrid links are analyzed. A multi- objective programming model on static resource scheduling constraint satisfaction problem is established, and a hybrid optimization algorithm integration of artificial immune strategies, niche ideas and improved genetic algorithm is put forward to solve the scheduling model. Simulation results show that the hybrid optimization algorithm optimizes the model quickly, and the ability of global optimization and performs well in convergence. The results validate the static resource scheduling model could accurately describe the microwave and laser hybrid links relay satellite system resource scheduling problem with multi-tasking and multi-type antenna1.
关键词： tabu search,resources scheduling,genetic algorithm,niche,Data relay satellite
更新于2025-09-11 14:15:04
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A hybrid shuffled frog‐leaping and pattern search algorithm for load frequency controller design of a two‐area system composing of PV grid and thermal generator
摘要： The shuffled frog-leaping algorithm (SFLA) is a nature-inspired metaheuristic swarm-based optimization algorithm, which mimics the social behavior of memetics. The SFLA comprises an arrangement of communicating virtual population of frogs divided into various memeplexes. Many attempts have been made to find the variant of the SFLA that performs better on a variety of optimization tasks by making the original SFLA more complex. This paper proposes the hybrid approach by combining the SFLA algorithm with a pattern search algorithm, which improves the original technique named as the hybrid shuffled frog-leaping and pattern search algorithm (hSFLA-PS). The superiority of the proposed hybrid algorithm over the original SFLA in terms of implementation time and solution quality is compared by taking several benchmark test functions. In the next step, the real application of the proposed hybrid approach in the engineering field is done by designing a proportional-integral-derivative (PID) controller for frequency regulation of a two-area power system that is composed of a photovoltaic (PV) grid and a thermal generator. It is observed that the hSFLA-PS–based PID controller is more effective for the load frequency control compared with conventional controllers tuned with genetic algorithm (GA) and firefly algorithm (FA).
关键词： automatic generation control (AGC),multiarea multisource power system,maximum power point tracker (MPPT),hybrid shuffled frog-leaping and pattern search algorithm (hSFLA-PS),PID controller,load frequency control (LFC)
更新于2025-09-11 14:15:04
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Large-Temporal-Numerical-Aperture Parametric Spectro-Temporal Analyzer Based on Silicon Waveguide
摘要： In the distributed integrated modular avionics (DIMA), it is desirable to assign the DIMA devices to the installation locations of the aircraft for obtaining the optimal quality and cost, subject to the resource and safety constraints. Currently the routine device assignments in DIMA are conducted manually or by experience, which becomes more and more dif?cult with the increasing number of devices. Especially in the face of large-scale device assignment problems (DAPs), manual allocation will become an almost impossible task. In this paper, a bi-objective safety-constraint device assignment model in DIMA is formulated with the integer encoding for better scalability. A two-Phase multiobjective local search (2PMOLS) is proposed for addressing it. In the ?rst phase of 2PMOLS, the fast convergence of the population towards the Pareto front (PF) is achieved by the weighted sum approach. In the second phase, Pareto local search is conducted on the solutions delivered in the ?rst phase for the extension of the PF approximation. 2PMOLS is compared with three decomposition-based approaches and one domination-based approach on DAPs of different sizes in the experimental studies. The experimental results show that 2PMOLS outperforms all the compared algorithms, in terms of both the convergence and diversity. It has also been demonstrated that the solution obtained by 2PMOLS is better in terms of both objectives (mass and ship set costs), compared with the solution designed by the domain expert. The experimental results show that 2PMOLS performs increasingly better with the increase of the problem size, compared with other algorithms, which indicates it has better scalability.
关键词： device assignment,Distributed Integrated Modular Avionics,multiobjective optimization,Pareto local search
更新于2025-09-11 14:15:04
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A Novel Spline Model Guided Maximum Power Point Tracking Method for Photovoltaic Systems
摘要： This paper develops a novel data-driven maximum power point tracking (MPPT) method, which is of two-fold, to benefit the power generation of photovoltaics (PV) systems facing variable partial shading conditions (PSCs). Under each PSC, the proposed MPPT utilizes a compact data-driven modelling process to develop the power-voltage (P-V) curve model via the natural cubic spline. Next, the proposed MPPT method develops a novel natural cubic spline guided iterative search process to update the P-V curve model having multiple peaks and to promptly obtain the global maximum power point (GMPP) under the considered PSC. This is a pioneer study which discusses a GMPPT algorithm using a natural cubic spline based P-V curve model. The convergence of the MPP tracked by the proposed algorithm to the GMPP is theoretically ensured by the property of the natural cubic spline. The effectiveness and robustness of the proposed algorithm have been comprehensively evaluated via extensive simulation studies and experiments. Computational results demonstrate that the proposed algorithm is more efficient and effective to attain GMPPs under variable PSCs by comparing with recent MPPT methods using heuristic techniques, which are easily trapped into local MPP under variable PSCs.
关键词： photovoltaics systems,maximum power point tracking,Heuristic search,partial shading conditions,data-driven
更新于2025-09-11 14:15:04
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The $$\hbox {Na}_2\hbox {W}_2\hbox {O}_7$$Na2W2O7 crystal: a crystal scintillator for dark matter search experiment
摘要： A single crystal of Na2W2O7 (NWO) was grown by a low-thermal-gradient Czochralski technique (LTG-CZ). The scintillation properties of the crystal were evaluated for the ?rst time as a potential material for dark matter search experiments. The luminescence and scintillation characteristics of the crystal were studied at room temperature and low temperatures by using a light-emitting diode (LED) and a 90Sr beta source. The luminescence and scintillation light yield at 10 K were signi?cantly higher than those at room temperature. The crystal showed higher light yield at 10 K than a CaMoO4 (CMO) crystal. The decay time of the crystal was investigated at temperatures between 10 and 300 K. The sensitivity to spin-independent weakly interacting massive particle-nucleon interactions based on 10 kg (2 months) and 50 kg (12 months) data for the NWO crystal detectors was estimated by a simulated experiment using the standard halo model. The luminescence, scintillation, and sensitivity results revealed that the NWO crystal is a promising candidate for a dark matter search experiment in the near future.
关键词： dark matter search,Na2W2O7 crystal,cryogenic temperatures,luminescence,scintillation properties
更新于2025-09-10 09:29:36
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A multiobjective approach for design of an off-grid PV/Diesel system considering reliability and cost
摘要： The aim of the present study is to solve multiobjective optimization (MO) of an off-grid hybrid power generation system including photovoltaic (PV) and diesel generator by multiobjective version of a recently developed metaheuristic approach named crow search algorithm (CSA). For this goal, the objective functions are regarded as net present cost (NPC) and system reliability defined by loss of power supply probability (LPSP) index. In the optimization problem, operating limitations of diesel generator and uncertainties of solar radiation and load demand are considered. To solve this problem, a multiobjective CSA (MO-CSA) is developed and the obtained results are compared with the results of nondominated sorting genetic algorithm II (NSGA-II). On the case study, simulation results reveals that when diesel generator ramp rate is 100%, at LPSP = 0, MO-CSA reaches to 54.8 kW and 172.8 m2 for rated power of diesel generator and PV surface area (corresponding cost is 3.7219 × 105 $), while the values found by NSGA-II are 55 kW and 86.04 m2 (corresponding cost is 3.7345 × 105 $). Based on the results, it can be drawn that (1) MO-CSA finds more promising results than NSGA-II, (2) Combination of PV and diesel generator leads to having a cost-effective and reliable power generation system, and (3) by considering the solar radiation and load uncertainties, the system cost increases.
关键词： crow search algorithm,hybrid photovoltaic/diesel system,multiobjective optimization
更新于2025-09-10 09:29:36