- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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A Solution of Implicit Model of Series-Parallel Photovoltaic Arrays by Using Deterministic and Metaheuristic Global Optimization Algorithms
摘要： The implicit model of photovoltaic (PV) arrays in series-parallel (SP) configuration does not require the LambertW function, since it uses the single-diode model, to represent each submodule, and the implicit current-voltage relationship to construct systems of nonlinear equations that describe the electrical behavior of a PV generator. However, the implicit model does not analyze different solution methods to reduce computation time. This paper formulates the solution of the implicit model of SP arrays as an optimization problem with restrictions for all the variables, i.e., submodules voltages, blocking diode voltage, and strings currents. Such an optimization problem is solved by using two deterministic (Trust-Region Dogleg and Levenberg Marquard) and two metaheuristics (Weighted Differential Evolution and Symbiotic Organism Search) optimization algorithms to reproduce the current–voltage (I–V) curves of small, medium, and large generators operating under homogeneous and non-homogeneous conditions. The performance of all optimization algorithms is evaluated with simulations and experiments. Simulation results indicate that both deterministic optimization algorithms correctly reproduce I–V curves in all the cases; nevertheless, the two metaheuristic optimization methods only reproduce the I–V curves for small generators, but not for medium and large generators. Finally, experimental results confirm the simulation results for small arrays and validate the reference model used in the simulations.
关键词： partial shading,global optimization,series–parallel,deterministic optimization algorithm,implicit model solution,metaheuristic optimization algorithm,photovoltaic array
更新于2025-09-23 15:19:57
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Highly Efficient (110) Orientated FA‐MA Mixed Cation Perovskite Solar Cells via Functionalized Carbon Nanotube and Methylammonium Chloride Additive
摘要： Structural design optimization has always been a topic of concern in industry because good design can improve the safety and economic e?ciency of structures during their service periods. Selecting the appropriate optimization algorithm is the key to solving structural optimal design problems. In this study, a new global optimization idea is proposed and named the moving baseline strategy. A baseline is initially set and will be repeatedly moving upward or downward to approach the optimal value. The proposed strategy is a simple but e?ective, general, and stable algorithm that can be used to solve constrained and unconstrained structural optimization problems. Di?erent from traditional gradient-based, stochastic and heuristic algorithms, the developed algorithm provides a completely new idea to solve global or local optimization problems. Some unconstrained and constrained numerical benchmark examples are used to test the proposed methodology. In addition, structural optimal design problems of a ten-bar planar truss structure and a hypersonic wing structure (X-37B) are utilized to verify the e?ectiveness of the developed strategy in addressing structural design optimization problems in engineering.
关键词： Constrained optimization,Optimization algorithm,Moving baseline strategy,Structural design,Global optimization
更新于2025-09-19 17:13:59
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Implementation of Metallic Vertical Interconnect Access in Hybrid Intercalated Graphene/Quantum Dot Photodetector for Improved Charge Collection
摘要： Performance improvement of heat recovery-based power generation (HRPG) systems puzzles researchers due to the implicitly coupled property. This contribution builds the heat current model of a HRPG system and applies the circuit principle to derive its heat transfer and conversion constraints. Then, derivation of the flow resistance balance equations describes the pressure distribution in circulation loop. Combining with the relations between fluid temperatures and pressures constructs the integrated system model. Based on the separation of linear topology equations and explicit nonlinear component equations from implicit nonlinear constraints using heat current model, this contribution introduces a fast and stable divide-and-conquer solution scheme, which solves linear equations in iterations and updates the iterative variables by substitutions. Finally, optimization of the fluid flow rates for the maximum net electricity generation under different working conditions shows the superiority of the heat current method over the commercial software Ebsilon. The optimized results show that a smaller mass flow rate of flue gas leads to lower optimal evaporation and condensation pressures, while the optimal dryness fraction of exhaust steam is almost unchanged. Besides, the constant backpressure operation strategy apparently deviates from the optima, and the maximum deviation reaches 8.6%.
关键词： Energy conservation,Heat recovery-based power generation,Solution scheme,Heat current model,Global optimization
更新于2025-09-19 17:13:59
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[IEEE 2019 International Conference on Advanced Electrical Engineering (ICAEE) - Algiers, Algeria (2019.11.19-2019.11.21)] 2019 International Conference on Advanced Electrical Engineering (ICAEE) - Photovoltaic module parameters extraction using best-so-far ABC algorithm
摘要： Existing multiobjective evolutionary algorithms (MOEAs) tackle a multiobjective problem either as a whole or as several decomposed single-objective sub-problems. Though the problem decomposition approach generally converges faster through optimizing all the sub-problems simultaneously, there are two issues not fully addressed, i.e., distribution of solutions often depends on a priori problem decomposition, and the lack of population diversity among sub-problems. In this paper, a MOEA with double-level archives is developed. The algorithm takes advantages of both the multiobjective-problem-level and the sub-problem-level approaches by introducing two types of archives, i.e., the global archive and the sub-archive. In each generation, self-reproduction with the global archive and cross-reproduction between the global archive and sub-archives both breed new individuals. The global archive and sub-archives communicate through cross-reproduction, and are updated using the reproduced individuals. Such a framework thus retains fast convergence, and at the same time handles solution distribution along Pareto front (PF) with scalability. To test the performance of the proposed algorithm, experiments are conducted on both the widely used benchmarks and a set of truly disconnected problems. The results verify that, compared with state-of-the-art MOEAs, the proposed algorithm offers competitive advantages in distance to the PF, solution coverage, and search speed.
关键词： multiobjective optimization,Evolutionary algorithm (EA),global optimization
更新于2025-09-16 10:30:52
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Ultrastable plasmonic nanofluids in optimized direct absorption solar collectors
摘要： Nanofluids used in low-flux direct absorption solar collectors (DASCs) typically encounter critical stability issues due to long-term storage, elevated temperatures, high particle concentrations, and fouling from free surfactants. Here, we developed ultrastable nanofluids, and their properties were used to computationally optimize DASC designs. Broadband photothermal absorption was achieved using citrate- (CIT-) and polyethylene glycol-coated (PEG-) gold nanoparticles, circumventing the need for free surfactants. The nanofluids were subjected to long-term ambient storage, high particle concentrations, and incremental heating to analyze their stability and utility in DASCs. Electrosteric stabilization (PEG + CIT) provided superior colloidal stability and more consistent optical properties; chemical and colloidal stability was verified for 16 months, the longest demonstration of stable nanofluids under ambient storage in the solar literature. Optical measurements of the stabilized solar nanofluids were fed into a DASC optimization model. A constrained generalized pattern search (GPS) algorithm simultaneously maximized collector thermal power-gain and minimized nanoparticle mass loading, while maintaining a collector temperature-gain target. Ultimately, by simultaneously developing ultrastable solar nanofluids, minimizing nanoparticle loading requirements, and maximizing collector thermal power gain, the outcomes from this study are considered significant steps towards deploying efficient and reliable low-flux, nanofluid-based DASCs in field applications.
关键词： Plasmonic nanoparticles,Direct absorption solar collector,Electrosteric stabilization,Nanofluid,Global optimization,Dispersion stability
更新于2025-09-12 10:27:22
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Global Optimization of All-Optical Hybrid-Casting in Inter-Datacenter Elastic Optical Networks
摘要： In inter-datacenter elastic optical networks (IDC-EONs), routing, modulation-level, and spectrum assignment (RMLSA) is one of the key measures to increase network capacity and flexibility of spectrum resource management. The coexistence of unicast, anycast, multicast, and manycast traffic in IDC-EONs forms a more complex network communication scheme called hybrid cast. However, the majority of the previous RMLSA approaches focused on the network communication scheme with single traffic type and optimized network performance on the specific network metric, which leads to less practicability and a limit to one-sided network performance improvement. To achieve better network performance, we investigate the hybrid-cast RMLSA (HC-RMLSA) problem with the objective of improving IDC-EON overall performance. Specifically, a criterion is defined to estimate the overall network performance by considering both the overall network service and operation effectiveness and the network cost. An ILP model is formulated to solve the HC-RMLSA problem under static network scenario. Then, we propose an independent optimization genetic algorithm with priority-based rationality adaption (IOGA-PRA) by coordinating a set of hybrid-cast requests simultaneously to solve the HC-RMLSA problem under both static and dynamic network scenarios. Numerical results show that the performance of IOGA-PRA is very close to the optimal solutions obtained by the ILP model on the network cost-effectiveness in static network scenario. The IOGA-PRA also achieves outstanding improvement of the overall network performance compared with benchmark algorithms in the dynamic network scenario.
关键词： global optimization,hybrid-cast,modulation level,spectrum assignment (RMLSA),inter-datacenter,routing,Elastic optical networks (EONs)
更新于2025-09-10 09:29:36