Traditional maximum power point tracking (MPPT) methods can hardly find global maximum power point (MPP) because output characteristics curve of photovoltaic (PV) array may have multi local maximum power points in irregular shadow, and thus easily fall into the local maximum power point. To address this drawback, Considering that sliding mode variable structure (SMVS) control strategy have such advantages as simple structure, fast response and strong robustness, and P&O method have the advantages of simple principle and convenient implementation, so a new algorithm combining SMVS control method and P&O method is proposed, besides, PI controller is applied to reduce system chattering caused by switching sliding surface. It is applied to MPPT control of PV array in irregular shadow to solve the problem of multi-peak optimization in partial shadow. In order to verity the rationality of the proposed algorithm, the experimental circuit is built, which achieves MPPT control by means of the proposed algorithm and P&O method. The experimental results show that compared with the traditional P&O algorithm, the proposed algorithm can fast track the global MPP, tracking speed increases by 60% and the relative error decreased by 20%. Moreover, the system becomes more stable near the MPP, the fluctuations of output power is greatly reduced, and thus make full use of solar energy. 相似文献
Extended Graetz problem in microchannel is analyzed by using eigenfunction expansion to solve the energy equation. The hydrodynamically developed flow is assumed to enter the microchannel with uniform temperature or uniform heat flux boundary condition. The effects of velocity and temperature jump boundary condition on the microchannel wall, streamwise conduction and viscous dissipation are all included. From the temperature field obtained, the local Nusselt number distributions are shown as the dimensionless parameters (Peclet number, Knudsen number, Brinkman number) vary. The fully developed Nusselt number for each boundary condition is obtained also in terms of these parameters. 相似文献
Particle clogging in the artificial groundwater recharge process is one of the main factors influencing the artificial groundwater recharge efficiency, and particle deposition is the microscopic mechanism of the occurrence and development of particle clogging. Particle deposition in porous media changes the pore structure. The computed tomography (CT) scanning technique is a nondestructive testing method and determines the spatial distribution of pores in porous media. This study combines physical and CT scanning experiments to identify the change process of the pore structure in the artificial groundwater recharge process and compares the pore changes during recharge experiments between two columns containing different media. Porous media changes are observed with the CT scanning technique. The fractal theory is applied in the analysis of CT scan images and physical experiment results. The results of this study indicate that particle deposition can be examined by using CT scan images to obtain pore-related parameters, the internal pore structure of porous media determined through CT scan images can be applied in numerical simulation, and a mathematical model for particle deposition calculation in porous media is established. Compared to the physical experiment measurements, the spatial particle deposition information acquired with the CT scanning technique exhibits a higher accuracy and contains much more relevant data. Not only does this research reveal more clearly the particle clogging mechanism which is based on particle deposition, but also characterize, simulate and predict more accurately the development tendency of particle clogging during artificial groundwater recharge.
Heuristic algorithms (HAs) are widely used in multi-objective reservoir optimal operation (MOROO) due to the rapidity of the calculation and simplicity of their design. The literature usually focuses on one or two categories of HAs and simply reviews the state of the art. To provide an overall understanding and a specific comparison of HAs in MOROO, differential evolution (DE), particle swarm optimisation (PSO), and artificial physics optimisation (APO), which serve as typical examples of the three categories of HAs, are compared in terms of the development and applications using a designed experiment. Besides, the general model with constraints and fitness function, and the solution process using a hybrid feasible domain restoration method and penalty function method are also presented. Taking a designed experiment with multiple scenarios, the mean average of the optimal objective function values, the standard deviation of optimal objective function values, the mean average of the computational time, and population diversity are used for comparisons. Results of the comparisons show that (a) the problem of optimal multipurpose reservoir long-term operation is a mathematic programming problem with narrow feasible region and monotonic objective function; (b) it is easy to obtain the same optimal objective function value, but different optimal solutions using HAs; and (c) comparisons do not result in a clear winner, but DE can be more appropriate for MOROO.
针对混凝土坝位移监测数据的时频非线性特征严重影响到数值模型预报精度的难题,通过小波技术解析原型数据中多重交叉环境驱动的效应实况,有机结合非线性自回归模型(Nonlinear Autoregressive Model with Exogenous Input, NARX)和差分整合移动平均自回归模型(Autoregressive Integrated Moving Average Model, ARIMA),建立了多尺度组合机制下的自回归模型体系,解决了内蕴复杂混沌特性的监测序列的信息挖掘难点。工程实例分析表明,所建模型的拟合精度及预测能力均得以提升,相比于传统模型具有较好的抗噪性和鲁棒性。此外,所建立的计算模型经一定的优化和拓展,亦可推广应用于其它水工建筑物的效应预报分析。 相似文献
In this paper, we present the induced generalized intuitionistic fuzzy ordered weighted averaging (I-GIFOWA) operator. It is a new aggregation operator that generalized the IFOWA operator, including all the characteristics of both the generalized IFOWA and the induced IFOWA operators. It provides a very general formulation that includes as special cases a wide range of aggregation operators for intuitionistic fuzzy information, including all the particular cases of the I-IFOWA operator, GIFOWA operator and the induced intuitionistic fuzzy ordered geometric (I-IFOWG) operator. We also present the induced generalized interval-valued intuitionistic fuzzy ordered weighted averaging (I-GIIFOWA) operator to accommodate the environment in which the given arguments are interval-valued intuitionistic fuzzy sets. Further, we develop procedures to apply them to solve group multiple attribute decision making problems with intuitionistic fuzzy or interval-valued intuitionistic fuzzy information. Finally, we present their application to show the effectiveness of the developed methods. 相似文献