并网光伏系统性能检测初探

光伏发电系统的性能以及输出的电能质量是决定太阳能光伏发电系统能否规模化应用的关键因素。然而,国内目前还没有一套统一、有效、合理的对光伏发电系统进行评估和检测的标准及与之对应的技术方案。这已成为摆在每个光伏认证和检测工作者面前急需解决的问     

Multi-objective optimization of a cooling tower assisted vapor compression refrigeration system

A cooling tower assisted vapor compression refrigeration machine has been considered for optimization with multiple criteria. Two objective functions including the total exergy destruction of the system (as a thermodynamic criterion) and the total product cost of the system (as an economic criterion), have been considered simultaneously. A thermodynamic model based on energy and exergy analyses and an economic model according to the Total Revenue Requirement (TRR) method have been developed. Three optimized systems including a single-objective thermodynamic optimized, a single-objective economic optimized and a multi-objective optimized are obtained. In the case of multi-objective optimization, an example of decision-making process for selection of the final solution from the Pareto frontier has been presented. The exergetic and economic results obtained for three optimized systems have been compared and discussed. The results have shown that the multi-objective design more acceptably satisfies generalized engineering criteria than other two single-objective optimized designs.     

Multi-objective system reliability-based optimization method for design of a fully parametric concept car body

This article investigates multi-objective optimization under reliability constraints with applications in vehicle structural design. To improve computational efficiency, an improved multi-objective system reliability-based design optimization (MOSRBDO) method is developed, and used to explore the lightweight and high-performance design of a concept car body under uncertainty. A parametric model knowledge base is established, followed by the construction of a fully parametric concept car body of a multi-purpose vehicle (FPCCB-MPV) based on the knowledge base. The structural shape, gauge and topology optimization are then designed on the basis of FPCCB-MPV. The numerical implementation of MOSRBDO employs the double-loop method with design optimization in the outer loop and system reliability analysis in the inner loop. Multi-objective particle swarm optimization is used as the outer loop optimization solver. An improved multi-modal radial-based importance sampling (MRBIS) method is utilized as the system reliability solver for multi-constraint analysis in the inner loop. The accuracy and efficiency of the MRBIS method are demonstrated on three widely used test problems. In conclusion, MOSRBDO has been successfully applied for the design of a full parametric concept car body. The results show that the improved MOSRBDO method is more effective and efficient than the traditional MOSRBDO while achieving the same accuracy, and that the optimized body-in-white structure signifies a noticeable improvement from the baseline model.     

Models for the schedule optimization problem at a public transit terminal

This work deals with the proposal of some models for the schedule optimization problem for public transit networks. In particular, we consider the case of a transit terminal where passengers are supposed to split among different lines of a service, or even change mode of transportation in case of intermodal systems. Starting from a given schedule for the transit lines arriving at the terminal, the aim is to decide the optimal schedule for the output lines, in such a way to balance the operative costs of the service and the passenger waiting time at the transit terminal. We propose two different models for this problem, which present strong similarities with some well known combinatorial optimization models. Computational results are also presented, showing the suitability of the models to solve real case studies.     

Multi-objective optimization of stiffness and workspace for a parallel kinematic machine

This paper presents optimizations of a parallel kinematic manipulator used for a machine tool in terms of its workspace and stiffness. The system stiffness and workspace of the parallel manipulator are conducted in the paper. In order to locate the maximum system stiffness and workspace, single and multi-objective optimizations are performed in terms of rotation angles in x and y axes and translation displacement in z axis with genetic algorithms. By optimizing the design variables including geometric dimensions of the manipulator, the system stiffness and workspace of the proposed parallel kinematic manipulator has been greatly improved.     

考虑转子系统耦合影响的球轴承动态性能多目标优化设计

考虑滚动轴承与转子系统动态性能的耦合影响,使用有限单元法建立包含转轴、轴承、圆盘等单元的动力学方程组,转子响应达到稳定值后,再根据滚动轴承拟动力学模型计算滚动轴承的动态性能参数。以额定动负荷、支承刚度、旋滚比为目标,基于NSGA II遗传算法进行多目标优化设计,分析结构参数对轴承动态性能的影响。以某转子系统的支承轴承为例进行计算,结果表明外圈沟曲率半径系数增大则额定动负荷减小、径向刚度增大、旋滚比增大;内圈沟曲率半径系数增大则额定动负荷减小、径向刚度减小、旋滚比减小;滚动体直径增大则额定动负荷增大、刚度增大、旋滚比增大,内圈沟曲率半径系数变化对动态性能优化结果影响最明显。高速转子系统中,为获取较好的支承动态性能,应考虑耦合影响对支承轴承进行多目标优化设计。     

Multi-objective optimization of water consumption for a methanol synthesis process

Clean Technologies and Environmental Policy - Methanol is an important product in chemical industries, having many applications: solvent, fuel and mainly being a feedstock for a large number of...     

基于代理模型的空投装备气囊缓冲系统多目标优化

基于有限元法和控制体积法建立装备-气囊系统有限元模型,并采用试验数据对模型进行验证。复杂气囊系统着陆缓冲过程仿真计算资源消耗大,难以应用传统迭代方法进行参数优化。为克服这些问题,结合扩展拉丁超立方设计,以最大着陆冲击加速度和最大翻转角度为响应,采用径向基函数构建代理模型。在代理模型基础上,利用多目标遗传算法对主气囊高度、横向宽度及排气孔面积等气囊缓冲系统参数进行了多目标优化。优化结果表明:优化后最大冲击加速度减小了15.5%,最大翻转角度减小了70.3%,缓冲性能与横向稳定性均有所提高。     

公共建筑空调系统节能设计的若干思考

本文结合工程实践经验,详细探讨了影响公共建筑空调系统节能设计主要几个问题,包括空调冷热负荷设计计算重要参数选取,空调冷热源选取模式,以及空调输配水系统等,以供专业人员在工程设计中参考.     

Multi-objective robust optimization design of a front-end underframe structure for a high-speed train

A multi-objective robust design optimization of a front-end underframe structure for application in high-speed trains is proposed and the structural parameter uncertainty is considered. A finite element model of the structure is developed and verified by dynamic impact experiments. The sensitivity analysis demonstrates that the thicknesses of the centre sill have significant influences on structural crushing behaviours. The specific energy absorption and the initial peak crushing force (F_p) are taken as optimization objectives. Compared with the baseline structure, the 6-sigma robust design shows that the F_p and the structural mass are reduced by 54.86% and 13.06%, respectively, and the robust optimum is more reliable. The 6-sigma robust optimal solution has an efficient energy-absorbing capacity while satisfying the design constraint. Thus, 6-sigma robust optimization can be applied for high-speed trains.     

Multi-objective robust design optimization of fatigue life for a welded box girder

To reduce the scatter of fatigue life for welded structures, a robust optimization method is presented in this study based on a dual surrogate modelling and multi-objective particle swam optimization algorithm. Considering the perturbations of material parameters and environment variables, the mean and standard deviation of fatigue life are fitted using dual surrogate modelling and selected as the objective function to be minimized. As an example, a welded box girder is presented to reduce the standard deviation of fatigue life. A set of non-dominated solutions is produced through a multi-objective particle swam optimization algorithm. A cognitive approach is used to select the optimum solution from the Pareto sets. As a comparative study, traditional single objective optimizations are also presented in this study. The results reduced the standard deviation of the fatigue life by about 16.5%, which indicated that the procedure improved the robustness of the fatigue life.     

Development of a flickermeter for grid-connected wind turbines using a DSP-based prototyping system

The measurement of one of the power-quality problems (flicker), which may arise due to the presence of wind-turbine generators, is presented. This paper focuses on the design of a complete fully digital flickermeter relying on an in-house-developed measurement system, which features a data-acquisition system, using a C6711 DSP-based starter kit (DSK) and a field programmable gate array (FPGA). To study flicker produced during the wind turbine's continuous operation, special attention is given to the simulation of the voltage fluctuations on a fictitious grid.     

Multi-objective optimization design using amended particle swarm optimization and Taguchi method for a six-phase copper rotor induction motor

A multi-objective optimization design technique for a six-phase copper rotor induction motor is proposed. The amended particle swarm optimization (PSO) and Taguchi methods combined with finite element analysis are used in this design technique. The objectives in the first-stage optimization are the minimization of manufacturing cost and starting current. In the second-stage optimization, the objectives are the maximization of efficiency, power factor and output torque. The Taguchi method can optimize the machine parameters of performance characteristics in electrical discharge machining. The experimental results are further transformed into the signal-to-noise ratios and amended PSO coefficients based on amended PSO analysis with regard to multiple performance characteristics index values. The results of the optimizations showed significant reduction in terms of the use of magnets as well as improvement in the machine performance. Finally, the experimental results confirm the validity of the proposed optimization design approach.     

Multi-objective design optimization of reconfigurable machine tools: a modified fuzzy-Chebyshev programming approach

A reconfigurable manufacturing system (RMS) is designed for rapid adjustment of functionalities in response to market changes. A RMS consists of a number of reconfigurable machine tools (RMTs) for processing different jobs using different processing modules. The potential benefits of a RMS may not be materialized if not properly designed. This paper focuses on RMT design optimization considering three important yet conflicting factors: configurability, cost and process accuracy. The problem is formulated as a multi-objective model. A mechanism is developed to generate and evaluate alternative designs. A modified fuzzy-Chebyshev programming (MFCP) method is proposed to achieve a preferred compromise of the design objectives. Unlike the original fuzzy-Chebyshev programming (FCP) method which imposes an identical satisfaction level for all objectives regardless of their relative importance, the MFCP respects their priority order. This method also features an adaptive satisfaction-level-dependent process to dynamically adjust objective weights in the search process. A particle swarm optimization algorithm (PSOA) is developed to provide quick solutions. The application of the proposed approach is demonstrated using a reconfigurable boring machine. Our computational results have shown that the combined MFCP and PSOA algorithm is efficient and robust. The advantages of the MFCP over the original FCP are also illustrated based on the results.     

Multi-objective optimization of suspension parameters for rail vehicles based on a virtual prototype surrogate model

This research is intended to develop a suspension parameter optimization approach based on a virtual prototype surrogate model of rail vehicles considering the coupling effects of suspension parameters. In order to analyze the effects on the dynamic indexes, which were affected by the suspension parameters, a virtual prototype model of a rail vehicle was established. The indexes of lateral ride quality and motion stability were obtained under different combinations of suspension parameters by design of experiment and simulation of virtual prototype. For constructing objective function of multi-objective optimization model for suspension parameters, the suspension parameters that have significant effects on ride quality and motion stability simultaneously were taken as the design variables, and thereafter Kriging models of lateral ride quality index, derailment coefficient, and reduction ratio of wheel load were obtained. On this basis, the multi-objective optimization model of suspension parameters was established, in which the objective function was combined with the three Kriging models. Then, the Pareto optimal solution set and concrete value of suspension parameters were sought using the NSGA-II algorithm. The dynamic simulation results indicated that both ride quality and motion stability of the rail vehicle had been improved after the multi-objective optimization of suspension parameters.     

Multi-objective design optimization of functionally graded material for the femoral component of a total knee replacement

The optimal design of complex systems in engineering requires pursuing rigorous mathematical modeling of the system’s behavior as a function of a set of design variables to achieve goal-oriented design. Despite the success of current knee implants, the limited life span remains the main concern of this complex system. The mismatch between the properties of engineered biomaterials and those of biological materials leads to insufficient bonding with bone, stress shielding effects and wear problems (i.e. aseptic loosening). The use of a functionally graded material (FGM) for the femoral component of knee implants is attractive because the properties can be designed to vary in a certain pattern to meet the desired requirements at different regions in the knee joint system, thereby decreasing loosening problem. However, matching the properties does not necessarily guarantee the best functionality of the knee implant and there is a need for developing the optimal design of an FGM femoral component that is longer lasting. In this study, therefore, a multi-objective design optimization of a FGM femoral component is carried out using finite element analysis (FEA) and response surface methodology (RSM). The results of using optimized FGM are then compared with the use of standard Co–Cr alloy in a femoral component knee implant to demonstrate relative performance.     

Magnetic charged system search: a new meta-heuristic algorithm for optimization

An improved version of the charged system search (CSS) algorithm is introduced which is called magnetic charged system search (MCSS). In the new algorithm, magnetic forces are considered in addition to electrical forces, using the Biot–Savart law. Each charged particle (CP), as a search agent, exerts magnetic forces on other CPs based on the variation of its objective function value during its last movement and its distance between other CPs. This additional force provides useful information for the optimization process and enhances the performance of the CSS algorithm. The efficiency of the MCSS is examined by application of this algorithm to well-known mathematical benchmarks and three well-studied engineering design problems. The results are compared to those of the CSS, and the improvements are highlighted.     

A system dynamics-based decision-making tool and strategy optimization simulation of green building development in China

Clean Technologies and Environmental Policy - Green building has emerged as a new type of building to mitigate the conflict between the rapid expansion of buildings and the deteriorating ecological...     

Performance characterisation of a small milk cooling system with ice storage for PV applications

The presented work proposes a calculation method to estimate the transient performance of a small on-farm milk cooling system for PV applications. The system employs 3 kg ice for fast cooling of 17 L milk in conventional 20-L-milk-cans. Two units of a commercial DC refrigerator operate at −10 °C and at 4 °C for ice production and milk preservation respectively. The development of milk temperature and energy consumption during a cooling event was studied experimentally at different ambient temperatures of 20 °C, 30 °C and 40 °C. A computational model was developed and validated where thermal resistances and COP were adjusted with experimental data. The results between 20 °C and 40 °C ambient temperature show a COP reduction of around 30% and a total daily energy consumption increase of around 100%. The specific total energy consumption of the system per litre milk was between 30 Wh/L and 58 Wh/L for the studied ambient temperature range. The suggested model can be used for the optimisation of photovoltaic stand-alone systems at specific locations.     

Joint optimization of maintenance and inventory policies for a simple system

We examine age replacement and ordering decisions for a system with only one component subject to random failure and with room for only one spare in stock. The system incurs costs for replacement, shortage, holding, and breakage; the lead time for receipt of an ordered spare is constant. We consider the solvability and desirability of jointly optimizing these two traditionally separate decisions. We show that the problem has some convexity properties that make it amenable to minimization. For our data set, we find that using separate optimization gives an average loss of 3% relative to the joint minimum; about a tenth of die time the difference was more than 10%, but in general this loss can vary from zero to arbitrarily large.