Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations.To accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response capabilities.Firstly,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation resources.On this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation capabilities.Secondly,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within clusters.Simultaneously,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of resources.This model can provide scientific guidance for the economic dispatch of the distribution station area.Finally,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of the distribution station area.

Optimized CUDA Implementation to Improve the Performance of Bundle Adjustment Algorithm on GPUs

The 3D reconstruction pipeline uses the Bundle Adjustment algorithm to refine the camera and point parameters. The Bundle Adjustment algorithm is a compute-intensive algorithm, and many researchers have improved its performance by implementing the algorithm on GPUs. In the previous research work, “Improving Accuracy and Computational Burden of Bundle Adjustment Algorithm using GPUs,” the authors demonstrated first the Bundle Adjustment algorithmic performance improvement by reducing the mean square error using an additional radial distorting parameter and explicitly computed analytical derivatives and reducing the computational burden of the Bundle Adjustment algorithm using GPUs. The naïve implementation of the CUDA code, a speedup of 10× for the largest dataset of 13,678 cameras, 4,455,747 points, and 28,975,571 projections was achieved. In this paper, we present the optimization of the Bundle Adjustment algorithm CUDA code on GPUs to achieve higher speedup. We propose a new data memory layout for the parameters in the Bundle Adjustment algorithm, resulting in contiguous memory access. We demonstrate that it improves the memory throughput on the GPUs, thereby improving the overall performance. We also demonstrate an increase in the computational throughput of the algorithm by optimizing the CUDA kernels to utilize the GPU resources effectively. A comparative performance study of explicitly computing an algorithm parameter versus using the Jacobians instead is presented. In the previous work, the Bundle Adjustment algorithm failed to converge for certain datasets due to several block matrices of the cameras in the augmented normal equation, resulting in rank-deficient matrices. In this work, we identify the cameras that cause rank-deficient matrices and preprocess the datasets to ensure the convergence of the BA algorithm. Our optimized CUDA implementation achieves convergence of the Bundle Adjustment algorithm in around 22 seconds for the largest dataset compared to 654 seconds for the sequential implementation, resulting in a speedup of 30×. Our optimized CUDA implementation presented in this paper has achieved a 3× speedup for the largest dataset compared to the previous naïve CUDA implementation.

Improving Accuracy and Computational Burden of Bundle Adjustment Algorithm Using GPUs

Bundle adjustment is a camera and point refinement technique in a 3D scene reconstruction pipeline. The camera parameters and the 3D points are refined by minimizing the difference between computed projection and observed projection of the image points formulated as a non-linear least-square problem. Levenberg-Marquardt method is used to solve the non-linear least-square problem. Solving the non-linear least-square problem is computationally expensive, proportional to the number of cameras, points, and projections. In this paper, we implement the Bundle Adjustment (BA) algorithm and analyze techniques to improve algorithmic performance by reducing the mean square error. We investigate using an additional radial distortion camera parameter in the BA algorithm and demonstrate better convergence of the mean square error. We also demonstrate the use of explicitly computed analytical derivatives. In addition, we implement the BA algorithm on GPUs using the CUDA parallel programming model to reduce the computational time burden of the BA algorithm. CUDA Streams, atomic operations, and cuBLAS library in the CUDA programming model are proposed, implemented, and demonstrated to improve the performance of the BA algorithm. Our implementation has demonstrated better convergence of the BA algorithm and achieved a speedup of up to 16× on the use of the BA algorithm on various datasets.

Experimental Investigation and Optimization Design of Multi-Support Pipeline System

The design of aircraft hydraulic pipeline system is limited by many factors,such as the integrity of aviation structure or narrow installation space,so the limited clamp support position should be considered.This paper studied the frequency adjustment and dynamic responses reduction of the multi-support pipeline system through experiment and numerical simulation.To avoid the resonance of pipeline system,we proposed two different optimization programs,one was to avoid aero-engine working range,and another was to avoid aircraft hydraulic pump pulsation range.An optimization method was introduced in this paper to obtain the optimal clamp position.The experiments were introduced to validate the optimization results,and the theoretical optimization results can agree well with the test.With regard to avoiding the aero-engine vibration frequency,the test results revealed that the first natural frequency was far from the aero-engine vibration frequency.And the dynamic frequency sweep results showed that no resonance occurred on the pipeline in the engine vibration frequency range after optimization.Additionally,with regard to avoiding the pump vibration frequency,the test results revealed that natural frequencies have been adjusted and far from the pump vibration frequency.And the dynamic frequency sweep results showed that pipeline under optimal clamp position cannot lead to resonance.The sensitivity analysis results revealed the changing relationships between different clamp position and natural frequency.This study can provide helpful guidance on the analysis and design of practical aircraft pipeline.

Study on the Optimization for Design of Indoor Natural Ventilation and Lighting Based on Passive Design Measurements

Based on the current indoor natural ventilation and lighting in the space of traditional residential buildings,this paper starts from the passive-design optimization of the spatial natural ventilation and lighting,and makes quantitative evaluation on the quality of current interior natural ventilation and lighting for two typical residential buildings by three indexes,including wind speed,static wind area ratio and satisfaction ratio about minimum lighting coefficient. Based on that, this paper conducts the passive design optimization, and establishes the quantitative association and reevaluation among the passive reformation design, natural ventilation,and lighting environmental quality,proposing the general strategy for the existing residential buildings to respond to the passive reformation design of the natural ventilation and lighting. The special reconstruction of core functionary space of integration of "the living room + dining room + partial space"is researched,and the redesign for the optimization and replacement of both indoor and outdoor enclosure parts is explored,which is expected to provide practical exploration on the strategies for passive construction of spatial natural environmental quality within a large number of highly-energy-consumed residential buildings in China,as well as the green design of residential buildings.

Study of the Optimization and Adjustment ofthe IndustrialStructure Subjected to Water Resource in the Drainage Area of the Yellow River

Since the 1990s, the Yellow River stream has been temporarily interrupted for several years, which affects the development of society, the economy and human life, limits the economic potential of the drainage areas, and especially causes great harm to regions on the lower reaches. Based on the analysis of the relationship between the development of society and economy and water scarcity, the author thinks it is necessary to optimize and adjust the industrial structure that has extravagantly consumed enormous amounts of water, and to develop ecological agriculture, industry and tourism which are balanced with the ecological environment. Finally, the author puts forward several pieces of advice and countermeasures about how to build the economic systems by which water can be used economically.

Ventilation Structure Optimization and Performance Analyses of Permanent Magnet Wind Generators

为了提高永磁风力发电机的通风冷却效果,以一台2.5 MW永磁风力发电机为例,基于计算流体力学（computational fluid dynamics,CFD）以及传热传质学基本理论,根据流–热协同机理,建立了包括外部通风系统的三维流体流动与传热的求解模型。应用有限体积元法,对电机通风冷却性能进行了数值研究,并与实验数据进行对比分析,实验结果验证了计算结果的准确性以及求解方法的合理性。通过改变电机内径向通风沟结构尺寸,提出4种优化方案,通过对不同结构方案条件下通风冷却性能进行对比研究,给出了发电机最佳的结构方案。所得结论可以为永磁风力发电机通风结构的设计提供参考。

Adjustment and Optimization of Public Art to the Folk Psychology

Public art has practical significance by showing a variety of forms to explore the various design factors on the psychological reactions of different people. Public art should fit the characteristics of human physiology and psychology. The mental aberration phenomenon induced by unhealthy circumstance could be adjusted and compensated by certain style of public art, and from which the optimization of psychological ecology is resulted. A variety of psychological ecology environment, such as gestalt, artistic exaggeration, implicit, pleasure, interesting, relax, mystery, intricacy, metaphor, and so on, could be constructed by different methods in public art. The excellent public art design optimizes the person's mental spiritual ecology, reduces the burden on people's lives and enhances the quality of life by using the meaningful forms and combinations to achieve the living environment and people's coordination.

PSO算法下GP-周期随机共振的微弱OFDM信号检测

为了解决传统随机共振系统在微弱正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)信号解调应用中存在的人工选择参数困难、解调效果差的问题,提出一种基于粒子群优化(Particle Swarm Optimization,PWO)算法的GP(Gaussian Potential)-周期随机共振系统的微弱OFDM信号检测方法。该方法利用GP-周期随机系统对OFDM信号经正交变换后的两路高频信号分别进行随机共振,同时运用阻尼参数与信号频率之间的关系对两路信号进行降频处理,使得上下两路信号都能够发生随机共振;然后使用PWO算法对随机共振的系统参数进行优化处理,以使得上下两路信号达到最优的共振效果;最后,将上下两路共振之后的信号合成完成OFDM信号解调,得到最终的数字序列。本文探讨了优化前后GP-周期随机共振系统的共振效果,研究了优化前后GP-周期随机共振诱导下的OFDM系统星座图的聚集程度以及误码率情况,对比分析了经典双稳随机共振、经典三稳随机共振和所提模型对OFDM信号检测的影响。仿真结果表明:相比常用的传统随机共振模型,该方法用于OFDM信号检测的星座图中信号点的聚集程度更高,同时OFDM系统误码率在同样的信噪比下降低50%左右。

A modified model for concurrent topology optimization of structures and materials

This paper presents a study on the concur- rent topology optimization of a structure and its material microstructure. A modified optimization model is proposed by introducing microstructure orientation angles as a new type of design variable. The new model is based on the assumptions that a structure is made of a material with the same microstructure, and the material may have a different orientation within the design domain of the structure. The homogenization theory is applied to link the material and structure scales. An additional post-processing technique is developed for modifying the obtained design to avoid local optima caused by the use of orientation angle variables. Numerical examples are presented to illustrate the viabil- ity and effectiveness of the proposed model. It is found that significant improvement in structural performance can be achieved by optimizing the orientation of microstructures in concurrent topology optimization of structures and materials.

The Optimal Solution of the Model with Physical and Human Capital Adjustment Costs

We prove that the model with physical and human capital adjustment costs has optimal solution when the production function is increasing return and the structure of vetor fields of the model changes substantially when the prodution function from decreasing return turns to increasing return. And it is shown that the economy is improved when the coefficients of adjustment costs become small. Key words optimal solution - nonzero equilibrium - adjustment costs CLC number O 29 Foundation item: Supported by the National Natural Science Foundation of China (79970104)Biography: RAO Lan-lan (1978-), female, Master candidate, research direction: mathematical economy.

Hybrid genetic algorithm for the optimization of mine ventilation network

Used genetic algorithm (GA) to optimize the network of ventilation in order toavoid artificial convergence and speed up the convergence rate to introduce the Powellalgorithm. The Powell algorithm had been integrated into GA. Powell had the effectivecapacity of solving the local optimal solution. Powell and the cross as a method ofchoice, a variation of the parallel operator, can be a better solution to the prematureconvergence of the GA problem. The two methods will be improved to make it an effective combination of hybrid GA called hybrid genetic algorithm (HGA) for the introductionof mine ventilation network optimization and to be used to solve the problem of regulating mine optimization.

Temperature-Based Fan Speed Optimization Strategy

As energy efficiency and indoor comfort increasingly become key standards in modern residential and office environments,research on intelligent fan speed control systems has become particularly important.This study aims to develop a temperature-feedback-based fan speed optimization strategy to achieve higher energy efficiency and user comfort.Firstly,by analyzing existing fan speed control technologies,their main limitations are identified,such as the inability to achieve smooth speed transitions.To address this issue,a BP-PID speed control algorithm is designed,which dynamically adjusts fan speed based on indoor temperature changes.Experimental validation demonstrates that the designed system can achieve smooth speed transitions compared to traditional fan systems while maintaining stable indoor temperatures.Furthermore,the real-time responsiveness of the system is crucial for enhancing user comfort.Our research not only demonstrates the feasibility of temperature-based fan speed optimization strategies in both theory and practice but also provides valuable insights for energy management in future smart home environments.Ultimately,this research outcome will facilitate the development of smart home systems and have a positive impact on environmental sustainability.

Study on Injection-Production System Adjustment of Fault Block Reservoir Based on Equilibrium Displacement

This paper proposed a method of injection-production system adjustment to solve the problem that the water flooding effect was restricted because of the horizontal and vertical contradictions during the development process of fault block reservoirs. Considering the heterogeneity of reservoir, the Buckley-Leverett water flooding theory was applied to establish the relationship between the recovery and cumulative water injection. In order to achieve the goal of vertically balanced recovery of each section, the calculation method of vertical sectional injection allocation was proposed. The planar triangular seepage unit was assumed and sweep coefficients of different oil-water distribution patterns were characterized using multi-flow tube method. In order to balance and maximize the plane sweep coefficient, the calculation method of plane production system optimization was obtained. Then the injection-production system stereoscopic adjustment method based on equilibrium displacement was proposed with vertical sectional injection allocation and plane production system optimization. This method was applied to injection and production adjustment of BZ oilfield in southern Bohai. The effect of water control and oil increase was obvious. This method can greatly improve the effect of water flooding of offshore fault block reservoirs with the adjustment of injection-production system.

Analysis of Mine Ventilation Network Using Genetic Algorithm

目的在给定的网络拓扑和风巷特征条件下求解风流分配和压力分布以及风机的工况点．方法采用遗传算法寻求自然分风条件下矿井通风网络的全局最优解．结果提出了一种改进的遗传算法．采用实值对交叉算子和变异算子编码，从两组可行解中选优产生新一代群体，从而避免算法陷入早期收敛．结论实例计算结果表明，遗传算法用于矿井通风网络分析，无论是收敛迭代次数，还是网络的全局最优解。

A structural topological optimization method for multi-displacement constraints and any initial topology configuration

In density-based topological design, one expects that the final result consists of elements either black （solid material） or white （void）, without any grey areas. Moreover, one also expects that the optimal topology can be obtained by starting from any initial topology configuration. An improved structural topological optimization method for multidisplacement constraints is proposed in this paper. In the proposed method, the whole optimization process is divided into two optimization adjustment phases and a phase transferring step. Firstly, an optimization model is built to deal with the varied displacement limits, design space adjustments, and reasonable relations between the element stiffness matrix and mass and its element topology variable. Secondly, a procedure is proposed to solve the optimization problem formulated in the first optimization adjustment phase, by starting with a small design space and advancing to a larger deign space. The design space adjustments are automatic when the design domain needs expansions, in which the convergence of the proposed method will not be affected. The final topology obtained by the proposed procedure in the first optimization phase, can approach to the vicinity of the optimum topology. Then, a heuristic algorithm is given to improve the efficiency and make the designed structural topology black/white in both the phase transferring step and the second optimization adjustment phase. And the optimum topology can finally be obtained by the second phase optimization adjustments. Two examples are presented to show that the topologies obtained by the proposed method are of very good 0/1 design distribution property, and the computational efficiency is enhanced by reducing the element number of the design structural finite model during two optimization adjustment phases. And the examples also show that this method is robust and practicable.

Optimized model-based control of main mine ventilation air flows with minimized energy consumption

In early 2018,the Boliden Garpenberg operation implemented an optimized control strategy as an addition to the existing ventilation on demand system.The purpose of the strategy is to further minimize energy use for main and booster fans,whilst also fulfilling airflow setpoints without violating constraints such as min/max differential pressure over fans and interaction of air between areas in mines.Using air flow measurements and a dynamical model of the ventilation system,a mine-wide coordination control of fans can be carried out.The numerical model is data driven and derived from historical operational data or step changes experiments.This makes both initial deployment and lifetime model maintenance,as the mine evolves,a comparably easy operation.The control has been proven to operate in a stable manner over long periods without having to re-calibrate the model.Results prove a 40%decrease in energy use for the fans involved and a greater controllability of air flow.Moreover,a 15%decrease of the total air flow into the mine will give additional proportional heating savings during winter periods.All in all,the multivariable controller shows a correlation between production in the mine and the ventilation system performance superior to all of its predecessors.