Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried out.This has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the day-aheadmarket.The standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight technique.The proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PSO),and salp swarm algorithm(SSA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub limitations.Additionally,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.

HIGH ACCURACY FINITE VOLUME ELEMENT METHOD FOR TWO-POINT BOUNDARY VALUE PROBLEM OF SECOND ORDER ORDINARY DIFFERENTIAL EQUATIONS

In this paper, a high accuracy finite volume element method is presented for two-point boundary value problem of second order ordinary differential equation, which differs from the high order generalized difference methods. It is proved that the method has optimal order error estimate O(h3) in H1 norm. Finally, two examples show that the method is effective.

Fitting method of pseudo-polynomial for solving nonlinear parametric adjustment

The optimal condition and its geometrical characters of the least square adjustment were proposed. Then the relation between the transformed surface and least squares was discussed. Based on the above, a non iterative method, called the fitting method of pseudo polynomial, was derived in detail. The final least squares solution can be determined with sufficient accuracy in a single step and is not attained by moving the initial point in the view of iteration. The accuracy of the solution relys wholly on the frequency of Taylor’s series. The example verifies the correctness and validness of the method. [

A SPARSITY AND COMPRESSION RATIO JOINT ADJUSTMENT METHOD FOR COLLABORATIVE SPECTRUM SENSING

Spectrum sensing is the fundamental task for Cognitive Radio (CR). To overcome the challenge of high sampling rate in traditional spectral estimation methods, Compressed Sensing (CS) theory is developed. A sparsity and compression ratio joint adjustment algorithm for compressed spectrum sensing in CR network is investigated, with the hypothesis that the sparsity level is unknown as priori knowledge at CR terminals. As perfect spectrum reconstruction is not necessarily required during spectrum detection process, the proposed algorithm only performs a rough estimate of sparsity level. Meanwhile, in order to further reduce the sensing measurement, different compression ratios for CR terminals with varying Signal-to-Noise Ratio (SNR) are considered. The proposed algorithm, which optimizes the compression ratio as well as the estimated sparsity level, can greatly reduce the sensing measurement without degrading the detection performance. It also requires less steps of iteration for convergence. Corroborating simulation results are presented to testify the effectiveness of the proposed algorithm for collaborative spectrum sensing.

Big-M based MILP method for SCUC considering allowable wind power output interval and its adjustable conservativeness

In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable wind power output interval and its adjustable conservativeness.The wind power accommodation capability is usually limited by spinning reserve requirements and transmission line capacity in power systems with large-scale wind power integration.Therefore,by employing the big-M method and adding auxiliary 0-1 binary variables to describe the allowable wind power output interval,a bilinear programming problem meeting the security constraints of system operation is presented.Furthermore,an adjustable confidence level was introduced into the proposed robust optimization model to decrease the level of conservatism of the robust solutions.This can establish a trade-off between economy and security.To develop an MILP problem that can be solved by commercial solvers such as CPLEX,the big-M method is utilized again to represent the bilinear formulation as a series of linear inequality constraints and approximately address the nonlinear formulation caused by the adjustable conservativeness.Simulation studies on a modified IEEE 26-generator reliability test system connected to wind farms were performed to confirm the effectiveness and advantages of the proposed method.

Research on the adjustment model of ventilation characteristic parameters based on integrated method of circuit and path

Ventilation characteristic parameters are the base of ventilation network solution; however, they are apt to be affected by operating errors, reading errors, airflow stability, and other factors, and it is difficult to obtain accurate results. In order to check the ventilation characteristic parameters of mines more accurately, the integrated method of circuit and path is adopted to overcome the drawbacks caused by the traditional path method or circuit method in the digital debugging process of ventilation system, which can improve the large local error or the inconsistency between the airflow direction and the actual situation caused by inaccuracy of the ventilation characteristic parameters or checking in the ventilation network solution. The results show that this method can effectively reduce the local error and prevent the pseudo-airflow reversal phenomenon; in addition, the solution results are consistent with the actual situation of mines, and the effect is obvious.

A Two-Point Boundary Value Problem by Using a Mixed Finite Element Method

This paper describes a numerical solution for a two-point boundary value problem. It includes an algorithm for discretization by mixed finite element method. The discrete scheme allows the utilization a finite element method based on piecewise linear approximating functions and we also use the barycentric quadrature rule to compute the stiffness matrix and the L2-norm.

PTSD Outcome,Adjustment Disorder and Methods of Treatment

This research is pointed up on“Adjustment disorder and adaptation with anxiety,stress and depression following the catastrophic life events”.We explained the results of psychopathological and psychosocial effects of post-traumatic stress disorder(PTSD),especially depression and anxiety caused by catastrophic stressful life events or other factors(war,terrorist acts,etc.),and then discussed and presented different methods and forms of treatments.Our theoretical studies,in the fields of PTSD-Psychogeriatry and Psychiatry in one side and different Seminars in Paris etc.in other side,have completed this research;the studies at the University of Illinois,as full time Prof.are developed in this working research.Anxiety disorders,depression and stresses are not a new phenomenon in the field of psychiatry,they have existed several years B.C.,but their aetiology and physiopathology were not clear.Moreover,the treatments were on the basis of some medical plants or traditional and local methods which existed yet,more or less in some African or Asiatic countries,the hospitals for mental disorders had been limited;in plus,environmental factors,also heredity,quality of life and the degree of the vulnerability of individuals and the capacity of the patients to cope with the pain.etc were neglected.In our time,because of multifactorial reasons,anxiety disorders and depression,which are often accompanied by obsessive-compulsive disorders,are the most prevalent pathology in Psychiatry that we discussed in this paper(Figure 1).Actually,because of the global COVID-19 pandemic,the frequency of depression and anxiety disorders,according to the global news and audio-visual information,are significantly increased.Our teaching experiences,also clinical researches and observations in the Mental Health Centres showed clearly that in extreme cases when major depression and anxiety are accumulating and occur to coexist together,they can exert serious pathological effects not only on the cardiovascular system and endocrine glands but also on the cognitive system more particularly on flexibility,memory,creativity and attention(Figure 2);moreover,the coexistence of anxiety and a psychiatric condition can produce not only cognitive disorder,but in some cases-ex.inability to cope with pain or inadaptability to stress,may hasten and intensify ageing process.In many cases as shown,the anxious subjects,when confronted to psychosocial crisis,feel fear and expect to be facing to adverse events or catastrophic situations and believe to live negative future events;in plus,exhibit emotional distress,repetitive dreams and severe insomnia.In these cases,according to our experiences,in parallel to pharmacotherapy,the relaxation and complete massages in one side,physical education,meditation,positive emotion and muscular release etc.in other side,are useful to help these patients for a best control of emotional distress and relatively reduce anxiety and depression.We add that the syndrome of stress,depression and anxiety has been recognized not only in the different victims of war,but also in the non-war(cf.other factors noted in this paper:fig.1)traumatized population.

A two-parameter multiple shooting method and its application to the natural vibrations of non-prismatic multi-segment beams

This paper presents an enhanced version of the standard shooting method that enables problems with two unknown parameters to be solved.A novel approach is applied to the analysis of the natural vibrations of Euler-Bernoulli beams.The proposed algorithm,named as two-parameter multiple shooting method,is a new powerful numerical tool for calculating the natural frequencies and modes of multi-segment prismatic and non-prismatic beams with different boundary conditions.The impact of the axial force and additional point masses is also taken into account.Due to the fact that the method is based directly on the fourth-order ordinary differential equation,the structures do not have to be divided into many small elements to obtain an accurate enough solution,even though the geometry is very complex.To verify the proposed method,three different examples are considered,i.e.,a three-segment non-prismatic beam,a prismatic column subject to non-uniformly distributed compressive loads,and a two-segment beam with an additional point mass.Numerical analyses are carried out with the software MATHEMATICA.The results are compared with the solutions computed by the commercial finite element program SOFiSTiK.Good agreement is achieved,which confirms the correctness and high effectiveness of the formulated algorithm.

Efficient Decomposition Shooting Method for Solving Third-Order Boundary Value Problems

The present paper proposes a mathematical method to numerically treat a class of third-order linear Boundary Value Problems (BVPs). This method is based on the combination of the Adomian Decomposition Method (ADM) and, the modified shooting method. A complete derivation of the proposed method has been provided, in addition to its numerical implementation and, validation via the utilization of the Runge-Kutta method and, other existing methods. The method has been applied to diverse test problems and turned out to perform remarkably. Lastly, the simulated numerical results have been graphically illustrated and, also supported by some absolute error comparison tables.

地下工程竖井定向连接四边形法最优图形分析

为了提高地下工程竖井定向精度,阐释了连接四边形法竖井定向方法,用一个角和一条边为参数确定对称四边形,构建了连接四边形严密平差模型,采用间接平差进行网形精度评估。编写程序遍历条件角和条件边计算定向边精度,绘制等值线,定量分析连接四边形法最优图形。该研究对于地下工程竖井定向具有实际应用价值。

THE AUTO-ADJUSTABLE DAMPING METHOD FORSOLVING NONLINEAR EQUATIONS

The general approach for solving the nonlinear equations is linearizing the equations and forming various iterative procedures, then executing the numerical simulation. For the strongly nonlinear problems, the solution obtained in the iterative process is always difficult, even divergent due to the numerical instability. It can not fulfill the engineering requirements. Newton's method and its variants can not settle this problem. As a result, the application of numerical simulation for the strongly nonlinear problems is limited. An auto-adjustable damping method has been presented in this paper. This is a further improvement of Newton's method with damping factor. A set of vector of damping factor is introduced. This set of vector can be adjusted continuously during the iterative process in accordance with the judgement and adjustment. An effective convergence coefficient and quichening coefficient are employed to relax the restricted requirements for the initial values and to shorten the iterative process. Then, the numerical stability will be ensured for the solution of complicated strongly nonlinear equations. Using this method, some complicated strongly nonlinear heat transfer problems in airplanes and aeroengines have been numerically simulated successfully. It can be used for the numerical simulation of strongly nonlinear problems in engineering such as nonlinear hydrodynamics and aerodynamics, heat transfer and structural dynamic response etc.

育人为本在结构化学教学中的探索与实践

结构化学是化学专业的专业基础必修课,从微观角度探讨原子、分子和晶体结构,建立微观结构与宏观性能之间的关系,其教学内容较抽象、学生较难理解,且教学时数较少,因此有必要对教学内容进行合理的调整与整合、适当增减知识点、结合多种教学手段并注重教研相长,以期培养学生学习结构化学的兴趣,并激发创新能力。此外,在传授结构化学专业知识的同时将思政元素融入课堂,培养学生家国情怀、创新意识和社会责任感。这些教学措施充分体现了育人为本在结构化学教学中的探索与实践,从而实现立德树人、知识传授和能力培养融为一体,促进科学教育和人文教育的有效融合。

高洁净度超光滑非球面的自动化干涉检测方法

为了实现应用于高能激光等领域对表面洁净度有着极高要求的超光滑非球面检测,排除检测人员带来的洁净度与空气扰动的影响,研究了高洁净度超光滑非球面的自动化干涉检测方法。通过建立补偿干涉法非球面失调量与波前像差之间的灵敏度矩阵,实现利用波前像差求解被测非球面失调量。以理想干涉系统的离焦、彗差与像散为优化目标,进行反馈控制,实现被测非球面的自动化调整,进而实现高洁净度超光滑非球面的自动化干涉检测。实验结果表明,在干涉图可测范围内,利用灵敏度矩阵通过几步迭代即可实现非球面失调量的收敛。结合Stewart六自由度调整台,分别实现2μm精度的平移误差调整、2"精度的光轴自动化对准,最终完成被测非球面的精密调整,实现高洁净度超光滑非球面的自动化干涉检测。采用灵敏度矩阵与六自由度调整的非球面自动化干涉检测方法可实现被测非球面失调量的快速求解与自动调整,降低人员和环境带来的扰动影响,提高了非球面的检测速度,并实现了高洁净度超光滑非球面的自动化干涉检测。

DIP支付方式下医保供给侧政策协同对费用控制的影响研究

目的:本研究旨在探索DIP支付方式与其他医保供给侧政策间的协同效果。方法:以全国DIP改革试点城市A市为处理组,未改革城市B市为对照组进行比较研究。收集2019—2022年共1120个公立医疗机构样本,采用双重差分法对住院医疗总费用及部分费用结构进行分析。结果:A市DIP改革对医疗机构住院医疗总费用、住院检查化验总费用产生显著的抑制效应,对住院药品总费用和住院材料总费用未产生影响。结论:DIP支付方式发挥显著控费效果,住院医疗总费用得到有效控制;单纯采取调价政策与集采政策的控费效果尚有不足;DIP与其他供给侧政策协同,促进医疗费用结构更加合理。建议医保部门注重发挥供给侧政策协同作用,共同推动医保基金使用效率提升。

子午流注法穴位贴敷联合视力调节训练对儿童青少年低度近视的影响研究

目的:探讨子午流注法穴位贴敷联合视力调节训练对儿童青少年低度近视的影响。方法:选取2022年12月~2023年12月于我院接受治疗的100例患者进行研究。分组方法选择随机数字表法,分成两组各50例。对照组接受常规视力调节训练,观察组在此基础上接受子午流注法穴位贴敷干预。比较两组患儿的治疗效果以及干预前后裸眼远视力、屈光度、不同动脉的血流平均值、眼球生物测量参数检测结果的变化情况。结果:观察组治疗总有效率为96.00%,高于对照组的78.00%,统计学结果有显著差异(P<0.05);观察组干预后裸眼远视力高于对照组干预后,统计学结果有显著差异(P<0.05);观察组干预后基底动脉(BA)、左侧椎动脉(LVA)、右侧椎动脉(RVA)血流平均值均高于对照组干预后,统计学结果有显著差异(P<0.05);观察组干预后眼轴低于对照组干预后,中央角膜厚度高于对照组干预后,统计学结果有显著差异(P<0.05)。结论:在视力调节训练基础上实施子午流注法穴位贴敷能够提升儿童青少年低度近视的治疗效果,改善患儿视功能,值得临床推荐。

改进迭代贪婪算法求解可重入流水车间调度问题

可重入混合流水车间是在混合流水车间的基础上增加了可重入特性,具有更高的调度复杂性。为了求解可重入混合流水车间调度问题,首先建立了调度优化模型,优化目标为最小化最大完工时间,然后提出一种带精英调整的学习型迭代贪婪算法(LIG-EA)。LIG-EA算法采用基于工件的编码方式,对重组后的染色体进行解码。种群分为精英个体和普通个体两部分,对精英个体进行精英破坏重建和基于关键工件的染色体调整,对普通个体进行学习机制的构建和普通个体的破坏重建。为提高初始种群质量,采用NEH启发式算法进行种群初始化,并针对可重入混合流水车间的重入特性,在重建操作中增加了插入有效性判断,提高了算法的运行速度。通过大量实验表明LIG-EA算法能够有效求解可重入混合流水车间调度问题。

高精度管道漏风量测试仪的设计及实验研究

现有的国产漏风量测试仪普遍存在测量精度低、自动化水平低的问题,为此,基于漏风量测试仪的原理,开展了漏风量测试仪的结构设计、系统设计及整机实验研究。首先,对漏风量的测量过程、喷嘴流量测量原理进行了研究,推导了喷嘴流量测量公式,并根据相关标准设计了角接取压方式的喷嘴结构,基于仪器操作便捷性要求,对整机结构进行了设计;其次,采用空气密度补偿公式完成了高精度流量自适应测量,设计了基于自锁式电磁阀的换向调零电路,采用换向调零法对压差传感器零点漂移进行了补偿,使用小波阈值去噪算法消除了信号噪声,提高了流量的测量精度;采用抗积分饱和比例积分微分(PID)算法对流量进行了闭环控制;最后,研制了管道漏风量测试仪样机,开展了压差与流量测量精度与重复性实验。实验及研究结果表明:该高精度漏风量测试仪工作状态稳定,压差测量精度为±0.4%,流量测量精度为±2%;该漏风量测试仪的测量精度优于国内同类仪器,符合国家标准要求,具有良好的市场前景。

基于点估计仿射可调鲁棒优化的含储能电力系统实时调度

为应对大规模风电的接入,建立一种机组与储能联合参与自动发电控制的电力系统实时调度模型,并提出一种点估计仿射可调鲁棒优化来处理风电不确定性。不同于传统仿射可调鲁棒调度优化基准运行成本,点估计仿射可调鲁棒调度优化期望运行成本以提高系统经济性。提出利用确定性的点估计法来实现对期望运行成本的快速、精确评估。所提模型为一混合整数双线性约束问题,采用一种“预估-矫正”的凸化方法来求解该难题,预估阶段对储能的状态变量进行松弛,而矫正阶段直接对其状态变量进行矫正。最后,引入一种凸函数差优化进一步凸化2个阶段的双线性约束问题,以提高含储能实时调度的求解质量。在IEEE39、118以及300节点3个系统的仿真验证了所提模型及方法的有效性。