Modified neo-fuzzy neuron-based approach for economic and environmental optimal power dispatch

At the central energy management center in a power system, the real time controls continuously track the load changes and endeavor to match the total power demand with total generation in such a manner that the operating cost is minimized while all the operating constraints are satisfied. However, due to the strict government regulations on environmental protection, operation at minimum cost is no longer the only criterion for dispatching electrical power. The idea behind the environmentally constrained economic dispatch formulation is to estimate the optimal generation schedule of generating units in such a manner that fuel cost and harmful emission levels are both simultaneously minimized for a given load demand. Conventional optimization techniques become very time consuming and computationally extensive for such complex optimization tasks. These methods are hence not suitable for on-line use. Neural networks and fuzzy systems can be trained to generate accurate relations among variables in complex non-linear dynamical environment, as both are model-free estimators. The existing synergy between these two fields has been exploited in this paper for solving the economic and environmental dispatch problem on-line. A multi-output modified neo-fuzzy neuron (NFN), capable of real time training is proposed for economic and environmental power generation allocation.This model is found to achieve accurate results and the training is observed to be faster than other popular neural networks. The proposed method has been tested on medium-sized sample power systems with three and six generating units and found to be suitable for on-line combined environmental economic dispatch (CEED).     

钢筋混凝土梁的优化设计

针对钢筋混凝土结构承载力和工程造价要求,采用罚函数法,对钢筋混凝土梁的截面尺寸和钢筋的用量进行优化设计.提出了采用矩阵实验室(MATLAB)优化工具箱的方法,对C20到C40混凝土和HRB335,HRB400钢筋进行多种组合.结果显示在满足承载力要求及规范所规定的构造要求条件下,选用C35和HRB400为最经济的设计方案.     

Optimal error estimates of the penalty method for the linearized viscoelastic flows

In this article, optimal error estimates of the penalty method for the linearized viscoelastic flows equations arising in the Oldroyd model are derived. Furthermore, error estimates for the backward Euler time discretization scheme in L ² and H ¹-norms are obtained.     

Absolute penalty and shrinkage estimation in partially linear models

In the context of a partially linear regression model, shrinkage semiparametric estimation is considered based on the Stein-rule. In this framework, the coefficient vector is partitioned into two sub-vectors: the first sub-vector gives the coefficients of interest, i.e., main effects (for example, treatment effects), and the second sub-vector is for variables that may or may not need to be controlled. When estimating the first sub-vector, the best estimate may be obtained using either the full model that includes both sub-vectors, or the reduced model which leaves out the second sub-vector. It is demonstrated that shrinkage estimators which combine two semiparametric estimators computed for the full model and the reduced model outperform the semiparametric estimator for the full model. Using the semiparametric estimate for the reduced model is best when the second sub-vector is the null vector, but this estimator suffers seriously from bias otherwise. The relative dominance picture of suggested estimators is investigated. In particular, suitability of estimating the nonparametric component based on the B-spline basis function is explored. Further, the performance of the proposed estimators is compared with an absolute penalty estimator through Monte Carlo simulation. Lasso and adaptive lasso were implemented for simultaneous model selection and parameter estimation. A real data example is given to compare the proposed estimators with lasso and adaptive lasso estimators.     

网球比赛判罚中鹰眼技术运用探讨

在网球比赛越来越广泛的使用鹰眼判罚技术的今天,关于鹰眼技术运用点利与弊的问题已经展开过很多次的讨论。虽然至今为止还没有达成一个明确点统一的共识,但是在鹰眼技术引入赛场将近五年后的今天,我们再一次的对鹰眼技术的运用情况展开一次讨论,结合专业网球运动员以及网球业内权威人士的意见进行分析讨论,搜集相关数据进行论证得出结论并提出一些相关点意见与建议。对加强科研开发、把鹰眼使用成本降低、鹰眼挑战的应对措施等进行讨论,以期对运动员运用鹰眼技术提高比赛成绩有所帮助。     

塑料圆形管材挤出胀大的数值模拟

挤出胀大是塑料圆形管材生产过程中不可避免的一种现象。在实际生产中,目前主要采用传统经验试差方法设计挤出口模,缺乏相关的理论研究及指导。本研究针对管材挤出工艺,建立了几何模型和数学模型,采用稳态不可压缩流体流动的有限元模型,模拟了PTT流体经过圆环口模挤出胀大现象。采用罚有限元将连续性方程引入动量方程,减少了同时计算的变量数,有效提高了计算效率。模拟结果表明,口模出口处聚合物熔体表面第一法向应力差急剧增大。口模尺寸一定时,聚合物的挤出胀大率随体积流量的增大而增大。同时也系统分析了口模尺寸对挤出胀大的影响规律。模拟结果对实际生产中的模具设计具有一定的指导意义。     

联营交易模式下的输电阻塞管理模型研究

全面分析了电力市场交易的典型模式,即联营交易模式,总结了联营交易模式下输电阻塞管理原则。提出了一种新的阻塞管理模型,即通过序内少出力补偿、序外多出力补偿、安全裕度利用率的设置,得到以阻塞费用最小和线路安全运行为双目标的阻塞管理模型。考虑电力市场中的主要约束条件,得到既保证电力系统经济性又满足电力系统安全性的较优的阻塞管理方案。这种模型的显著优点是能够较为精确地确定发电计划,同时提供节点电价等经济信息,并且在双目标模型转化为单目标约束规划模型时操作简便。最后在求解模型时采用了SFEC算法,该算法针对电力市场实行实时结算的特点,达到了计算效率和效果的平衡。通过实例计算,表明模型的正确性及算法的合理性。     

粒子群优化算法在水库调度中的应用分析

寻求水库最优调度轨迹过程线是水库优化调度中的经典、难点问题.本文在分析以往水库优化调度模型优缺点的基础上,提出了基于粒子群优化算法(Particle Swarm Optimization,简称PSO)的水库优化调度模型,并通过引入罚函数解决强约束问题.以某综合利用水库优化调度为实例进行研究,并与动态规划模型计算结果进行对比分析.结果表明:粒子群优化算法原理简单,易于编程实现,而且占用计算机内存小,计算速度快,适用于年内水库优化调度规则的确定.     

刑罚人道主义若干问题探讨

世界范围内的刑法改革正朝着文明、人道的方向前进,中国的刑法也在为此积极探索。对刑罚人道主义的探讨无疑是一个很好的开端。国内外学者对人道的问题已有一些研究。文章拟通过对刑罚人道主义界定内涵,及我国刑法中人道主义的检讨,最终明了人道对于刑罚不但过去和现在如影随形,更是将来刑法的前进方向。     

A natural gas cash-out problem: A bilevel programming framework and a penalty function method

One of the many complex problems that arise from the transmission and marketing of natural gas is when a shipper draws a contract with a pipeline company to deliver a certain amount of gas among several points. What is actually delivered is often different from the amount that had been originally agreed upon. This phenomenon is called an imbalance. When an imbalance occurs, the pipeline penalizes the shipper by imposing a cash-out penalty policy. Since this penalty is a function of the operating daily imbalances, an important decision-making problem for the shippers is how to carry out their daily imbalances so as to minimize their incurred penalty. In this paper, we introduce the problem of minimizing the cash-out penalty costs from the point of view of a natural gas shipping party. We present a mixed integer bilevel linear programming model and discuss its underlying assumptions. To solve it efficiently, we reformulate it as a standard mathematical program and describe a penalty-function algorithm functions for its solution. The algorithm is well-founded and its convergence is proved. Results of numerical experiments support the algorithm’s robustness providing a valuable solution technique for this very important and complex problem in the natural gas market.