Lie symmetries of soliton equations with self-consistent sources via source generation procedure

In this paper, the ‘source generation’ procedure (SGP) proposed by Hu and Wang [X.B. Hu, H.Y. Wang, Construction of dKP and BKP equation with self-consistent sources, Inverse Problems 22 (2006) 1903-1920] is utilized to derive Lie symmetries of bilinear soliton equations with self-consistent sources (SESCS) such as KPESCS, BKPESCS, and differential-difference KPESCS. Furthermore, it is shown that these Lie symmetries constitute generators of the corresponding Lie symmetry algebras.     

Minimum norm approach to optimal long-term operation of multireservoir power systems with specified monthly generation

The aim of this paper is to present a new algorithm to maximize the value of the energy produced from a multireservoir power system, plus the estimated value of water remaining in storage at the end of the 12-month planning period. The systems described here are characterized by having a specified monthly generation, and this generation is equal to a certain percentage of the total generation at the end of the year.The problem is formulated as a minimum norm problem in the framework of analytic optimization. Numerical results are reported for a real system in operation consisting of three rivers; each river has two series reservoirs. The proposed algorithm is efficient in computing time and in calculating the total expected benefits from the system.This work was supported by the National Research Council of Canada, Grant No. A4146. The authors would like to acknowledge data obtained from B.C. Hydro, Vancouver, B.C., Canada.     

Modelling the clogging of gas turbine filter houses in heavy-duty power generation systems

ABSTRACT

A prognostic approach based on a MISO (multiple inputs and single output) fuzzy logic model was introduced to estimate the pressure difference across a gas turbine (GT) filter house in a heavy-duty power generation system. For modelling and simulation of clogging of the GT filter house, nine real-time process variables (ambient temperature, humidity, ambient pressure, GT produced load, inlet guide vane position, airflow rate, wind speed, wind direction and PM10 dust concentration) were fuzzified using a graphical user interface within the framework of an artificial intelligence-based methodology. The results revealed that the proposed fuzzy logic model produced very small deviations and showed a superior predictive performance than the conventional multiple regression methodology, with a very high determination coefficient of 0.974. A complicated dynamic process, such as clogging phenomenonin heavy-duty GT system, was successfully modelled due to high capability of the fuzzy logic-based prognostic approach in capturing the nonlinear interactions.     

Using stochastic optimization to determine threshold values for the control of unreliable manufacturing systems

A manufacturing system with two tandem machines producing one part type is considered in this work. The machines are unreliable, each having two states, up and down. Both surplus controls and Kanban systems are considered. Algorithms for approximating the optimal threshold values are developed. First, perturbation analysis techniques are employed to obtain consistent gradient estimates based on a single simulation run. Then, iterative algorithms of the stochastic optimization type are constructed. It is shown that the algorithms converge to the optimal threshold values in an appropriate sense. Numerical examples are provided to demonstrate the performance of the algorithms.The research of these authors was supported in part by grants from URIF, MRCO, National Science Foundation, and Wayne State University. The authors would like to thank Dr. X. R. Cao, Digital Equipment Corporation, for the valuable initial discussion and Dr. X. Y. Zhou, University of Toronto, for his helpful comments.     

Solving a novel multiobjective placement problem of recloser and distributed generation sources in simultaneous mode by improved harmony search algorithm

This article deals with optimal placement of Distributed Generation (DG) sources and recloser in simultaneous mode and develops an improved harmony search (iHS) algorithm to solve it. For this, two important control parameters have been adjusted to reach better solution from simple HS algorithm to obtain better solution from simple HS algorithm. The proposed multiobjective function consists of two parts; first is improving reliability indices and second is minimizing power loss. The reliability indices have been selected based on satisfactory requirements of costumer and electric company as well as response to transient and permanent faults. Then, four reliability indices has been used in objective function; that is, system average interruption duration index (SAIDI), cost of energy not supplied, momentary average interruption frequency index, and system average interruption frequency index (SAIFI). Simulation has been performed on a practical distribution network in North West of Iran. Three scenarios have been introduced; that is, scenario (i) First, placement of DGs, and then recloser, scenario (ii) First, placement of recloser, and then DG, and scenario (iii) simultaneous placement of DG and recloser. Also, three cases are defined based on the number of used DG and recloser. Results of the proposed algorithm have been compared with related values of particle swarm optimization and simple HS algorithms. The core contribution of the presented study is introducing several novel indices to analyze and discuss the obtained results from simulation. © 2014 Wiley Periodicals, Inc. Complexity 21: 328–339, 2015     

Finite generation of powers of ideals

Suppose is a maximal ideal of a commutative integral domain and that some power of is finitely generated. We show that is finitely generated in each of the following cases: (i) is of height one, (ii) is integrally closed and , (iii) is a monoid domain over a field , where is a cancellative torsion-free monoid such that , and is the maximal ideal . We extend the above results to ideals of a reduced ring such that is Noetherian. We prove that a reduced ring is Noetherian if each prime ideal of has a power that is finitely generated. For each with , we establish existence of a -dimensional integral domain having a nonfinitely generated maximal ideal of height such that is -generated.

     

Using multiple sources of information to recognize and classify objects

In this paper we consider the problem of selecting an object or a course of action from a set of possible alternatives. To give the paper focus, we concentrate initially on an object recognition problem in which the characteristic features of the object are reported by remote sensors. We then extend the method to a more general class of selection problems and consider several different scenarios.

Information is provided by a set of knowledge system reports on a single feature, and the output from these systems is not totally explicit but provides posible values for the observed feature along with a degree of certitude.We use fuzzy sets to represent this vague information. Information from independent sources is combined using the Dempster-Shafer approach adapted to the situation in which the focal elements are fuzzy as in the recent paper by J. Yen [7]. We base our selection rule on the belief and plausibility functions generated by this approach to accessing evidence.

For situations in which the information is too sparse and/or too vague to make a single selection, we construct a preference relationship based on the concept of averaged subsethood for fuzzy sets as discussed by B. Koskoin [4]. We also define an explicit metric upon which to base our selection mechanism for situations in which the Dempster-Shafer rule of combination is inappropriate     

可再生能源发电商最优减排补贴政策的激励效应研究

针对传统减排补贴激励政策的突出矛盾, 本文借助委托代理理论并从激励相容约束和参与约束条件的角度出发解析政府如何有效地设计优化减排补贴政策, 以此为基础分析了政府最优减排补贴政策的激励效应:首先, 基于最优发电量的最大减排量确定政府对增加环境经济效益和节约电煤消耗量的社会福利的平衡系数在减排水平对电能生产强弱敏感条件下的最大临界值和最小临界值; 其次, 以临界最值为基准, 基于发电商最优收益分析在强弱敏感条件下减排补贴政策存在负向激励效应的合理性和可靠性; 最后, 基于政府最优减排补贴成本分析在强弱敏感条件下减排补贴政策对发电商所产生的正向激励效应。研究结论为燃煤发电区域政府科学引导可再生能源发电商积极参与减排合作而制定有效的减排补贴激励政策提供了决策依据和管理启示。     

Generation and random generation: From simple groups to maximal subgroups

Let G   be a finite group and let d(G)$d(G)$ be the minimal number of generators for G  . It is well known that d(G)=2$d(G)=2$ for all (non-abelian) finite simple groups. We prove that d(H)?4$d(H)?4$ for any maximal subgroup H of a finite simple group, and that this bound is best possible.     

Two methods for large-scale nonlinear optimization and their comparison on a case study of hydropower optimization

This paper presents two methods for the optimization of structured large-scale problems: a decomposition method of dual type for nonlinear problems and a sequential quadratic programming based method. Practical details of application of the methods to the case study problem of the hydropower system of an African river are then given. Comparison of results is presented, indicating that both methods are useful and efficient, having however different features from a practical point of view. General remarks concerning the practical differences between a decomposition-based method and a method exploiting the problem structure within the framework of general purpose optimization routines are finally presented.This work was partly supported by the Water Resource Project, IIASA, Laxenburg, Austria.     

Transversal hypergraphs to perfect matchings in bipartite graphs: Characterization and generation algorithms

A minimal blocker in a bipartite graph G is a minimal set of edges the removal of which leaves no perfect matching in G. We give an explicit characterization of the minimal blockers of a bipartite graph G. This result allows us to obtain a polynomial delay algorithm for finding all minimal blockers of a given bipartite graph. Equivalently, we obtain a polynomial delay algorithm for listing the anti‐vertices of the perfect matching polytope of G. We also provide generation algorithms for other related problems, including d‐factors in bipartite graphs, and perfect 2‐matchings in general graphs. © 2006 Wiley Periodicals, Inc. J Graph Theory 53: 209–232, 2006     

Fast generation of regular graphs and construction of cages

The construction of complete lists of regular graphs up to isomorphism is one of the oldest problems in constructive combinatorics. In this article an efficient algorithm to generate regular graphs with a given number of vertices and vertex degree is introduced. The method is based on orderly generation refined by criteria to avoid isomorphism checking and combined with a fast test for canonicity. The implementation allows computing even large classes of graphs, like construction of the 4‐regular graphs on 18 vertices and, for the first time, the 5‐regular graphs on 16 vertices. Also in cases with given girth, some remarkable results are obtained. For instance, the 5‐regular graphs with girth 5 and minimal number of vertices were generated in less than 1 h. There exist exactly four (5, 5)‐cages. © 1999 John Wiley & Sons, Inc. J Graph Theory 30: 137–146, 1999     

Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems

We describe a bootstrap method for estimating mean squared error and smoothing parameter in nonparametric problems. The method involves using a resample of smaller size than the original sample. There are many applications, which are illustrated using the special cases of nonparametric density estimation, nonparametric regression, and tail parameter estimation.     

An extended Petviashvili method for the numerical generation of traveling and localized waves

A family of fixed-point iterations is proposed for the numerical computation of traveling waves and localized ground states. The methods are extended versions of Petviashvili type, and they are applicable when the nonlinear term of the system contains homogeneous functions of different degree. The methods are described and applied to several examples of interest, that calibrate their efficiency.     

Fast orthogonal transforms and generation of Brownian paths

We present a number of fast constructions of discrete Brownian paths that can be used as alternatives to principal component analysis and Brownian bridge for stratified Monte Carlo and quasi-Monte Carlo. By fast we mean that a path of length n$n$ can be generated in O(nlog(n))$O(nlog\left(n\right))$ floating point operations. We highlight some of the connections between the different constructions and we provide some numerical examples.     

Global and superlinear convergence of the smoothing Newton method and its application to general box constrained variational inequalities

The smoothing Newton method for solving a system of nonsmooth equations , which may arise from the nonlinear complementarity problem, the variational inequality problem or other problems, can be regarded as a variant of the smoothing method. At the th step, the nonsmooth function is approximated by a smooth function , and the derivative of at is used as the Newton iterative matrix. The merits of smoothing methods and smoothing Newton methods are global convergence and convenience in handling. In this paper, we show that the smoothing Newton method is also superlinearly convergent if is semismooth at the solution and satisfies a Jacobian consistency property. We show that most common smooth functions, such as the Gabriel-Moré function, have this property. As an application, we show that for box constrained variational inequalities if the involved function is -uniform, the iteration sequence generated by the smoothing Newton method will converge to the unique solution of the problem globally and superlinearly (quadratically).

     

Bilinear Control and Application to Flexible a.c. Transmission Systems

The purpose of this paper is an integrated overview of bilinear systems (BLS) research which has evolved over the past few decades, and a new result on control of flexible a.c. transmission systems (FACTS) is presented. BLS may be derived in many cases from principles of physics, chemistry, biology, socioeconomics, and engineering. In other cases, BLS are more accurate approximations to nonlinear systems than are traditional linear systems, as shown for example by the added bilinear terms (in state and control) for the Taylor series.While an appropriately designed linear control system may be optimum relative to some quadratic performance index without added constraints, bilinear or parametric control can be designed to improve more global performance and indeed to increase the region of attainable states. Such controllability and stabilization of BLS and of a series line-capacitor controlled FACTS is presented.     

Comparison of bundle and classical column generation

When a column generation approach is applied to decomposable mixed integer programming problems, it is standard to formulate and solve the master problem as a linear program. Seen in the dual space, this results in the algorithm known in the nonlinear programming community as the cutting-plane algorithm of Kelley and Cheney-Goldstein. However, more stable methods with better theoretical convergence rates are known and have been used as alternatives to this standard. One of them is the bundle method; our aim is to illustrate its differences with Kelley’s method. In the process we review alternative stabilization techniques used in column generation, comparing them from both primal and dual points of view. Numerical comparisons are presented for five applications: cutting stock (which includes bin packing), vertex coloring, capacitated vehicle routing, multi-item lot sizing, and traveling salesman. We also give a sketchy comparison with the volume algorithm. This research has been supported by Inria New Investigation Grant “Convex Optimization and Dantzig-Wolfe Decomposition”.     

风电场可靠性模型及其应用

考虑了风速分布的季节性差异和风速的随机变化的影响、风电机组的实际功率特性、风电场尾流效应以及风电机组故障状况,建立了风电场可靠性模型.根据某海上风电场实测数据进行数值仿真实验,结果验证了模型的正确性和有效性.模型为进一步研究大规模风电并网以及风电场功率预测等问题打下了基础.     

Evaluation and enhancement of dynamic performance of a microgrid including PV and wind generation systems

Large participation of renewable energy sources with rapidly varying inputs can affect the performance of a microgrid system. This article develops a detailed non-linear and small-signal dynamic model of a microgrid that includes photovoltaic (PV), wind and conventional small-scale generation along with their power electronics interfaces and the filters. The role of the extent of generation mix of the distributed generators (DGs) for satisfactory operation of the system has been investigated through small-signal dynamic model. It was observed that there exist critical values of PV and wind power above which the microgrid performance degrades. The enhancement of performance of the microgrid through various control inputs have been evaluated through decomposition techniques. Simulation studies showed that an energy storage system-based central supervisory controller and also control of PV system can improve transient performance when violations of proper generation mix of the DGs occur.