Solving nonconvex economic load dispatch problem using particle swarm optimization with time varying acceleration coefficients

This article presents the design and application of an efficient hybrid heuristic search method to solve the practical economic dispatch problem considering many nonlinear characteristics of power generators, and their operational constraints, such as transmission losses, valve‐point effects, multi‐fuel options, prohibited operating zones, ramp rate limits and spinning reserve. These practical operation constraints which can usually be found at the same time in realistic power system operations make the economic load dispatch (ELD) problem a nonsmooth optimization problem having complex and nonconvex features with heavy equality and inequality constraints. A particle swarm optimization with time varying acceleration coefficients is proposed to determine optimal ELD problem in this paper. The proposed methodology easily takes care of solving nonconvex ELD problems along with different constraints like transmission losses, dynamic operation constraints, and prohibited operating zones. The proposed approach has been implemented on the 3‐machines 6‐bus, IEEE 5‐machines 14‐bus, IEEE 6‐machines 30‐bus systems and 13 thermal units power system. The proposed technique is compared with solve the ELD problem with hybrid approach by using the valve‐point effect. The comparison results prove the capability of the proposed method give significant improvements in the generation cost for the ELD problem. © 2015 Wiley Periodicals, Inc. Complexity 21: 299–308, 2016     

Multi-parametric optimizations for power dissipation characteristics of Stockbridge dampers based on probability distribution of wind speed

Power dissipation characteristics of Stockbridge dampers (SD) is one of the important indexes in anti-vibration work of transmission line. The study focuses on the optimization of the SD's power dissipation characteristics under the effect of multi-structure parameter coupling. The aeolian vibration of overhead transmission lines is uncertain and random in stochastic dynamics. According to Strouhal formula, the relationship between the vibration frequency of transmission lines and wind speed can be found out. Based on the Weibull wind speed probability distribution, the probability density function of the transmission line conductor and damper coupling system vibration frequency is derived. The SD is considered as a typical 2-dimension of stochastic dynamical system. Based on the random process generated by the power dissipation of the SD, the characteristics of power dissipation and SD's resonant frequencies are analyzed when the multi-structure parameters of the SD are coupled. And the diagrams of the power dissipation at various frequencies are obtained.Based on the probability density function of the vibration frequency of the overhead conductor and damper, the objective function, namely the mathematical expectation of power dissipation (E(PD)), of the optimizations for the SD's power dissipation under the coupling of multiple structural parameters is proposed for the first time according to the author's knowledge. Constraint conditions of the optimizations are built by the quantization processing. The energy dissipation characteristics of the dampers can be evaluated by E(PD), and the power dissipation of SD with different coupled dual structure parameters is optimized based on the proposed method. The optimal values or the optimal value intervals of different coupled dual structure parameters are found, which may provide practical data.     

Detection of maximum loadability limits and weak buses using Chaotic PSO considering security constraints

In the current research chaotic search is used with the optimization technique for solving non-linear complicated power system problems because Chaos can overcome the local optima problem of optimization technique. Power system problem, more specifically voltage stability, is one of the practical examples of non-linear, complex, convex problems. Smart grid, restructured energy system and socio-economic development fetch various uncertain events in power systems and the level of uncertainty increases to a great extent day by day. In this context, analysis of voltage stability is essential. The efficient method to assess the voltage stability is maximum loadability limit (MLL). MLL problem is formulated as a maximization problem considering practical security constraints (SCs). Detection of weak buses is also important for the analysis of power system stability. Both MLL and weak buses are identified by PSO methods and FACTS devices can be applied to the detected weak buses for the improvement of stability. Three particle swarm optimization (PSO) techniques namely General PSO (GPSO), Adaptive PSO (APSO) and Chaotic PSO (CPSO) are presented for the comparative study with obtaining MLL and weak buses under different SCs. In APSO method, PSO-parameters are made adaptive with the problem and chaos is incorporated in CPSO method to obtain reliable convergence and better performances. All three methods are applied on standard IEEE 14 bus, 30 bus, 57 bus and 118 bus test systems to show their comparative computing effectiveness and optimization efficiencies.     

Detecting and approximating fault lines from randomly scattered data

Discretely defined surfaces that exhibit vertical displacements across unknown fault lines can be difficult to approximate accurately unless a representation of the faults is known. Accurate representations of these faults enable the construction of constrained approximation models that can successfully overcome common problems such as over-smoothing. In this paper we review an existing method for detecting fault lines and present a new detection approach based on data triangulations and discrete Gaussian curvature (DGC). Furthermore, we show that if the fault line can be described non-parametrically, then accurate support vector machine (SVM) models can be constructed that are independent of the type of triangulation used in the detection algorithms. We shall also see that SVM models are particularly effective when the data produced by the detection algorithms are noisy. We compare the performances of the various new and established models.     

基于故障树和混沌粒子群算法的锻压机床故障诊断方法

锻压机床由于生产效率高和材料利用率高的特点,被广泛应用于各领域.然而,锻压机床发生故障时,其故障种类繁多、故障数据量大,所以对锻压机床故障源的快速、准确诊断较困难.针对该问题,文章提出一种将故障树分析法和混沌粒子群算法相融合的方法,对锻压机床的故障源进行故障诊断.该方法是先通过故障树分析法对锻压机床的故障进行分析从而得到故障模式及其故障概率,然后由得到的故障模式和已知的故障维修经验分析归纳出故障模式的学习样本,再根据得到的故障概率运用混沌粒子群算法的遍历性快速、准确地诊断出锻压机床发生故障的精确位置.文章提出的方法以锻压机床的伺服系统为例进行了故障诊断实验,将该实验结果与遗传算法、粒子群算法进行对比.实验结果表明,文章的算法在锻压机床伺服系统的故障诊断中准确度更高、速度更快.     

A model for setting services on auxiliary bus lines under congestion

In this paper, a mathematical programming model and a heuristically derived solution is described to assist with the efficient planning of services for a set of auxiliary bus lines (a bus-bridging system) during disruptions of metro and rapid transit lines. The model can be considered static and takes into account the average flows of passengers over a given period of time (i.e., the peak morning traffic hour). Auxiliary bus services must accommodate very high demand levels, and the model presented is able to take into account the operation of a bus-bridging system under congested conditions. A general analysis of the congestion in public transportation lines is presented, and the results are applied to the design of a bus-bridging system. A nonlinear integer mathematical programming model and a suitable approximation of this model are then formulated. This approximated model can be solved by a heuristic procedure that has been shown to be computationally viable. The output of the model is as follows: (a) the number of bus units to assign to each of the candidate lines of the bus-bridging system; (b) the routes to be followed by users passengers of each of the origin–destination pairs; (c) the operational conditions of the components of the bus-bridging system, including the passenger load of each of the line segments, the degree of saturation of the bus stops relative to their bus input flows, the bus service times at bus stops and the passenger waiting times at bus stops. The model is able to take into account bounds with regard to the maximum number of passengers waiting at bus stops and the space available at bus stops for the queueing of bus units. This paper demonstrates the applicability of the model with two realistic test cases: a railway corridor in Madrid and a metro line in Barcelona.     

Unstable limit cycles in an electric power system and basin boundary of voltage collapse

It has been reported that a saddle node bifurcation or a blue sky bifurcation causes voltage collapse in an electric power system. In these references, computer simulations are carried out with the voltage magnitude of the generator bus terminal held constant. The generator model described by differential equations of internal flux linkages allows the voltage magnitude of the generator bus terminal to change. By using this model, we have carried out computer simulations of the power system to determine the cause of voltage collapse. It is a cyclic fold bifurcation of the stable limit cycle caused by an unstable limit cycle that leads to the voltage collapse. The involvement of complicated sequences of unstable limit cycles with cyclic fold bifurcations is confirmed, and the voltage collapse which is caused by perturbation for steady states is related to these unstable limit cycles. This is very interesting from the point of view of a nonlinear problem. From the point of view of a power system, the power system will fluctuate in practice even in normal operation, and may sometimes operate beyond the limit of its stability in recent year. It is very important in this situation that we clarify bifurcations of limit cycles on the power system.     

Diagnosis for uncertain,dynamic and hybrid domains using Bayesian networks and arithmetic circuits

System failures, for example in electrical power systems, can have catastrophic impact on human life and high-cost missions. Due to an electrical fire in Swissair flight 111 on September 2, 1998, all 229 passengers and crew on board sadly lost their lives. A battery failure most likely took place on the Mars Global Surveyor, which unfortunately last communicated with Earth and thus ended its mission on November 2, 2006. Fault diagnosis techniques that seek to hinder similar accidents in the future are being developed in this article. We present comprehensive fault diagnosis methods for dynamic and hybrid domains with uncertainty, and validate them using electrical power system data. Our approach relies on the use of Bayesian networks, which model the electrical power system, compiled to arithmetic circuits. We handle in an integrated way varying fault dynamics (both persistent and intermittent faults), fault progression (both abrupt and drift faults), and fault behavior cardinality (both discrete and continuous behaviors). Our work has resulted in a software system for fault diagnosis, ProDiagnose, that has been the top performer in three of the four international diagnostics competitions in which it participated. In this paper we comprehensively present our methods as well as novel and extensive experimental results on data from a NASA electrical power system.     

An Analysis of <Emphasis Type="Italic">M/M/s</Emphasis> Queueing Systems Based on the Maximum Entropy Principle

There have been some interesting attempts to derive the equilibrium probability distribution of possible states of queueing systems by using the maximum entropy principle. In particular, Shore introduced an entropy model for the M/M/∞ queueing system. In this paper an inconsistency in Shore's procedure is indicated and an exact entropy model for the multiple server queueing system is presented.     

Phase- and sequence-domain static models equivalent to long double-circuit transmission lines

The application of equivalent rather than nominal models of transmission lines in various areas of power system studies ensures the accuracy of results when the line length and hence distributed-parameter effect is significant. In this research, the static modeling of long double-circuit lines is comprehensively addressed. Equivalent models are analytically derived for them in different possible operating configurations, incorporating both mutual induction and capacitive coupling between the circuits. This is achieved by finding the solution to the differential equations characterizing the phase voltages and currents of the line circuits. Hence, the equivalent models are first derived in the phase domain, and then the equations are transformed into the sequence domain to obtain equivalent models of sequence networks. The accuracy of the models derived is validated via simulation studies in PSCAD/EMTDC.     

Numerical recovery strategies for parallel resilient Krylov linear solvers

As the computational power of high‐performance computing systems continues to increase by using a huge number of cores or specialized processing units, high‐performance computing applications are increasingly prone to faults. In this paper, we present a new class of numerical fault tolerance algorithms to cope with node crashes in parallel distributed environments. This new resilient scheme is designed at application level and does not require extra resources, that is, computational unit or computing time, when no fault occurs. In the framework of iterative methods for the solution of sparse linear systems, we present numerical algorithms to extract relevant information from available data after a fault, assuming a separate mechanism ensures the fault detection. After data extraction, a well‐chosen part of missing data is regenerated through interpolation strategies to constitute meaningful inputs to restart the iterative scheme. We have developed these methods, referred to as interpolation–restart techniques, for Krylov subspace linear solvers. After a fault, lost entries of the current iterate computed by the solver are interpolated to define a new initial guess to restart the Krylov method. A well‐suited initial guess is computed by using the entries of the faulty iterate available on surviving nodes. We present two interpolation policies that preserve key numerical properties of well‐known linear solvers, namely, the monotonic decrease of the A‐norm of the error of the conjugate gradient or the residual norm decrease of generalized minimal residual algorithm for solving. The qualitative numerical behavior of the resulting scheme has been validated with sequential simulations, when the number of faults and the amount of data losses are varied. Finally, the computational costs associated with the recovery mechanism have been evaluated through parallel experiments. Copyright © 2016 John Wiley & Sons, Ltd.     

Early fault detection of rotating machinery through chaotic vibration feature extraction of experimental data sets

Fault detection of rotating machinery by the complex and non-stationary vibration signals with noise is very difficult, especially at the early stages. Also, many failure mechanisms and various adverse operating conditions in rotating machinery involve significant nonlinear dynamical properties. As a novel method, phase space reconstruction is used to study the effect of faults on the chaotic behavior, for the first time. Strange attractors in reconstructed phase space proof the existence of chaotic behavior. To quantify the chaotic vibration for fault diagnosis, a set of new features are extracted. These features include the largest Lyapunov exponent; approximate entropy and correlation dimension which acquire more fault characteristic information. The variations of these features for different healthy/faulty conditions are very good for fault diagnosis and identification. For the first time, a new chaotic feature space is introduced for fault detection, which is made from chaotic behavior features. In this space, different conditions of rotating machinery are separated very well. To obtain more generalized results, the features are introduced into a neural network to identify different faults in rotating machinery. The effectiveness of the new features based on chaotic vibrations is demonstrated by the experimental data sets. The proposed approach can reliably recognize different fault types and have more accurate results. Also, the performance of the new procedure is robust to the variation of load values and shows good generalization capability for various load values.     

Fault tolerant routing algorithm based on the artificial potential field model in Network-on-Chip

Recent advances in semiconductor technology enable the VLSI chips to integrate hundreds of intellectual properties with complex functionality. However, as the chip scales, the probability of faults is increasing, making fault tolerance a key concern in designing the large scale chips. The fault tolerant routing algorithms can guarantee sustained communication even the faults exist. It is an efficient technique to achieve fault tolerance in Networks-on-Chip. In this paper, we propose a new model based on the theory of artificial potential field (APF) to design various fault tolerant routing algorithms. In our model, the faults are considered as the poles of the repulsive potential fields while the destinations as the poles of the attractive potential fields. Messages are attracted to destinations and repelled by faults in the combined artificial potential field. The parameters used in the proposed APF based model are optimized through theoretical analysis and simulation experiments. They can support flexible fault tolerant routing algorithms. Finally, we evaluate the performance of the proposed fault tolerant routing algorithm based on the APF model in 2D-mesh NoCs with random faults. The simulation results show that the proposed APF based model is feasible and the routing algorithm can maintain good network performance.     

Detection,isolation and identification of multiple actuator and sensor faults in nonlinear dynamic systems: Application to a waste water treatment process

The goal in many fault detection and isolation schemes is to increase the isolation and identification speed. This paper, presents a new approach of a nonlinear model based adaptive observer method, for detection, isolation and identification of actuator and sensor faults. Firstly, we will design a new method for the actuator fault problem where, after the fault detection and before the fault isolation, we will try to estimate the output of the instrument. The method is based on the formation of nonlinear observer banks where each bank isolates each actuator fault. Secondly, for the sensor problem we will reformulate the system by introducing a new state variable, so that an augmented system can be constructed to treat sensor faults as actuator faults. A method based on the design of an adaptive observers’ bank will be used for the fault treatment. These approaches use the system model and the outputs of the adaptive observers to generate residues. Residuals are defined in such way to isolate the faulty instrument after detecting the fault occurrence. The advantages of these methods are that we can treat not only single actuator and sensor faults but also multiple faults, more over the isolation time has been decreased. In this study, we consider that only abrupt faults in the system can occur. The validity of the methods will be tested firstly in simulation by using a nonlinear model of waste water treatment process with and without measurement noise and secondly with the same nonlinear model but by using this time real data.     

配电设备实时故障风险评估方法

现有配电设备故障风险评估方法在因素分析方面不够全面,未能综合考虑天气等环境因素与设备健康状态因素对设备故障风险的影响,且数据来源主要为长期历史数据,缺乏时效性。为解决此问题,本文提出了一种配电设备实时故障风险评估方法,结合天气状况、设备状态两大因素计算配电设备实时故障概率,通过负荷损失量、停电用户数量、负荷重要等级三个因素评估配电设备故障影响程度,并以设备故障概率和故障影响程度为准则建立风险评估模型。通过IEEE-RBTS BUS2算例分析,证明该模型能够有效评估配电设备实时故障风险,对于电力企业优化设备检修工作,提升应急管理水平具有重要的指导意义。     

Maximum entropy analysis to the N policy M/G/1 queueing system with a removable server

We study a single removable server in an M/G/1 queueing system operating under the N policy in steady-state. The server may be turned on at arrival epochs or off at departure epochs. Using the maximum entropy principle with several well-known constraints, we develop the approximate formulae for the probability distributions of the number of customers and the expected waiting time in the queue. We perform a comparative analysis between the approximate results with exact analytic results for three different service time distributions, exponential, 2-stage Erlang, and 2-stage hyper-exponential. The maximum entropy approximation approach is accurate enough for practical purposes. We demonstrate, through the maximum entropy principle results, that the N policy M/G/1 queueing system is sufficiently robust to the variations of service time distribution functions.     

Path integral for the probability of the trajectories generated by fractional dynamics subject to Gaussian white noise

One considers a fractional stochastic process defined as the dynamics of a non-random fractional system subject to a Gaussian white noise. One shows how the probability distribution of the random paths so generated can be obtained by combining path integrals and the maximum entropy principle.     

Failure of bridges in thin plates

The nonlinear theory of fracture development in a zone with preexisting faults is used to consider failure of bridges between two semi-infinite cracks along a line under the influence of given forces perpendicular to the given line. A linear relation is proposed for the relationship between the size of the opening and the normal stress in the zone of the preexisting fault: this makes it possible to state a spectral problem for an integral operator. which is solved numerically. The critical value for the force holding the zone of pre-existing fault together is determined. Translated fromDinamicheskie Sistemy. Vol. 12, pp. 3–7. 1993.     

Line graphs: Their maximum nullities and zero forcing numbers

The maximum nullity over a collection of matrices associated with a graph has been attracting the attention of numerous researchers for at least three decades. Along these lines various zero forcing parameters have been devised and utilized for bounding the maximum nullity. The maximum nullity and zero forcing number, and their positive counterparts, for general families of line graphs associated with graphs possessing a variety of specific properties are analysed. Building upon earlier work, where connections to the minimum rank of line graphs were established, we verify analogous equations in the positive semidefinite cases and coincidences with the corresponding zero forcing numbers. Working beyond the case of trees, we study the zero forcing number of line graphs associated with certain families of unicyclic graphs.     

Determination of active power limits at a bus of AC network

This work deals with the problem of determining the maximum volumes of the active power which can be generated or consumed in an arbitrary bus of an AC network when the powers at the buses are in proportion to the squares of magnitudes of the voltage at the corresponding buses. Solutions to this problem (when formalized as a constrained optimization problem) are shown as having a unique minimum and unique maximum, and explicit forms of the extrema are obtained.