Binary-Representation-Based Genetic Algorithm for Aircraft Arrival Sequencing and Scheduling

Arrival sequencing and scheduling (ASS) at airports is an NP-hard problem. Much effort has been made to use permutation-representation-based genetic algorithms (GAs) to tackle this problem, whereas this paper attempts to design an efficient GA based on a binary representation of arriving queues. Rather than using the order and/or arriving time of each aircraft in the queue to construct chromosomes for GAs, this paper uses the neighboring relationship between each pair of aircraft, and the resulted chromosome is a 0-1-valued matrix. A big advantage of this binary representation is a highly efficient uniform crossover operator, which is normally not applicable to those permutation representations. The strategy of receding horizon control (RHC) is also integrated into the new GA to attack the dynamic ASS problem. An extensive comparative simulation study shows that the binary-representation-based GA outperforms the permutation-representation-based GA.     

Multiairport Capacity Management: Genetic Algorithm With Receding Horizon

The inability of airport capacity to meet the growing air traffic demand is a major cause of congestion and costly delays. Airport capacity management (ACM) in a dynamic environment is crucial for the optimal operation of an airport. This paper reports on a novel method to attack this dynamic problem by integrating the concept of receding horizon control (RHC) into a genetic algorithm (GA). A mathematical model is set up for the dynamic ACM problem in a multiairport system where flights can be redirected between airports. A GA is then designed from an RHC point of view. Special attention is paid on how to choose those parameters related to the receding horizon and terminal penalty. A simulation study shows that the new RHC-based GA proposed in this paper is effective and efficient to solve the ACM problem in a dynamic multiairport environment     

Traffic scheduling in distributed networked control systems with packet losses and delays for power systems voltage stabilization

In this paper, medium access control (MAC) sublayer data traffic scheduling in distributed networked control systems (DNCSs) with networked induced packet losses and delays is investigated for stabilization and control of system dynamics. An effective‐information‐directed distributed sensor selection algorithm is proposed to select sensors to participate in delay‐tolerant information filtering for state estimation. The distributed scheduling algorithm is based on the total amount of effective information for all measurements stored in the sensors. We consider packet loss in wireless networks as a special type of delay, so the impact of packet losses on effective information amount can also be studied for the formulation of distributed scheduling strategy in the presence of packet losses. The distributed data traffic scheduling considering packet losses and delays is carried out in a networked system with data packet dropout governed by a Markov process for voltage regulation and stabilization with distributed energy resources (DERs). Experimental results demonstrate that the scheduling algorithm with awareness of the system dynamic state can well control the power system dynamics. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

基于WSN的机棚温湿度精确监测系统设计

沿海地区的航空装备因高温、高湿和盐雾导致的腐蚀尤为严重,目前对此普遍采用的维护措施缺乏可靠的参考,影响维护效率和装备完好率.构建开放环境中贴近停机位的多点实时温湿度监测系统是实现科学维护的重要基础.通过比较目前机场采用的各种监测网络、分析停机位分布特征以及机场传感器布放的特殊要求,提出基于无线传感器网络(WSN)的温湿度精确监测系统.通过采用NI公司的WSN技术搭建监测网络,实现无线网络与有线网络的无缝连接,实现了对不同气候环境、不同规模机场以及不同形式停机位的全适应,具有能耗低、布线少和软硬件扩展能力强等优点.该系统为机务人员的防潮维护工作提供精确的定量参考,对实现按需维护和保障装备完好率具有重要意义.     

基于负载再分配的边缘计算任务均衡调度策略

目前5G异构网络的计算卸载机制在边缘节点资源方面和电力业务调度算法时延与负载均衡方面存在问题。综合考虑边缘服务器负载均衡和业务计算时延,针对min-min算法与max-min算法的不足,文中提出了基于电力业务优先级二次再分配的均衡调度算法。该算法根据业务的最大容忍时延划分业务的优先级,并且根据最小完成时间标准差确定长短业务比例,实现业务的预分配。基于各个边缘服务器的负载情况,该算法再将高负载边缘服务器上的业务分配给负载低的服务器,实现二次再分配。仿真结果表明,与典型的算法相比较,所提算法缓解了现有技术中存在的以上问题,降低了计算时延,实现负载均衡,提高了系统资源利用率。     

A study of aircraft taxi performance for enhancing airport surfacetraffic control

In view of the ever-increasing air traffic, much attention in air traffic management research has been given to improving arrival and departure efficiency. As air traffic begins and ends at the airport, the issues of taxi delays and ground incursions are becoming more evident. The paper considers the surface-traffic problem at major airports and envisions a collaborative traffic and aircraft control environment where a surface traffic automation system will help coordinate surface traffic movements. Specifically, the paper studies the performance potential of high-precision taxi toward the realization of such an environment. A state-of-the-art nonlinear control system based on feedback linearization is designed for a detailed B-737 aircraft taxi model. The simulation model with the nonlinear control system is evaluated extensively in a scenario representing the demanding situation of an arrival aircraft crossing an adjacent active runway immediately following its own landing. The evaluation establishes the potential of an automated system to achieve high-precision taxi control, including the ability to comply with taxi clearances with tight time margins. Such a high-precision taxi capability reduces the time margin required for clearing taxiing aircraft to cross active runways, thus increasing the opportunity for issuing such clearances, which in turn reduces the need for aircraft to hold short at the runways to wait for the opportunity for crossing. The results from the analyses provide insight into future aircraft operational capabilities toward the design of the envisioned surface traffic automation system. Moreover, the nonlinear control design serves as a preliminary study for future auto-taxi functional development     

考虑热网传输延时及储热的电-热综合能源系统日前优化调度策略

综合考虑热网传输延时及储热的优化调度,可显著提高电-热综合能源系统的灵活性,在实现系统经济运行的同时,进一步提高系统的新能源消纳能力。对此,文中提出考虑热网传输延时及储热的电-热综合能源系统日前优化调度策略。首先,建立描述热网的传输延时和储热的供热系统模型;接着结合具体的能源设备,将热网作为调度资源参与到日前优化调度中,提出一种热网传输延时及储热的日前优化调度模型,实现对热网虚拟储能的调度利用。最后对不同场景下含风电的电-热综合能源进行算例分析,验证了文中所提方法的有效性。仿真结果表明,该方法可利用热网传输延时和储热进一步降低系统的运行成本,提高风电的消纳率。     

考虑多重因素的空调负荷聚合响应潜力评估及控制策略研究

空调负荷已成为电力系统重要的需求响应资源,但由于其类型差异性、接入分散性,造成调度中心难以直接获取其聚合功率并开展调度控制,限制了响应潜力发挥。对此,提出考虑空调负荷聚合响应潜力多类型资源协同调度与精准控制相结合的双层调控框架。在日前调度层,基于近似聚合模型获取空调负荷聚合功率,考虑用户热舒适度、意愿度及可控度等多重因素,建立空调负荷聚合响应潜力评估模型,获取其聚合响应潜力,并结合基础柔性负荷响应特性建立联合调度模型,充分挖掘负荷侧多类型资源参与系统调节的潜力;在日内控制层,针对执行降负荷调温控制策略中空调群组功率跌落现象,为引导其有序参与电网需求响应,建立变状态数的状态队列模型,并引入准备时间对参数异质空调集群进行分组控制,使空调负荷跟随调度计划,提升控制精度,缓解功率跌落对系统运行产生的影响。最后,通过某简化配网系统进行仿真分析,结果表明:所提双层调控框架在调度层可深度挖掘并引导利用空调负荷响应潜力,在控制层实现精准控制并削弱功率跌落负面影响,工程应用价值显著。     

具有延时补偿的数字控制在PWM整流器中的应用

由零阶保持器及计算时间产生的控制延时是数字控制的主要缺点之一，这会导致系统振荡以至不稳定。为补偿延时，提出了一种基于状态反馈的新方法。该方法没有采用状态观测器，首先建立包含延时影响的PWM整流器的新数学模型，然后采用线性状态反馈，通过配置系统极点，得到新控制器。该方法消除延时影响不仅保证系统稳定而且对给定电流输入可取得无差拍响应。1kW的能量回馈型交流电子负载样机被用于验证新方法。样机采用20kHz的开关频率和TMS320F2812 DSP控制芯片。样机实验验证了理论分析的正确。     

A FAST ALGORITHM FOR OPTIMAL HYDROTHERMAL SCHEDULING WITH CASCADED AND INDEPENDENT HYDRO PLANTS

ABSTRACT

This paper presents a fast algorithm for solving the short-term hydrothermal scheduling problem in a power system consisting of cascaded plants with time delay and independent hydro plants. The operational planning of such problem is concerned with the determination of scheduling for hydro as well as thermal plants to meet the daily system demand with the objective of minimizing the total fuel cost of the thermal plants over the day subject to the relevant operating constraints associated with the thermal and hydro plants.

The algorithm employs a fast and simple alternating solution approach for hydrothermal scheduling in which the hydro subproblem is solved using the method of local variation while the associated thermal subproblem is solved through a judicious combination of Successive Linear Programming (SLP) method and Participation Factor method. Many computational features are incorporated in the solution algorithm exploiting the inherent characteristic of the complex hydrothermal scheduling problem.     

基于LQEKF的机载光电平台的模型预测控制

为了提高机载光电平台对目标稳定跟踪控制性能，提出一种基于线性二次增强卡尔曼滤波器的机载光电平台模型预测控制算法。建立机载光电平台的动力学模型，在卡尔曼滤波状态估计的基础上，引入线性二次调节器增益减小估计状态的相位延迟，使状态估计值更为精确，利用估计的状态设计模型预测控制器，减小目标跟踪误差。跟踪目标仿真实验结果与卡尔曼滤波状态估计结果最大误差减小了58.14%，与扩展卡尔曼滤波状态估计最大误差减小了52.62%，表明本算法能够有效提高机载光电平台对目标的跟踪控制性能，实现了机载光电平台对目标的稳定跟踪控制。     

半实物网络控制系统仿真平台设计

网络控制系统(NCS)是一种新型计算机控制系统,通过工业网络实现控制单元之间的数据交换,但这也给控制系统带来了时延等问题。采用德国费斯托过程控制装置中的液位控制单元为实物被控对象,以校园局域网为通信介质,基于OPC协议,以西门子S7-300 PLC作为OPC服务器,将MATLAB作为OPC客户端,最终开发出一种基于OPC技术的实体对象与MATLAB结合的半实物NCS实验系统,为高级控制算法的研究和验证提供了一个良好的实验平台。     

A genetic algorithm with local search using activity list characteristics for solving resource‐constrained multiproject scheduling problem

In this paper, we aim to solve the resource‐constrained multiproject scheduling problem (rc‐mPSP), in which more than one project are scheduled simultaneously, projects share global resources, and the average project delay and total project time are minimized as objectives. In order to solve this problem by a centralized scheduling method, we present a new genetic algorithm (GA) approach. In this procedure, we follow the GA described in Okada et al.. (2014) and improve its genetic operators, such as crossover and mutation, and local search so as to work better on rc‐mPSP. Furthermore, in order to evaluate the proposed approach, we compare the results of the computational experiment on certain standard project instances with the several competing decentralized methods and centralized methods presented in the literature. We show that our procedure is one of the most competitive among such algorithms. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

考虑服务配置的细粒度电力任务云边协同优化调度策略

新型电力系统的建设促使电力业务范围向用户侧深入,业务种类及数量不断增加。边设备资源有限,只能配置有限数量的服务,任务的时延能耗需求与设备资源有限的矛盾日益突出。为实现云边资源协同与任务的优化调度,提出了一种考虑服务配置的细粒度电力任务云边协同优化调度策略。通过建立微服务的时延与能耗模型,并对任务调度中的约束条件进行分析,将时延与能耗的优化决策问题转化为带约束的多目标优化问题,采用NSGA-Ⅱ算法求解。然后通过基于模糊逻辑的多准则决策方法为任务选择调度方案。仿真结果表明,所提策略在时延和能耗方面的性能优于其他策略,能够适应不同的任务场景并做出最优决策,提高了任务的完成率。     

Optimal daily scheduling of cascaded plants using a new algorithmof nonlinear minimum cost network flow

An optimality condition theorem and an algorithm for nonlinear minimum-cost network flow are proposed. A computational network model for optimal daily scheduling of cascaded plants (ODSCP) is established, and an algorithm for searching the minimum-cost flow-augmenting path and the maximum-cost flow-reducing path in the computational network model of ODSCP is described. Digital computations are carried out and the results show that the proposed method is very fast compared to existing methods     

EAST极向场电源现场总线多任务实时调度的研究

以太网现场总线广泛应用于工业控制系统中,但以太网CSMA/CD介质访问控制机制使其难以适应高实时性控制过程。针对实时性要求极高的EAST极向场电源控制系统,分析了现场总线网络中存在的实时性问题,设计了一种多任务实时调度策略。采用新的调度策略优化网络后,硬实时任务可以确保在截止期前完成。实验结果表明,网络满足了电源控制系统的高实时性要求。     

The rate control index for traffic flow

The objective of air traffic flow management is to maintain safe and efficient use of airspace and airports by regulating the flow of traffic. We introduce a single-valued metric for post-operatively rating the performance of achieved traffic flow against targeted traffic flow. We provide variations on the metric, one of which factors out stochastic conditions upon which a plan is formulated, and show how these improve on current traffic control analysis techniques. The core of the metric is intuitive and simple, yet leads to an interesting optimization problem that can be efficiently solved via dynamic programming. Numerical results of the metric are given as well as a sample of the type of analysis that should follow a low rating by the metric. Although this metric was originally developed to rate the performance of ground delay programs, it is equally applicable to any setting in which the flow of discrete objects such as vehicles is controlled and later evaluated     

具有通信约束的网络控制系统的协同优化方法

对于传感器、控制器和执行器典型空间分布且具有通信约束条件的网络控制系统,应用通信序列的概念和混合逻辑动态的构架,将其建模成一类集成控制和调度的通信约束离散周期系统。采用线性矩阵不等式来描述信息调度与控制的协同优化问题,使闭环系统具有指数渐近稳定。启发式求解方法在最优H∞性能下解决了信息调度策略问题,同时也节省了搜索最优解的计算时间。     

Detection and location of partial discharges in power transformers using acoustic and electromagnetic signals

The measurement of partial discharges (PD) is a non-destructive and sensitive diagnostic tool for the condition assessment of insulating systems. Two major tasks of PD measurements may be distinguished, (i) PD detection, hence providing evidence and the type of the PD and (ii) the location of the PD. The question "Where is the PD source?" is amongst others tremendously important for scheduling and starting maintenance/repair actions cost and time efficiently or to perform a risk analysis. Here the possibility to geometrically localize the flaw, by means of arrival times of acoustic PD signals, gets an extremely interesting option. Precise acoustic arrival times are consequently essential to accurately locate PD in a power transformer. The averaging of acoustic PD signals helps to enhance the acoustic sensitivity. The acoustic detection limit is lowered significantly and the determination of the arrival times is made possible for weaker PD. Supplementary steps, like automatic objective arrival time determination or additional wavelet-based de-noising further improve the overall location accuracy. A new location approach works with pseudo-times and allows for the use of robust direct solvers instead of the previously used iterative algorithms.     

含多微网稀疏通信优化的主动配电网分层分布式协调控制

针对多微网及主动配电网协调运行时控制目标的不同,通过多智能体系统构建含配电网级、微网级、元件级的三层协调控制架构,将调度管理过程分为配电网级智能体调度和微网级智能体调度两个部分,提出了稳态运行时主动配电网和多微网之间的互联、互动的新方案,并在元件级智能体上设计了一种基于分布式稀疏通信网络的二级优化控制器,可以实现微网内负荷波动时元件上电压、频率的快速恢复,以及联络线有功功率的精确分配。另外,为了分析通信时滞对多微网智能体之间协调控制的影响,根据图论的基本理论对通信拓扑进行了优化设计。最后,以一个含三微网群的主动配电网为例,在PSCAD/EMTDC仿真平台上,验证了所提控制策略的有效性。