用于智能电网的有差别射频充电传感器网络

针对应用于智能电网中的无线传感器网络(WSNs)节点能量受限问题,分析了基于无线射频充电技术的为传感器节点充电技术,改进了可持续无线充电传感器网络(SWRSNs),提出有差别射频充电传感器网络(DRRSNs)技术,增加节点的优先级设置,建立整数线性规划模型,用CPLEX求解模型确定标志性节点位置。求解数据表明:节点获得的能量平均提高105%,高优先级节点比低优先级节点平均多获得43%的能量,提高了节点的寿命,保证了WSNs的可靠性,但是路径访问效率平均降低了14%。     

The challenges of the unit commitment problem for real-life small-scale power systems

Small-scale power systems mainly present two particular problems when it comes to their modeling and solution. Due to their size, it is important to consider and meet various types of reserve requirements in order to have a reliable operation of the power system. It is also important to consider variable start-up costs in order to obtain a more accurate unit commitment. In this paper six different types of reserve requirements are considered for the unit commitment problem: spinning reserve, regulation reserve (AGC per unit), ten-minute reserve, ten-minute non-synchronized reserve, ten-minute operational reserve, and ten-minute distributed reserve. Additionally, a Mixed Integer Programming formulation is introduced to represent variable start-up costs. The model introduced here is currently in use by the Baja California (México) power system operator.     

考虑源荷特性的双层互动优化调度

针对含风电电力系统的风电消纳水平低及高峰谷差问题,提出了一种综合考虑电源侧与负荷侧特性的双层互动调度策略。该策略将源荷分层并各自建模,考虑分时电价等激励措施下可控负荷时空调节能力,以最小发电成本为目标优化电源组合,降低负荷峰谷差,增强常规机组提供旋转备用的能力。采用CPLEX对源荷双层互动模型优化求解。经验证,该策略在保证电网稳定运行的前提下,可进一步提高电力系统运行的经济性和调节能力,具有较好的实用性。     

Pattern-set generation algorithm for the one-dimensional multiple stock sizes cutting stock problem

A pattern-set generation algorithm (PSG) for the one-dimensional multiple stock sizes cutting stock problem (1DMSSCSP) is presented. The solution process contains two stages. In the first stage, the PSG solves the residual problems repeatedly to generate the patterns in the pattern set, where each residual problem is solved by the column-generation approach, and each pattern is generated by solving a single large object placement problem. In the second stage, the integer linear programming model of the 1DMSSCSP is solved using a commercial solver, where only the patterns in the pattern set are considered. The computational results of benchmark instances indicate that the PSG outperforms existing heuristic algorithms and rivals the exact algorithm in solution quality.     

考虑碳捕集电厂能量转移特性的弃风消纳多时间尺度调度策略

风电预测精度和火电厂的调节速率对于风电消纳影响较大。考虑到风电预测精度随预测时间尺度的缩短而提高,同时计及碳捕集电厂更深的调节范围和更快的调节速率,提出提高电力系统弃风消纳水平的多时间尺度优化调度策略。首先,将其分为日前、日内、实时调度阶段,分析各个阶段的相互关系,并对碳捕集电厂不同时间尺度下的调度策略进行研究,分析其对于解决弃风消纳问题的合理性。其次,建立日前、日内、实时三时间尺度优化调度模型,并分析实时阶段碳捕集电厂调节量和风电调整量的关系。最后,基于IEEE39节点电网模型并利用CPLEX对该文方法应对弃风消纳以及失负荷情况的有效性进行仿真验证。     

冷热电联供型微电网优化运行及敏感性分析

冷热电联供型(CCHP)微电网是一种以联供设备为核心,包含多种分布式单元存在冷热电三种能量平衡的微电网形态,具有能源利用率高、供电可靠性高、环境污染小、调度灵活等特点。文中建立由多种微电源数学模型和约束条件组成的混合整数规划模型,使建立的系统更实际情况。从微电网经济调度运行出发,在满足微电网冷热电负荷需求下,以系统的整体费用最小为优化目标,采用CPLEX优化软件求解,仿真了各月典型日的优化运行,从仿真结果可以了解不同电源在不同时段的出力情况,使电源经济运行。同时对天然气价格进行敏感性分析,分析该价格对各电源出力情况的影响。     

考虑转换约束的汽车混流装配线投产排序研究

讨论了有生产线线边替补人员协助完成超载工作量的情况下,汽车混流装配线投产排序的问题,并且考虑工作人员行走占用的时间。通过对某整车厂进行实地调研,将汽车装配生产中的优化问题从以往文献中只考虑的总装车间向前延伸到涂装车间,给出连续喷涂某种颜色的车辆数的上界s。在此基础上,并考虑总装线线边物料消耗速率波动均衡和子装配工负荷均衡的约束条件,建立涂装切换成本和总装车间人工成本最小化的数学模型。最后,用CPLEX对模型进行优化求解,并分析得出生产节拍和工作站长度等参数与总成本之间的变化关系。     

基于计算物流的自动化集装箱码头AGV生产调度

针对自动化集装箱码头自动导引车（Automatic Guided Vehicle,AGV）在线实时生产调度约束动态复杂和难以可视化的问题,本文在计算物流框架下,利用AnyLogic平台创建自动化码头水平运输计算实验模型并针对平台中已有的经典资源分配策略,面向AGV生产调度提出两方面的改进。一、将运筹规划商业求解器与计算实验平台结合求解动态复杂组合优化问题;二、基于计算物流的思想方法,迁移和定制出五种面向问题探索的自定义AGV在线调度算法。由于商业求解器的局限性,模型和实验数据是基于自动化码头进口箱作业部分。实验表明,两种改进策略能够弥补商业求解器和计算实验平台的部分不足,尤其是自定义策略相较于经典资源分配策略能够面向特定装卸船需求更好地实现AGV生产调度,实现自动化码头水平运输的高效作业。     

考虑综合需求响应的电热系统优化调度

考虑配电网中电、热负荷的不断增长,以及热电联产装置(Combined heat and power,CHP)和风机等分布式电源的迅速发展,提出考虑电、热综合需求响应的优化模型。首先,在负荷侧分析电负荷和热负荷的可调价值,电负荷建立实时电价模型,采用价格型需求响应进行调整；热负荷是考虑热负荷的传输延迟特性,采用自回归滑动平均(ARMA)模型描述和计及模糊性供热舒适度特性,使得热负荷具有一定的弹性,即热力需求响应,通过这两种响应模式对电、热负荷进行调整,增大风电上网的空间；其次在源侧增加电锅炉和储热装置,增加系统的灵活性,解耦CHP“以热定电”的刚性需求,最后以系统的日运行费用与弃风成本最小为目标,在Matlab中调用CPLEX对模型进行求解。算例结果表明,在源侧采用CHP+电锅炉和储热相比于传统的CHP+储热,风电的消纳能力有显著提升；在荷侧考虑电、热综合需求响应相比于传统的考虑单一需求响应,可有效的降低系统的运行成本,提高能源的利用效率。     

A multi-step approach for block-cave production scheduling optimization

Production schedules that provide optimal operating strategies while meeting practical, technical, and environmental constraints are an inseparable part of mining operations. Relying only on manual planning methods or computer software based on heuristic algorithms will lead to mine schedules that are not the optimal global solution. Mathematical mine planning models have been proved to be very effective in supporting decisions on sequencing the extraction of material in mines. The objective of this paper is to develop a practical optimization framework for caving operations’ production scheduling. To overcome the size problem of mathematical programming models and to generate a robust practical near-optimal schedule, a multi-step method for long-term production scheduling of block caving is presented. A mixed-integer linear programming (MILP) formulation is used for each step. The formulations are developed, implemented, and verified in the TOMLAB/CPLEX environment. The production scheduler aims to maximize the net present value of the mining operation while the mine planner has control over defined constraints. Application and comparison of the models for production scheduling using 298 drawpoints over 15 periods are presented.