A multi-energy inertia-based power support strategy with gas network constraints

An integrated energy system with multiple types of energy can support power shortages caused by the uncertainty of renewable energy. With full consideration of gas network constraints, this paper proposes a multi-energy inertia-based power support strategy. The definition and modelling of gas inertia are given first to demonstrate its ability to mitigate power fluctuations. Since partial utilization of gas inertia can influence overall gas network parameters, the gas network is modelled with an analysis of network dynamic changes. A multi-energy inertia-based power support model and strategy are then proposed for fully using gas-thermal inertia resources in integrated energy systems. The influence of gas network constraints on strategy, economy and power outputs is analyzed. Special circumstances where the gas network can be simplified are introduced. This improves the response speed and application value. The feasibility and effectiveness of the proposed strategy are assessed using a real scenario.     

An energy-efficient multi-objective integrated process planning and scheduling for a flexible job-shop-type remanufacturing system

This study considers an energy-efficient multi-objective integrated process planning and scheduling (IPPS) problem for the remanufacturing system (RMS) integrating parallel disassembly, flexible job-shop-type reprocessing, and parallel reassembly shops with the goal of realizing the minimization of both energy cost and completion time. The multi-objective mixed-integer programming model is first constructed with consideration of operation, sequence, and process flexibilities in the RMS for identifying this scheduling issue mathematically. An improved spider monkey optimization algorithm (ISMO) with a global criterion multi-objective method is developed to address the proposed problem. By embedding dynamic adaptive inertia weight and various local neighborhood searching strategies in ISMO, its global and local search capabilities are improved significantly. A set of simulation experiments are systematically designed and conducted for evaluating ISMO’s performance. Finally, a case study from the real-world remanufacturing scenario is adopted to assess ISMO’s ability to handle the realistic remanufacturing IPPS problem. Simulation results demonstrate ISMO’s superiority compared to other baseline algorithms when tackling the energy-aware IPPS problem regarding solution accuracy, computing speed, solution stability, and convergence behavior. Meanwhile, the case study results validate ISMO’s supremacy in solving the real-world remanufacturing IPPS problem with relatively lower energy usage and time cost.     

基于程序模块化建模的智慧电站一体化平台构建

为实现在智慧电站高度一体化融合的同时,提高电站报警响应时效性和准确性,开展基于程序模块化建模的智慧电站一体化平台构建。通过电子式互感器选型、全站智能组件装置整合等硬件设计和基于程序模块化建模的三维一体化信息模型构建、电站门禁管理与人员轨迹跟踪、电站危险源识别与动态预警等软件设计,提出一种全新的智慧电站一体化平台。通过将新的平台应用到某电站火电厂中,验证了该平台能够实现对电站异常故障问题的快速响应,并保证误报警次数始终为0,在促进智慧电站安全性不断提升的同时,实现高度一体化融合。     

Integrated Risk of Progress-Based Costs and Schedule Delays in Construction Projects

This article aims to explore the impact of the integration of risk factors into delayed milestones for construction projects. A simulation model was developed to determine the impact of schedule variability on cost estimation. To generate random scenarios a Monte Carlo Simulation (MCS) technique was applied. The developed model computes the cost impact of delayed milestone in the expected budget. Using a risk integration approach revealed the critical time frame that may lead to a budget deficit for a project. As a result, a number of cost-sensitive risk factors and schedule delays were identified for the critical time period where the risk of budget deficit increases. The method of integration proposed in this article highlights the priority of risk factors and schedule delays for construction contracts involving Payments at Event Occurrences (PEO). Consequently, the developed method can be useful for practitioners in anticipation of potential increase of costs, hence, prevention of failure due to budget deficit.     

火电厂辅控系统的集成与应用

国内大多数火电厂的辅助控制系统都是按功能独立运行的,这样就造成了人力资源的浪费和调度指挥的困难,而采用辅控系统的集成则很好地解决了这一难题。它利用现代通信技术将基于计算机控制的辅控系统进行互联,从而实现对辅控系统的集中监视和控制,并完成了它与厂级监控信息系统、电厂管理信息系统及分散控制系统之间的数据共享。该系统大大提高了电厂的管理效率,减少了运营成本。辅控系统一体化设计的成功,证明火电厂一体化控制必将成为日后主要的发展方向。     

基于乘积季节模型的GPRS小区流量预测

针对GPRS小区流量预测问题,提出一种基于乘积季节自回归移动平均模型的解决方法。该方法分析GPRS小区流量的变化情况,利用小区流量以天为周期变化的特点,应用该模型进行建模,得到GPRS小区的流量变化预测模型。该预测模型可以根据GPRS小区过去的流量情况,预测将来某一时间的流量,为提前采取措施保持GPRS小区性能提供一定的决策依据。     

基于PTIDES执行策略的调度算法

分析现有PTIDES执行策略调度算法,综合考虑事件的截止期和执行时间,改进传统最小空闲时间优先算法,将空闲时间作为事件调度优先权,提出零空闲时间优先PTIDES调度算法——ZSFPTIDES。实例分析表明,ZSFPTIDES调度算法能避免事件在处理过程中因得不到及时处理而夭折的现象,减小事件的抢占切换率,优化分布实时嵌入式系统的调度性能。     

A computer implementation of the partition of the unity procedure and its application to arthropod population dynamics. A case study on the European grape berry moth

This paper presents a new procedure to construct families of spatial approximation-prediction functions which depend on several parameters. The method is based on partitions of the unity. In order to find optimal functions in these families we introduce a Vietoris simplicial set associated to an influence radius. We consider error estimators induced by these Vietoris simplicial sets. A computational implementation of these mathematical models has been developed to be applied to any kind of finite discrete data. Our methods provide a useful tool for the analysis of the spatial distribution of species, which is imperative for developing accurate and efficient management of endangered and invasive species, biological conservation programs, etc. We demonstrate the application of our method to the analysis of the spatial distribution of the grape moth Lobesia botrana (Lepidoptera: Tortricidae) in the vineyards of La Rioja obtaining useful results for the management of this pest.     

Combined planning and scheduling in a divergent production system with co-production: A case study in the lumber industry

Many research initiatives carried out in production management consider process planning and operations scheduling as two separate and sequential functions. However, in certain contexts, the two functions must be better integrated. This is the case in divergent production systems with co-production (i.e. production of different products at the same time from a single product input) when alternative production processes are available. This paper studies such a context and focuses on the case of drying and finishing operations in a softwood lumber facility. The situation is addressed using a single model that simultaneously performs process planning and scheduling. We evaluate two alternative formulations. The first one is based on mixed integer programming (MIP) and the second on constraint programming (CP). We also propose a search procedure to improve the performance of the CP approach. Both approaches are compared with respect to their capacity to generate good solutions in short computation time.