Lagrangian relaxation hybrid with evolutionary algorithm for short-term generation scheduling

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.     

Global optimization for power dispatch problems based on theory of moments

Non-convex of an optimal power dispatch problem makes it difficult to guarantee the global optimum. This paper presents a convex relaxation approach, called the Moment Semidefinite Programming (MSDP) method, to facilitate the search for deterministic global optimal solutions. The method employs a sequence of moments, which can linearize polynomial functions and construct positive semidefinite moment matrices, to form an SDP convex relaxation for power dispatch problems. In particular, the rank of the moment matrix is used as a sufficient condition to ensure the global optimality. The same condition can also be leveraged to estimate the number of global optimal solution(s). This method is effectively applied to {0,1}-economic dispatch (ED) problems and optimal power flow (OPF) problems. Simulation results showed that the MSDP method is capable of solving {0,1}-ED problems with integer values directly, and is able to identify if more than one global optimal solutions exist. In additional, the method can obtain rank-1 moment matrices for OPF’s counterexamples of existing SDP method, this ensures the global solution and overcomes the problem that existing SDP method cannot meet the rank-1 condition sometimes.     

高性能调度技术中应用程序调度模型设计--地理空间信息网格调度技术的研究

地理空间信息网格调度技术，要比传统的高性能计算中的调度技术复杂，原因是如果将全部网格资源作为一个应用程序的调度和执行目标，必将导致通信延迟、成本昂贵、执行低效等。为此，综合考虑应用程序特性、机器特性等，研究设计了地理空间信息网格高性能调度技术中的应用程序调度模型，包括地理空间信息网格应用程序分析；资源特性分析；应用程序分解；性能预测；资源调度；机器选择；任务映射；任务调度；任务调度器和调度器管理模块。以实现为不同的应用程序匹配不同的计算资源，提高计算资源的利用率和应用程序的执行效率。     

油库发油过程中的HSE管理

叙述了石油库在发油过程中的HSE管理；发油过程中的危害识别，包括识别范围和内容；发油过程中风险评价的常用基本方法和常见问题；发油过程中危险源的管理控制，包括建立危险源网络图、加强现场监控和制定应急预案。     

绝对时钟智能控制器的研制

介绍了一种日常参数智能控制器的研制及研制过程中的几个重要问题的解决方法。特别是用于城市照明及美化城市的彩灯的开、关时间智能控制方面，给出了依据当地绝对时间、经度、纬度进行昼夜时间计算的方法，使之在不接光电传感器情况下可跟踪季节的昼夜变化。控制系统采用８９Ｃ２０５１单片机，配有时钟日历芯片ＤＳ１２８８７，系统体积小、功能强、可靠性高。     

西津电站对南宁及贵港防洪的作用

江河中的闸坝、电站等水利工程的调度运行对其上下游城市防洪有着重要的作用。郁江上的西津电站在洪水期如何调度可减轻上游南宁及下游贵港的洪水压力?通过分析"2001 7"洪水的调度,论述调度过程的作用和效果,为以后的防洪调度提供决策参考。     

Decentralized adaptive coordinated control of multiple robot arms without using a force sensor

This paper presents a distributed adaptive coordinated control method for multiple robot arms grasping a common object. The cases of rigid contact and rolling contact are analyzed. In the proposed controller, the dynamic parameters of both object and robot arms are estimated adaptively. The desired motions of the robot arms are generated by an estimated object reference model. The control method requires only the measurements of the positions and velocities of the object and robot arms, but not the measurements of forces and moments at contact points. The asymptotic convergence of trajectory is proven by the Lyapunov-like Lemma. Experiments involving two robot arms handling a common object are shown.     

反应堆材料热物性数据库管理系统

衡量一个数据库的质量，不以要看其所包含的数据还应考虑数据库管理系统的使用功能。为了更有效地实施ＩＡＥＡ的ＣＲＰ（ＣｏｏｒｄｉｎａｔｅｄＲｅｓｅａｒｃｈＰｒｏｇｒａｍｍｅ）中有关建立反应堆材料热物性数据库的计划，并考虑到能使所收集的数据方便地为用户服务和进行广泛的国际交流，为此设计并编制了该数据库的软件管理系统ＴＰＳＹＳ。这个系统可在ＩＢＭ－ＰＣ（３８６，４８６）等兼容机上运行，采用人机对话、菜单提示、全屏幕操作。其主要功能有：数据库维护、数据检索、与大型计算程序ＭＡＴ－ＰＲＯ接口和与国际上现有的数据库ＴＨＥＲＳＹＳＴ接口。     

A coordinated reverse logistics system for regional management of multi-source hazardous wastes

This paper presents a coordinated reverse logistics (CRL) management system for the treatment of multi-source hazardous wastes in a given region, in this case, a specific high-technology manufacturing zone. A linear multi-objective analytical model is formulated that systematically minimizes both the total reverse logistics operating costs and corresponding risks. In addition to inter-organizational logistics operating factors, environmental concerns are considered and formulated as corresponding risk-related constraints. Using the proposed model, results of numerical studies indicate that when the aspect of risk-induced penalties is not considered, the operational costs of regional hazardous-waste management can be efficiently reduced by 58%, compared to the existing operational costs at the study site. In addition, it is also observed that the corresponding weight associated with the risk-induced objective function embedded in the proposed model seems to have a significant effect on the CRL costs.     

On-line emission and economic load dispatch using adaptive Hopfield neural network

This paper presents an adaptive Hopfield neural network (AHNN) based methodology, where the slope of the activation function is adjusted, for finding approximate Pareto solutions for the multi-objective optimization problem of emission and economic load dispatch (EELD). We have placed emphasis on finding solutions quickly, rather than the global Pareto solutions, so that our algorithm can be employed in large on-line power systems where variations in load are quite frequent. To enable faster convergence, adaptive learning rates have been developed by using energy function and applied to the slope adjustment method. The proposed algorithm has been tested on selected IEEE bus benchmark systems. The convergence of AHNN is found to be nearly 50% faster than the non-adaptive version.