Delphi环境下目标规划图解法算法程序的开发

作为目标规划算法平台的一个重要组成部分,研究了多目标线性规划中的目标规划图解法算法程序的开发,以方便该方法在各领域的应用。首先,介绍了目标规划的原理、建立目标规划模型的步骤。然后,介绍目标规划图解法的计算步骤以及在Del-phi环境下开发目标规划图解法的流程和具体方法。最后,通过实例对目标规划图解法算法程序的正确性进行了验证。所开发的算法程序直观简捷,方便工程人员的使用。     

核电厂电力电子化CRDM电源数字控制系统设计

为了使核电厂反应堆电力电子化控制棒驱动机构（CRDM）电源在不同工况下安全、可靠运行,研究了其数字控制系统设计方法。重点考虑了采样保持器和数字控制延时对系统稳定性的影响,并采用最佳阻尼设计方法对各级变换器控制器参数进行整定,形成了一套完整的电力电子化CRDM电源数字控制系统设计方法。仿真结果表明,系统稳态性能良好,并能够在负荷突变和故障切换等工况下快速、平稳地过渡到新稳态。该结果验证了所提设计方法的正确性和有效性。该设计方法对核电厂其他电力电子装置数字控制系统设计具有一定的指导意义。     

基于XYZ/SE的软件部分正确性验证

针对软件形式化描述和正确性验证研究中存在的问题,提出了基于XYZ/SE的统一框架研究该问题。在该框架下,基于逐步求精思路对软件进行抽象;对软件整体进行形式化描述和部分正确性验证;对抽象得到的软件各部分进行形式化描述和部分正确性验证;进行调整和验证,即：如果推导结果与预期不一致,则需要重写相关程序或者回溯检查推导过程是否存在错误,直至程序部分正确性得到验证为止。以国库信息处理系统为对象,分析了基于XYZ/SE的统一框架性能。分析表明,基于该框架能够对软件的不同抽象层次进行规范描述,实现从抽象（静态语义）到具体（动态语义）的平滑过渡。同时,基于XYZ/SE的统一框架也可以表示Hoare逻辑推演规则。     

浙江省中长期电力负荷需求预测分析

随着目前电力市场的深入改革，为了实现电网的规划合理，合理预测浙江省中长期电力需求非常必要，本文搜集了可能影响电力负荷的众多宏观经济影响因素，通过相关分析先去除一部分影响不大的因素，然后建立了一个浙江省中长期电力负荷预测的多元线性回归模型，并进行了模型的验证。验证结果表明该模型预测精度比较高，可以进行浙江省的中长期的电力负荷预测。对于科学编制浙江省电网中长期电力发展规划，促进电力工业与国民经济协调发展具有重要意义。     

命令式程序终止性验证方法综述

作为软件完全正确性的重要组成部分,程序终止性受到越来越多的关注。旨在跟踪国内外针对命令式程序的终止性验证方法,调研该领域的最新研究成果,同时提出解决该问题的建议性方法框架,对命令式程序终止性研究提供有意义的帮助。给出了程序终止性问题的定义,介绍了已有的数值程序、堆操作程序终止性验证方法,并分别进行了分析与对比。总结了当前研究中存在的难点与热点问题,给出了一种基于模型检验的C程序终止性验证框架,该框架可以作为研究命令式程序终止性的基本框架。     

基于BP神经网络的装甲车辆电源系统故障诊断方法研究

为实现装甲车辆电源系统故障诊断的智能化,在Simulink中建立爪极同步发电机数学模型和桥式不可控整流电路来构建装甲车辆电源系统基础模型,通过设置各类故障,采集不同的电压故障波形中的数据并进行归一化处理;在Matlab中编写、运行BP神经网络训练程序,得到网络模型,并取测试样本进行验证;结果证明了该训练后的神经网络的正确性,表明了BP神经网络在装甲车辆电源系统故障诊断中具有可行性,达到了对整流器故障诊断的目的。     

基于复杂适应理论的电力系统生产模拟

针对电力系统发展规划、需求侧管理、电力市场的理论和模拟研究工作对时序性、互动性、随机性生产模拟的需要,在智能工程的空间基础和方法工具支持下,根据复杂适应系统框架建立了生产模拟模型。模型通过用户需求模块、电网企业调度模块、电力市场模块和电源企业生产模块模拟电力系统的不同环节和功能,利用k-means聚类法、整数规划法等算法,模型实现了对系统的生产模拟,模拟结果与实际数据差异在可接受范围之内,可以在电力发展规划、需求侧管理、电力市场等相关分析研究方面起到一定支撑作用。     

有源电力滤波器降低容量控制策略研究

对有源电力滤波器(APF)能量流进行分析,得出决定APF容量的基本要素.针对复杂电源环境下APF的补偿目标,提出一种基于电源电流基波正弦化的降低容量控制策略,获取负载电流中的基波有功功率及基波无功功率,并获得补偿参考电流.为实现控制策略,提出适用于电源电压畸变情况下的三相电压基波正序检测的改进方法,减小APF变流电路总电流和自身损耗,提高了APF的效率.仿真和实验结果验证了该控制策略的正确性和有效性,对并联型APF的小型化及电力系统滤波改造具有实用的参考价值.     

航空地面电源检测仪可靠性分析

航空地面电源检测仪是新开发的航空地面电源测试产品,在产品投入生产前,需要对该产品的可靠性性能进行评估。本文建立了航空地面电源检测仪可靠性分析模型,应用该模型评估了航空地面电源检测仪的可靠性。实验验证表明了该评估模型的科学性、正确性。     

基于抽象域和数值熵协同的数值程序分析

在软件日益丰富的信息时代,程序的正确性验证问题需要深入地研究。提出了基于抽象解释和数值熵协同的数值程序正确性分析方法。利用抽象解释理论框架对数值程序进行抽象解释分析,提取不变量的抽象域区间;在抽象域区间上进行数值熵运算;运行程序获取数值变量的实际取值,计算数值熵;将抽象域区间数值熵和实际数值熵信息进行对比分析,准确地判断程序的正确性等性质。单纯的抽象解释分析只可以近似得到数值变量的取值范围,而引入数值熵算法,在取值范围的基础上对程序静态分析的准确性进一步检验,同时也做到了对程序的正确性验证。通过C语言程序实例,对抽象解释基础上的熵值分析方法进行了验证,证明了该分析方法的可行性和正确性。     

A Nested Benders Decomposition Approach to Locating Distributed Generation in a Multiarea Power System

A nested Generalized Benders decomposition scheme is used to solve a mixed-integer stochastic programming model. The model evaluates central station and distributed power generation, storage, and demand management assets on a linearized electric power transmission network. It considers temporal and spatial variations in the marginal cost of power, which are captured in the Benders cuts in the solution scheme. These variations are caused not only by differences in generating unit operating expenses and capacity expansion costs, but also by physical transmission constraints that can alter minimum cost dispatch and siting of these units. The transmission constraints addressed include limits on MW power flows and both of Kirchhoff's laws via a linearized DC load flow representation. The model consists of three modules: a stochastic linear production costing model for operating central system generation, a nonlinear program for planning central system generation and transmission, and a mixed-integer program for evaluation of local area distributed resources. Generalized Benders decomposition is applied twice to coordinate these modules. The production costing model is a subproblem to the central system planning model, which is in turn a subproblem to the distributed resource model. The coordination scheme is described in detail, including the calculation of marginal costs. An application shows the effects of marginal cost variations on capacity expansion decisions.     

基于多状态概率模型的新能源消纳能力分析

新能源发电装机规模日益增加,客观评价电网消纳新能源的能力是提高新能源渗透率又保证系统安全稳定运行的重要条件。本文基于新能源联合出力多状态概率模型,考虑系统调峰容量约束,利用新能源装机规模、损失电量及消纳电量在无约束情况下新能源理论可发电量中的占比等指标来综合评估电网的新能源消纳能力,进而提出一种基于多状态概率模型的新能源消纳能力分析方法。对某省2020水平年规划电网新能源消纳能力进行了实例分析,统计历史年新能源出力概率分布,并依据该统计结果求取了风电、光伏联合出力概率分布,利用该省电源、负荷等规划数据测算了系统剩余调峰容量,进而评估了新能源消纳能力,分析了状态数选择对分析结果的影响,验证了所提出方法的正确性和有效性。     

A Multiobjective Evolutionary Programming Algorithm and Its Applications to Power Generation Expansion Planning

The generation expansion planning (GEP) problem is defined as the problem of determining WHAT, WHEN, and WHERE new generation units should be installed over a planning horizon to satisfy the expected energy demand. This paper presents a framework to determine the number of new generating units (e.g., conventional steam units, coal units, combined cycle modules, nuclear plants, gas turbines, wind farms, and geothermal and hydro units), power generation capacity for those units, number of new circuits on the network, the voltage phase angle at each node, and the amount of required imported fuel for a single-period generation expansion plan. The resulting mathematical program is a mixed-integer bilinear multiobjective GEP model. The proposed framework includes a multiobjective evolutionary programming algorithm to obtain an approximation of the Pareto front for the multiobjective optimization problem and analytical hierarchy process to select the best alternative. A Mexican power system case study is utilized to illustrate the proposed framework. Results show coherent decisions given the objectives and scenarios considered. Some sensitivity analysis is presented when considering different fuel price scenarios.      

Transmission planning for Indian power grid: a mixed integer programming approach

The paper presents a modeling framework to analyze some important issues associated with operation planning of a power system. Major activities involved in operations planning of large integrated power systems are considered simultaneously to ensure optimal utilization of generation and transmission capacity. The model also examines optimal transmission expansion plans vis-à-vis fuel supply issues. A mixed integer programming model is developed for this purpose and the Indian power system considered. Specific emphasis is on spatial transmission expansion plan for the existing Indian inter-state transmission grid and new transmission links, coordinated operation of the isolated regional grids and system benefits accruing from transmission expansion, enhanced fuel production and supply rescheduling to ensure efficient operation of various generating stations.     

A Multiple Objective Linear Programming Approach to Power Generation Planning with Demand-Side Management (DSM)

The optimization of an economic indicator has traditionally been the sole objective function of mathematical programming models for power generation expansion planning. Recently, however, other evaluation aspects, such as environmental concerns, were also given an explicit role as objective functions in mathematical models. Models become thus more realistic so that decision makers are able to grasp the inherent conflicts and trade-offs among the distinct objectives in selecting a best compromise plan. A significant change in the planning processes has also occurred concerning new planning methodologies integrating demand-side management (DSM) techniques, in an attempt to change the levels and forms of electricity use by the consumers. This paper presents a multiple objective linear programming model for power generation expansion planning incorporating DSM. The objective functions are the total expansion cost, the environmental impact associated with the installed power capacity and the environmental impact associated with the energy output. DSM is included by modelling it as a new generating group along with the generating alternatives from the supply side. Five categories of constraints are considered related to the reliability of the supply system, the availability of the generating units, the capacity of the DSM-equivalent generating group, the total capacity installed throughout the planning period, the pollutant emissions. Some results are presented derived by using an interactive method, aimed at assisting decision makers in a progressive and selective search of good compromise solutions.     

Modeling the effects of demand response on generation expansion planning in restructured power systems

Demand response is becoming a promising field of study in operation and planning of restructured power systems. More attention has recently been paid to demand response programs. Customers can contribute to the operation of power sys- tems by deployment demand response. The growth of customers＇ participation in such programs may affect the planning of power systems. Therefore, it seems necessary to consider the effects of demand response in planning approaches. In this paper, the impact of demand responsiveness on decision making in generation expansion planning is modeled. Avoidance or deferment in installation of new generating units is comprehensively investigated and evaluated by introducing a new simple index. The effects of demand responsiveness are studied from the points of view of both customers and generation companies. The pro- posed model has been applied to a modified IEEE 30-bus system and the results of the study are discussed. Simulation results show that reducing just 3% of the customers＇ demand （due to price elasticity） may result in a benefit of about 10% for customers in the long term.     

A method for generation and transmission planning

This paper presents a method for the optimal expansion planning of generation and transmission facilities in a power system for a given future demand. The planning problem is defined as to minimize the cost associated with the installation of generating stations, transmission lines and the operating costs of the system subject to constraints associated with the security of the transmission system and the limits on the capacities available for expansion at each power plant site and the maximum number of lines permitted in each right of way available for new construction.     

An energy planning approach based on mixed 0–1 Multiple Objective Linear Programming

Multiple Objective Linear Programming (MOLP) models have been widely used in the energy sector for taking into account several conflicting objectives pursued in energy planning. However, continuous variables are not suffcient to accurately represent discrete phenomena encountered in many practical decision situations, such as the power generation expansion problem. This paper presents a new approach based on a mixed 0–1 MOLP model and applied to the Greek electricity generation sector for identifying the number and output of each type of power units needed to satisfy the expected electricity demand in the future. The core of the model is a branch and bound algorithm, which has been properly modified for the multi-objective case and is capable of generating the whole set of effcient solutions. The results provided by this method is the extraction of the effcient combinations of the power generation units, and for each combination the effcient solutions determining electricity production from each unit.     

一种用于测试编译优化的程序控制结构生成算法*

代码优化是编译器的重要阶段,是编译技术的研究重点。优化算法复杂度高,需要有效地测试用例生成方法对其进行充分的测试。提出了一种测试用例自动生成方法,能直观简单地生成具有可优化成分的程序,有针对性地对编译优化进行有效测试。重点介绍了该方法的基础、程序控制结构生成算法,并介绍了基于本方法实现的一个编译器自动测试工具。     

Long range stochastic planning of generation considering overdesign

This paper presents a new model for the optimal expansion planning of generation facilities in Power Systems under uncertainties of demand forecasts and generator outages. The objective is to find an expansion strategy requiring minimum present worth of revenue requirements so that electric power can be supplied to consumers at a reasonably low price with high degree of reliability. System utility is evaluated in terms of its capacity to meet demand requirements under uncertain conditions. The design also aims at reducing the over design of the system which requires a large capital outlay. A method based on the preference order dynamic programming is presented to determine the long-range optimal expansion strategy. This avoids the drawbacks of the conventional dynamic programming methods and requires lesser number of alternatives to be considered for selection of the optimal expansion policy.