中央空调系统节能设计与运行控制策略研究

根据大型商场中央空调系统运行原理,建立了商场"冷负荷需求模型",提出了节能设计与节能运行控制策略.假设人流或室外温度在一定范围内变化,对商场"冷负荷需求模型"进行误差分析.以某大型商场实际运行数据为例,求出某商场人流与电器设备的冷负荷,给出其误差范围,并验证了模型合理性.以保持商场内部温度尽可能稳定且节能为目标,在冷冻水、冷却水流量以及制冷机运行台数等约束条件下,建立多目标规划模型;并进行求解分析,给出优化控制策略.利用模型按"日"计算出夏季合理基准冷负荷;求出在商场设定温度提高1度时,其合理基准冷负荷减少量.     

基于冷负荷需求的空调节能控制模型

针对商场中央空调的节能控制问题,首先建立了基于空调运行模式、经验值的冷负荷计算模型,给出了4种计算方法,并得出了人体冷负荷和照明电气设备冷负荷值的范围;然后对人流量分布进行合理假设,得出了商场冷负荷的函数表达式,讨论了冷负荷的误差范围,并用最小二乘方法对表达式进行了修正;再根据冷负荷的表达式建立了基于能量需求的空调节能模型,得出了制冷机组的控制策略,并给出了节能效果;最后计算出了基准冷负荷的值以及当商场温度升高1度基准冷负荷的减少比例.     

中央空调系统节能控制的全局优化模型

首先通过分析得出商场内各产热单元的冷负荷,给出商场内总冷负荷关于人流量和商场温度的表达式;然后分别用优化方法和解超定方程方法求出商场内人流量随时间的变化;最后采用全局优化原理对中央空调系统的节能控制进行建模,实现了整个中央空调系统的能耗最小化.     

中央空调系统节能设计问题

通过分析中央空调系统的工作原理,针对中央空调系统节能设计中的几个关键问题做了探讨和计算.在已有数据欠缺的条件下,通过拟合恢复部分原始数据,利用双目标规划建立了符合维持温度和节能要求的数学模型,基于冷负荷控制算法给出了相应控制策略.     

空调冷热源方案评选数学模型的建立及应用

从空调冷热源设计的实际需要出发 ,建立了层次分析法数学模型作为方案评选依据 ,并采用了一种构造良好一致性判断矩阵的新建模方法 ,以保证所建立的数学模型具有较强的工程实用性 ,更有利于在计算机上实现 .使用该模型对某大厦中央空调系统冷热源设计的具体实例进行了计算 ,得出了合理的结论     

考虑气象因素的短期负荷预测模型研究

短期负荷预测是针对未来一天到数天各时段的负荷预测的研究,是电力系统负荷预测工作的一项重要内容.针对传统神经网络预测模型应用于短期负荷预测的缺陷,改进了多角度数据分析和组织策略,选择不同年份相近历史日作为相似日,通过最小二乘支持向量机填补确实数据,利用聚类算法预测相似日的短期负荷;同时通过灰度关联算法,考虑气象因素作用下的短期负荷预测模型.实例证明:通过建立与负荷数据相适应的数学模型,对负荷数据进行分析与预测,通过气象因素修正预测模型,可以获得更精确的负荷数据预测.     

基于回归BP神经网络误差分级迭代法的逐时气温预测方法研究

气温预测是天气预测中的一项主要内容,由于气温的影响因素多而复杂,要想达到精细化预测目的,仍是十分复杂的科学难题.当前学术界的一般方法是假设数学模型对温度物理过程进行研究,建立了BP神经网络模型、温度与相对湿度之间的回归模型,最终在回归模型的基础上通过改进的BP神经网络建模,即利用BP神经网络误差分级迭代法建模,通过历史温度进行逐时气温预测,全样本误差达到0.617℃.     

基于PLSIM模型的住房建筑物能耗分析

采用牛津大学Angeliki Xifara使用Ecotect系统模拟的768个不同建筑物数据,尝试将半参数中的部分线性单指标模型(PLSIM)用于住房建筑物负荷的预测研究中。同时采用BP神经网络以及迭代加权最小二乘法分别建立热负荷、冷负荷预测模型,将3种方法所得结果进行比较。研究结果表明部分线性单指标模型在建筑物负荷预测中相对误差均在0.00104以内且更直观,可以为国家调整住房结构、节约能源提供有力的模型支持。     

打折问题

假期带学生进行社会调查 ,发现了一个现象 :正值换季 ,商场为了促销推出了一系列优惠活动 ,有的商场打折 ,如 8.5折 ;有的采用满一定金额送购物券的形式 ,如满 2 0 0送4 0 .经观察发现 ,同样品牌的同种商品在各商场的原售价是相同的 .该进哪家店消费才合算呢 ?我们可以建立一个简单的数学模型来解决 .不妨设打 8.5折的商场为甲 ,满 2 0 0送4 0的商场为乙 .假设计划消费都为x(x >0 )元 ,在甲商场的实际消费为 y1元 ,在乙商场的实际消费为 y2 元 ,则可得函数关系式 :y1=0 .85x ,y2 =x ,　　　　x <2 0 0 ;x - 40 ,　　2 0 0≤x <4 0 0 ;x - 80…     

带有优惠券销售的商品利润模型及其求解

根据"满100元返x元"的优惠券的特点,建立了商场商品在保持原来定价的基础上、以商家利润最大化为目的的数学模型;同时,利用遗传算法对此模型优化求解,仿真结果说明该模型及其解法具有一定的实用价值.     

公路客运监管的进化博弈分析

运用进化博弈理论研究公路客运监管问题,建立了公路客运监管问题的博弈模型,分析了公路客运车主和公路客运管理者之间的行为选择,得到了博弈方的复制动态方程,研究了博弈模型的进化稳定策略。探讨了影响进化稳定策略的因素。研究结果表明公路客运车主和公路客运管理者在有限理性基础上得到的进化稳定策略与博弈双方的收益、系统所处的初始状态有关,并根据所提出的博弈模型,提出了合理性建议。     

Optimizing the release of passenger flow guidance information in urban rail transit network via agent-based simulation

The passenger flow guidance is an effective demand management strategy to alleviate the excessive congestion in the urban rail transit network. In order to determine the scope and the timing, a simulation-based optimization model is proposed to optimize the release of passenger flow guidance information in the rail transit network in this paper. In the optimization model, we mainly focus on three aspects namely; where, when and what type of the guidance information should be released to the passengers. In the simulation model, the passenger choice behavior is captured by the agent-based simulation method, which responses to the congestion and the guidance information. Based on this, the dynamic passenger flow distribution can be derived. Furthermore, the adoption rate of the displayed guidance information on passenger information system as well as its impact on passenger travel behavior are also considered in the model. A hybrid heuristic solution algorithm, integrated with passenger simulator and genetic algorithm, is developed to solve the proposed simulation-based optimization model. Finally, a case study of Beijing subway is carried out with the large-scale smart card data. The numerical study shows that the passenger flow demand affects the guidance effect significantly and the best guidance effect can be met with sufficiently high passenger flow demand. And the guidance rate is also found to affect the guidance results. The results also show that the proposed model can provide a detailed guidance scheme for every station at selected time intervals. The results show that the dynamic releasing scheme can save up to a total of 46,319 min in passenger travel time during a single guidance period.     

Passenger flow control strategies for urban rail transit networks

Urban rail traffic congestion is becoming increasingly serious due to the large traffic demands in modern cities. In order to ensure the safety and quality of station services in peak hours, it's necessary to adopt some reasonable and effective passenger flow control strategies. In this study, through considering the time-dependent passenger demands, a passenger flow control model based on the network-level system is explicitly developed. The passenger successive motion process is discretized by the modeling method. Systematically considering the coordinated relationship between traffic demands and strict capacity constraints (including station passing capacity, platform load capacity and train transport capacity), we establish a mixed integer linear programming model to minimize the total passenger waiting time (including passengers outside stations and on the platforms). The optimization software Cplex is adopted to solve the developed model, and a real network of Beijing urban railway is calibrated to verify the effectiveness of the suggested model. As a result, the proposed flow control strategies can provide detailed information about control stations, control durations and control intensities, and can effectively reduce the total waiting time and relieve the number of stranded passengers in the urban rail transit network.     

An integrated thermal model of hot rolling

During the heavy plate rolling process, different production steps, i.e., roll passes, descaling passes, and air cooling periods, influence the temperature evolution of the plate. All these relevant aspects are covered by a one-dimensional thermal model proposed in this paper. Experiments were conducted in a rolling mill under realistic rolling conditions to parametrise and validate the model. Using pyrometer measurements, a simple model adaption strategy is developed, which can cope with uncertainties in the initial temperature profile. The model provides accurate predictions of the temperature evolution of the plate during the whole rolling process from the plate’s exit of the furnace to the last pass. Thus, it can be used for scheduling the production process. Based on the model, an observer can be designed.     

An efficient linear model and optimisation algorithm for multi-site combined heat and power production

Combined heat and power (CHP) production is an important energy production technology which can help to improve the efficiency of energy production and to reduce the emission of CO₂. Cost-efficient operation of a CHP system can be planned using an optimisation model based on hourly load forecasts. A long-term planning model decomposes into hourly models, which can be formulated as linear programming (LP) problems. Such problems can be solved efficiently using the specialized Power Simplex algorithm. However, Power Simplex can only manage one heat and one power balance. Since heat cannot be transported over long distances, Power Simplex applies only for local CHP planning.In this paper we formulate the hourly multi-site CHP planning problem with multiple heat balances as an LP model with a special structure. We then develop the Extended Power Simplex (EPS) algorithm for solving such models efficiently. Even though the problem can be quite large as the number of demand sites increases, EPS demonstrates very good efficiency. In test runs with realistic models, EPS is from 29 to 85 times faster than an efficient sparse Simplex code using the product form of inverse (PFI). Furthermore, the relative efficiency of EPS improves as the problem size grows.     

Transit passenger origin-destination estimation in congested transit networks with elastic line frequencies

This paper deals with the transit passenger origin-destination (O-D) estimation problem by using updated passenger counts in congested transit networks and outdated prior O-D matrix. A bilevel programming approach is extended for the transit passenger O-D updating problem where the upper-level problem seeks to minimize the sum of error measurements in passenger counts and O-D matrices, while the lower level is the stochastic user equilibrium assignment problem for congested transit networks. The transit assignment framework is based on a frequency-adaptive transit network model in this paper, which can help determine transit line frequencies and the network flow pattern simultaneously in congested transit networks. A heuristic solution algorithm is adapted for solving the transit passenger O-D estimation problem. Finally, a numerical example is used to illustrate the applications of the proposed model and solution algorithm. The work described in this paper was mainly supported by two research grants from the Research Grants Council of the Hong Kong Special Administrative Region (Project No. PolyU 5143/03E and PolyU 5040/02E).     

基于智能控制的高速线材轧机水冷控制系统优化

针对武汉钢铁集团公司大型轧钢厂当前在高速线材生产线中存在的水冷控制系统可靠性差,轧线温度波动范围大等问题,应用智能计算理论及方法对上述工业控制系统进行系统辨识、建模以及优化.分析比较了基于梯度下降搜索BP算法、径向基函数网络、Levenberg Marquardt BP算法的前馈神经网络对SMS水冷系统的逼近精度、训练速度.研究了采用Levenberg-Marquardt BP算法的前馈神经网络在样本集和测试集上的表现,建立了基于Levenberg-Marquardt BP算法的前馈神经网络水冷控制系统模型.解决了高速线材水冷控制系统可靠性,温度控制精度问题.