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通常情况下换热网络系统是按照特定的参数设计的,但实际工程实施中往往有很多因素影响运行工况偏离设定值,造成原网络结构无法满足出口温度或者使得运行费用大大增加,因此运用旁路控制是改善网络操作弹性、调节物流出口温度和节能降耗的有效方法,而如何确定旁路位置是人们关注较多的一个问题。提出以运行费用为优化目标,以所有潜在旁路开度为调节变量进行优化计算,从而确定旁路位置及数目的设计方法。实际算例说明,通过增设旁路优化不仅提高了换热网络自由度和可控性,其运行费用也平均降低了2.2%,说明所提出方法对改善网络操作弹性和节能降耗的有效性。 相似文献
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风电的随机性和波动性增大了电网系统的调节压力,文章提出一种基于分层模型预测控制的源荷协调控制策略,该策略采用长、短时间尺度的多时间尺度滚动优化控制。长时间优化控制以最小弃风运行成本最优为目标,以长时间风电预测为状态变量,以常规电源功率、高载能负荷功率和风电出力为控制变量,优化求解计划基点。短时间滚动优化控制以风电实际出力与计划出力偏差最小为目标,以短时间风电预测出力为状态变量,以连续可调高载能负荷为控制变量,优化求解控制指令,对预测误差的影响做出修正。采用二次规划法对优化控制模型进行求解。最后以新疆某地区电网为例,验证了所提出控制策略的有效性和可行性。 相似文献
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虚拟电厂(virtual power plants,VPPs)已经成为对分布式新能源进行调度控制的重要方式,而由于日前新能源预测和负荷预测的误差,经常会影响调度策略并造成VPPs次优运行。提出了一种基于反馈校正控制模型预测控制的VPP自适应预测优化调度策略,以实现不确定性条件下VPPs的最优运行。该策略包括2个部分:滚动时域优化(receding horizon optimization, RHO)和反馈校正(feedback correction, FC)。RHO采用时间序列模型与卡尔曼滤波相结合的混合预测算法对RES和负载的输出功率进行预测,并根据预测结果进行调度。FC采用基于快速滚动灰色模型的超短期误差预测,对RHO策略进行调整。FC用于最小化调整,以补偿预测误差。所提策略在某实际配电系统的VPP上实施,结果表明,其能更好地跟踪系统内实际可用资源,且供需之间的不匹配程度最小。 相似文献
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为了确定冷却蒸汽旁路管道设计和旁路蝶阀选型的依据,制定联通管蝶阀和旁路蝶阀协同控制的策略.本文结合某火力发电厂600 MW超临界湿冷汽轮发电机组切缸供热运行情况,通过所开发的计算机程序,对联通管蝶阀10%开度时,不同前后差压下的蒸汽通流量进行了计算,以计算所得最大容积流量确定旁路管道为DN500;旁路蝶阀规格选择DN500时,在30.6%开度下的蒸汽通流量与联通管蝶阀10%开度下相同,旁路蝶阀开度处于阀门调节特性较好的范围内;通过计算得到了过渡阶段和切缸状态下的阀门开度曲线,为协同控制策略的制定提供了指导. 相似文献
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针对风电场预测功率与实际功率不匹配以及风力发电不确定性问题,提出一种以补偿风电预测误差和平抑风电波动为目标的储能控制策略。该策略以先进控制理论为基础,结合储能补偿预测区间和储能平抑风电波动区间,提取考虑储能运行成本的储能最优滚动控制域。首先,针对储能补偿预测误差目标,制定储能控制策略,提取允许误差内的储能补偿区间;其次,考虑风电功率波动要求及荷电状态(SOC)约束,采用模型预测控制求解出储能滚动控制序列,确定储能平抑区间。最后,考虑储能运行成本,将补偿区间和平抑区间相结合,制定储能最优滚动控制区间,以此为基础确定储能容量。以中国新疆某风电场为例,对该文提出的储能控制策略与传统控制策略进行对比验证,验证所提策略的可行性和有效性。 相似文献
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现有的节点非结构模型(Node-wise non-structural superstructure, NW-NSS)在优化换热网络时需要预设固定的节点分流数量,难以满足结构进化过程对于求解空间和计算效率的需求,易造成换热单元生成空间受限,影响算法全局优化性能。本文提出一种流股分流动态调节策略,该策略基于实时结构的整型变量分布信息,动态增加结构进化所需的必要分流并减少无效结构对优化的阻碍,辅助算法以更高的效率跳出局部极值,提升优化质量。将策略应用于16SP、20SP算例,分别得到年综合费用为6 653 940和1 711 886$/a的最优换热网络结构,较文献最优结果降低了3 140和3 202$/a。 相似文献
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为监测间接空冷散热器的换热性能,提出了监测间接空冷塔出水温度的方法。根据间接空冷系统散热器传热量计算和热平衡方程,分析了间接空冷塔出水温度的影响因素,建立了以环境温度、环境风速、大气压力、间接空冷塔循环水进水温度、循环水进水压力、出水压力和百叶窗开度7个主要参数为输入,出水温度为输出的BP神经网络模型。为避免该模型陷入局部最优,采用非线性动态惯性权重的粒子群优化(PSO)算法对BP神经网络模型的初始权值和阈值进行了优化,构建了PSO-BP神经网络预测模型,并根据某660MW间接空冷机组的运行数据对该模型进行了训练和验证。结果表明:采用PSO算法优化的BP神经网络模型具有较强泛化能力,预测精度高于单纯的BP神经网络模型,预测平均绝对百分比误差为0.55%。 相似文献
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《Applied Energy》2007,84(9):893-903
A diabatic distillation model is improved and the effects of the allocation of a heat-exchanger inventory on the diabatic-distillation performance are taken into account. Minimizing the entropy-production rate of the diabatic distillation column is taken as the optimization objective and the allocations of the heat-exchanger inventory on each tray in the diabatic distillation column are optimally redistributed under the condition of the fixed total heat-exchanger inventory. The optimal performance of the diabatic distillation column is obtained. The diabatic distillation model is meaningful for the design and optimization of diabatic distillation plant. 相似文献
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分布式光伏发电的高密度接入给配电网原有的经济、稳定运行带来了不小的挑战。为了减少分布式光伏发电接入配电网造成的网络损耗,提高光伏发电的经济性,首先分析和归纳了分布式光伏集群的概念和特点;然后针对配电网内的分布式电源、柔性负荷、无功功率调节设备等装置在时间尺度、控制功能方面的调节特性,提出了一种含分布式光伏集群的协调优化调度方法。该方法以模型预测控制为基础,动态滚动协调光伏集群未来一段时间内的有功出力和无功出力,起到减小网络损耗和优化系统电压的作用。采用PG & E 69节点系统在MATLAB数学软件下进行建模仿真分析,结果证明了所提优化控制方法的可行性和有效性。 相似文献
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This paper demonstrates the use of artificial neural networks virtual sensors in emissions prediction and control for a gasoline engine. Tailpipe emissions and engine parameters were first measured experimentally to form a comprehensive database for network training and testing. Individual predictive models were constructed using the optimization layer-by-layer neural network. Simulation results demonstrated that the networks, as virtual sensors, can accurately predict the engine parameters and emissions quantitatively and qualitatively with RMS errors below 9%. The second part of this paper then presents a virtual sensor control model which is the combination of the two individual emissions and engine predictive models developed previously. The main objective of this part is to control the exhaust emissions within the desired limits by predicting optimum engine parameters with the use of artificial neural network virtual sensors. Results showed that the emissions levels were successfully controlled within the defined limits, with maximum tolerance of 6%. This first part of this paper demonstrated that with the use of artificial neural network virtual sensors, emissions and engine parameters can be accurately predicted. Hence with accurate virtual sensors, emissions were then controlled within the desired limits by optimizing the engine parameters. This proposed work demonstrated a viable and accurate methodology in emissions predictive and control. By applying virtual sensor models, the need additional, cumbersome and costly measuring and monitoring devices can be eliminated. 相似文献
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《Applied Energy》2005,82(2):181-195
In this paper, in the viewpoint of finite-time thermodynamics and entropy-generation minimization are employed. The analytical formulae relating the power and pressure-ratio are derived assuming heat-resistance losses in the four heat-exchangers (hot- and cold-side heat exchangers, the intercooler and the regenerator), and the effect of the finite thermal-capacity rate of the heat reservoirs. The power optimization is performed by searching the optimum heat-conductance distributions among the four heat-exchangers for a fixed total heat-exchanger inventory, and by searching for the optimum intercooling pressure-ratio. When the optimization is performed with respect to the total pressure-ratio of the cycle, the maximum power is maximized twice and a ‘double-maximum’ power is obtained. When the optimization is performed with respect to the thermal capacitance rate ratio between the working fluid and the heat reservoir, the double-maximum power is maximized again and a thrice-maximum power is obtained. The effects of the heat reservoir’s inlet-temperature ratio and the total heat-exchanger inventory on the optimal performance of the cycle are analyzed by numerical examples. 相似文献
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基于神经网络和混合遗传算法的凝汽器真空优化控制 总被引:1,自引:0,他引:1
利用人工神经网络进行凝汽器真空建模,然后采用混合遗传算法对运行工况寻优,以获得各种工况下凝汽器的最佳运行方式。通过对某电厂的300MW机组现场热态试验与计算,表明该方法可以指导运行人员进行凝汽器真空的优化调整。 相似文献
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基于模块化多电平换流器的高压直流输电系统(MMC-HVDC)具有广阔的发展前景,针对常规控制方法在不平衡网压下存在控制复杂且换流器内部能量难以控制等缺陷,提出基于多目标递阶模型预测理论的模块化多电平换流器(MMC)能量协同控制策略。该方法通过优化控制各桥臂的各电流分量来调节MMC功率分布,实现交流侧三相电流与换流器内部能量平衡的协同控制;为简化控制复杂度、降低控制计算量,对传统模型预测控制进行优化,建立相应的预测模型和目标函数,并将控制目标划分为内部和外部特性的分层控制,利用外部特性控制的最优解及内部特性分析结果,优化内部特性控制的寻优范围。最后,通过仿真和实验的结果验证所提出的控制策略能更快实现正常及交流侧不平衡工况下的换流器安全稳定运行。 相似文献
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Using mechanical ventilation with highly efficient heat-recovery in northern European or arctic climates is a very efficient way of reducing the energy use for heating in buildings. However, it also presents a series of problems concerning condensation and frost formation in the heat-exchanger. Developing highly efficient heat-exchangers and strategies to avoid/remove frost formation implies the use of detailed models to predict and evaluate different heat-exchanger designs and strategies. This paper presents a quasi-steady-state model of a counter-flow air-to-air heat-exchanger that takes into account the effects of condensation and frost formation. The model is developed as an Excel spreadsheet, and specific results are compared with laboratory measurements. As an example, the model is used to determine the most energy-efficient control strategy for a specific heat-exchanger under northern European and arctic climate conditions. 相似文献