Research on the Prediction of Load Regulation Capacity for Supercritical Thermal Power Unit

Both the modeling and the load regulation capacity prediction of a supercritical power plant are investigated in this paper. Firstly, an indirect identification method based on subspace identification method is proposed. The obtained identification model is verified by the actual operation data and the dynamic characteristics of the system are well reproduced. Secondly, the model is used to predict the load regulation capacity of thermal power unit. The power, main steam pressure, main steam temperature and other parameters are simulated respectively when the unit load is going up and down. Under the actual constraints, the load regulation capacity of thermal power unit can be predicted quickly.

Primary Frequency Control Ability Evaluation of Valve Opening in Thermal Power Units Based on Artificial Neural Network

With the development of new energy,the primary frequency control(PFC)is becoming more and more important and complicated.To improve the reliability of the PFC,an evaluation method of primary frequency control ability(PFCA)was proposed.First,based on the coupling model of the coordinated control system(CCS)and digital electro-hydraulic control system(DEH),principle and control mode of the PFC were introduced in detail.The simulation results showed that the PFC of the CCS and DEH was the most effective control mode.Then,the analysis of the CCS model and variable condition revealed the internal relationship among main steam pressure,valve opening and power.In term of this,the radial basis function(RBF)neural network was established to estimate the PFCA.Because the simulation curves fit well with the actual curves,the accuracy of the coupling model was verified.On this basis,simulation data was produced by coupling model to verify the proposed evaluation method.The low predication error of main steam pressure,power and the PFCA indicated that the method was effective.In addition,the actual data obtained from historical operation data were used to estimate the PFCA accurately,which was the strongest evidence for this method.

Source-Load Coordinated Optimal Scheduling Considering the High Energy Load of Electrofused Magnesium and Wind Power Uncertainty

In fossil energy pollution is serious and the“double carbon”goal is being promoted,as a symbol of fresh energy in the electrical system,solar and wind power have an increasing installed capacity,only conventional units obviously can not solve the new energy as the main body of the scheduling problem.To enhance the systemscheduling ability,based on the participation of thermal power units,incorporate the high energy-carrying load of electro-melting magnesiuminto the regulation object,and consider the effects on the wind unpredictability of the power.Firstly,the operating characteristics of high energy load and wind power are analyzed,and the principle of the participation of electrofusedmagnesiumhigh energy-carrying loads in the elimination of obstructedwind power is studied.Second,a two-layer optimization model is suggested,with the objective function being the largest amount of wind power consumed and the lowest possible cost of system operation.In the upper model,the high energy-carrying load regulates the blocked wind power,and in the lower model,the second-order cone approximation algorithm is used to solve the optimizationmodelwithwind power uncertainty,so that a two-layer optimizationmodel that takes into account the regulation of the high energy-carrying load of the electrofused magnesium and the uncertainty of the wind power is established.Finally,the model is solved using Gurobi,and the results of the simulation demonstrate that the suggested model may successfully lower wind abandonment,lower system operation costs,increase the accuracy of day-ahead scheduling,and lower the final product error of the thermal electricity unit.

500 MW Unit Simulator for Panshan Thermal Power Plant Passed Acceptance

After a thorough demonstration in Panshan Thermal Power Plant, the 500 MW super critical pressure unit simulator developed by the Simulation & Control Institute under the North China University of Electric Power was accepted by experts from the North China Electric Power Group Company on 3rd August 1996.

Study on Coal Consumption Curve Fitting of the Thermal Power Based on Genetic Algorithm

Coal consumption curve of the thermal power plant can reflect the function relationship between the coal consumption of unit and load, which plays a key role for research on unit economic operation and load optimal dispatch. Now get coal consumption curve is generally obtained by least square method, but which are static curve and these curves remain unchanged for a long time, and make them are incompatible with the actual operation situation of the unit. Furthermore, coal consumption has the characteristics of typical nonlinear and time varying, sometimes the least square method does not work for nonlinear complex problems. For these problems, a method of coal consumption curve fitting of the thermal power plant units based on genetic algorithm is proposed. The residual analysis method is used for data detection;quadratic function is employed to the objective function;appropriate parameters such as initial population size, crossover rate and mutation rate are set;the unit’s actual coal consumption curves are fitted, and comparing the proposed method with least squares method, the results indicate that fitting effect of the former is better than the latter, and further indicate that the proposed method to do curve fitting can best approximate known data in a certain significance, and they can real-timely reflect the interdependence between power output and coal consumption.

基于蝙蝠优化算法的电力系统经济调度

针对电力系统的优化调度问题,提出基于蝙蝠优化算法的运行策略,旨在降低发电机组的总燃料成本和减少污染物排放量.然而由于约束条件的复杂性,一般的数学方法难以解决这个难题.采用优化过的蝙蝠算法(NBA)来解决电力系统动态经济调度问题,为了验证优化过的NBA算法的性能,对一个含有6台火电机组的电力系统进行优化调度,并在Matlab软件中对模型进行了仿真和测试.以运行成本最小为目标函数,约束条件包含功率平衡约束、火电机组最大最小出力约束、火电机组爬坡约束、网络潮流约束等,然后使用NBA算法完成对电力系统优化调度决策任务,结果表明,优化过后的算法减少污染的同时降低了发电成本,提升了电力系统的效益.

集成蓄热装置的火电机组调峰特性分析

【目的】随着新能源的大规模发展,新能源出力不确定性和波动性问题展现出来,而为了弥补新能源出力缺点,火电机组承担起了调峰作用。为了提升火电机组的调峰能力,对其调峰特性进行了研究。【方法】首先,以某350 MW供热机组作为分析对象,应用仿真软件搭建热力系统模型,并验证该模型的精确性。其次,以蓄热系统为辅助系统,研究机组在满足供热需求情况下的机组调峰能力,并分析蓄热等储能单元对机组调峰能力的影响。最后,采用启发式粒子群算法对蓄热水罐运行策略进行优化,得到随热负荷变化的储热罐最优运行模式。【结果】通过蓄热水罐与火电机组耦合的方法有效提升了机组的调峰和供热能力,并提出可以根据实际热负荷数据确定最大化收益的运行模式。【结论】该方法对机组的运行策略具有指导意义。

火电耦合压缩空气储能技术研究进展及展望

火电耦合压缩空气储能技术作为一种提升传统火电机组灵活性和经济性的有效手段,近年来受到了广泛关注。该文从分析火电耦合压缩空气储能技术在提升电网调峰能力、促进可再生能源整合等方面的重要意义出发。首先,介绍典型耦合系统的结构组成与工作原理;然后,探讨耦合系统中关键设备的技术现状和面临的挑战;之后,梳理火-储耦合系统的集成方案设计、调峰运行优化以及经济性评估的研究现状;最后,针对当前技术难点,展望未来火电耦合压缩空气储能技术的研究方向与重点。该文旨在为今后相关领域研究提供参考与借鉴,推动其持续发展和创新。

Optimization of Minimum Power Output for Combined Heat and Power Units Considering Peak Load Regulation Ability

Northern China has rich wind power and photovoltaic renewable resources. Combined Heat and Power (CHP) Units to meet the load demand and limit its peaking capacity in winter, to a certain extent, it results in structural problems of wind-solar power and thermoelectric. To solve these problems, this paper proposes a plurality of units together to ensure supply of heat load on the premise, by building a thermoelectric power peaking considering thermal load unit group dynamic scheduling model, to achieve the potential of different thermoelectric properties peaking units of the excavation. Simulation examples show, if the unit group exists obvious relationship thermoelectric individual differences, the thermal load dynamic scheduling can be more significantly improved overall performance peaking unit group, effectively increase clean energy consumptive.

飞轮储能辅助火电机组一次调频及其性能评价

为促进太阳能、风能等新能源消纳,进一步拓宽火电储能技术升级和灵活性改造渠道,助力双碳目标和新型电力系统建设,提出增设储能系统辅助火电机组调频以解决火电机组爬坡慢、机组振荡不稳定等问题。基于国内外研究现状,提出机组以及储能系统荷电状态出力控制策略模型,通过Matlab/Simulink搭建两区域电网进行模拟仿真。结果表明,在阶跃扰动下区域1机组耦合1 MW飞轮储能系统后,峰值降至1.93×10^(-3)pu,降低4×10^(-4) pu,占原频率波动率的9.39%,机组实际出力从2.45×10^(-2)pu降至1.61×10^(-2)pu,降低34%。结果表明,在外界相同扰动条件下,采用飞轮储能辅助火电机组调频可有效减小系统频率波动量,减少汽轮机输出功率波动,提升调频性能。

基于麻雀算法优化支持向量机的NOx浓度预测

煤炭作为火电厂发电的主要能源,其在锅炉内焚烧过程中会产生大量的氮氧化物。各电厂一般利用烟气自动监控系统对其浓度进行实时测量,但由于测量时存在较大迟延,不能准确地反映SCR系统NOx浓度的实时变化。因此提出了一种基于改进麻雀算法优化最小二乘支持向量机的NOX浓度预测方法。首先,引入余弦因子改进麻雀算法中的比例算子,将迭代次数信息引入到迭代过程中,平衡算法前后期的全局与局部搜索能力。其次,使用新的变异算子代替原算子,将混沌理论融合到麻雀算法,解决了算法全局搜索能力较差、初始化麻雀分布不稳定及发现者位置更新方式不足的问题。最后,采用改进麻雀算法(CDE-SSA)对最小二乘支持向量机(LSSVM)进行参数寻优。实验结果证明,方法在NOX浓度预测的精度和稳定性上均表现出了良好的性能。

基于逐次变分模态分解的飞轮-火电一次调频控制策略

随着新型电力系统的大力建设与推广,火电机组面临的调频压力增大,提出一种逐次变分模态分解的飞轮-火电一次调频控制策略。首先,以飞轮储能和火电机组为研究对象,建立考虑新能源占比的飞轮-火电一次调频模型;其次,将一次调频功率指令利用逐次变分模态方法分解,由火电机组响应分解后的低频功率指令,同时设计飞轮储能下垂优化控制方法,实现飞轮储能与火电机组响应频率变化的协同控制;最后在不同工况下仿真验证,结果表明所提策略可有效避免火电机组一次调频时的频繁出力,减小火电机组响应频率变化时的调控要求,同时可最大限度地利用飞轮储能调频容量并保证飞轮储能调频期间的运行安全,进一步提升了系统的频率响应能力。

基于火电灵活性改造的可再生能源消纳系统成本优化

随着风电等可再生能源的大规模发展,带来了消纳难等新挑战,通过火电灵活性改造可以增强电力系统灵活调节能力、提升可再生能源消纳空间,同时需要考虑火电灵活性改造的经济性和对可再生能源消纳的影响。因此,综合考虑火电机组常规运行成本及灵活性改造后增加的各项成本,结合碳排放成本和弃风成本,建立以总成本最小为目标的火电灵活性改造前后优化调度模型,采用对比差值法计算基于火电灵活性改造的可再生能源消纳系统成本。通过算例,将所建模型应用于对比改造前后、不同碳排放强度、是否考虑弃风等不同方案下的机组运行状况及消纳系统成本大小,并拟合得到可再生能源渗透率和消纳系统成本的关系曲线,验证了模型的有效性。

双碳目标下高温气冷堆替代中小型火电的思考

碳达峰碳中和是我国一项重要的国家战略决策,“双碳”目标的提出给能源行业带来了深刻的变革,我国能源结构将进一步优化,电力行业必须实现低碳转型,新能源取代火电已成为必然。本文分析了新形势下火电企业面临的巨大挑战、发电规模受到限制、经营成本不断上升,尤其是中小型火电机组,面临着淘汰和关停的局面,而高温气冷堆具有固有安全性、发电效率高、用途广泛的显著特点,使其替代中小型火电成为可能。本文通过厂址适应性、技术可行性、经济可行性三方面,分析了高温气冷堆替代中小型火电的可行性,并从相关法律法规适用性、内陆厂址所带来的问题、开展公众沟通等方面提出建议。

新型电力系统下燃煤火电机组一次调频面临的挑战与展望

频率稳定是未来新型电力系统运行的最关键要求之一。中国的能源禀赋决定了燃煤火电机组是最核心、最可靠的一次调频资源。然而,燃煤火电已开始出现一次调频能力不足的趋势。为了满足当前和长远发展的需要,文中综述了燃煤火电在一次调频领域所面临的挑战、研究现状和关键科学问题。首先,总结了新型电力系统发展背景下火电一次调频的4个重要趋势,分析了下一步调频在电网和火电厂运行中的不足,提炼出提高一次调频能力和快速准确模拟调频的关键挑战。其次,从电网和火电厂运行的双向视角,综述了调频能力提升和调频动态仿真的研究现状和存在的问题。最后,结合上述挑战和瓶颈,展望了未来新型电力系统火电一次调频的关键技术问题。

应用集成极限学习机的电站SCR脱硝系统建模与分析

针对火电机组普遍采用的选择性催化还原(selective catalytic reduction,SCR)脱硝反应容易受到环境因素影响,且具有非线性、大迟延、强扰动特点,难以建立准确反应模型的问题,提出一种基于集成极限学习机的SCR脱硝系统建模方法。首先,选择4种具有不同激活函数的极限学习机和核极限学习机作为基学习器,分别建立SCR脱硝系统模型;然后,利用偏最小二乘算法将各基学习器的结果进行集成;最后,采用某1000 MW超超临界机组实际运行数据与所提建模方法相结合建立SCR脱硝系统模型。实验结果验证模型的有效性;与其他方法所建模型对比,结果表明基于集成极限学习机的SCR脱硝系统模型具有更好的模型泛化能力。