A Synthesis of Electronically Controllable Current-Mode PI, PD and PID Controllers Employing CCCDBAs

This paper presents a synthesis of current-mode PI, PD and PID controllers employing current controlled current differential buffer amplifiers (CCCDBAs). The features of these controllers are that: the output parameters can be electronically/independently controlled by adjusting corresponding bias currents in the proportional, integral, and deviation controllers;circuit description of the PID controller is simply formulated, it consists of four CCCDBAs cooperating with two grounded capacitors, and PI and PD controllers are composed of three CCCCDBAs and a grounded capacitor. Without any external resistor, the proposed circuits are very suitable to develop into integrated circuit architecture. The given results from the PSpice simulation agree well with the theoretical anticipation. The approximate power consumption in a closed loop control system consisting of the PI, PD and PID controller with low-pass filter passive plant are 4.03 mW, 4.85 mW and 5.71 mW, respectively, at ±1.5 V power supply voltages.

Inductor Current Sampled Feedback Control of Chaos in Current-Mode Boost Converter

A chaos control strategy for chaotic current-mode boost converter is presented by using inductor current sampled feedback control technique.The quantitative analysis of control mechanism is performed by establishing a discrete alterative map of the controlled system.The stability criterion,feedback gain,and corresponding critical duty ratio are obtained from the eigenvalue of the map.The simulation results verify the t heoretical analysis results of the control strategy.

Design and Application of Wind Power Peak Control Technology

Wind power control technology is an important part of intelligent control in wind farms. By the automatic calculation and implementation of control strategy, problems such as imprecise of manual control scheduling, slow adjust rate, heavy workload, etc. have been solved. It can improve the capacity of wind power grid, and it also has the important meaning to the safe and stable operation of power grid. This paper introduces wind power control system from certain aspects such as control mode, control principle, and so on.

Effect of Flood Peak Discharge Control by a Small Reservoir in an Urbanized Area—Case Study in the Kurabe River Basin, Japan

Recently severe damage of flooding by urbanization was frequently occurred. To prevent this damage, small reservoir was constructed in the urbanized residential area. This paper describes an effect of flood peak discharge control by a small reservoir (control reservoir) caused by rapidly developed urbanization. Although work for this purpose was conducted, research on the effects of the control reservoir was not conducted until now. This research, conducted by simulation, was a case study in the Kurabe River Basin in the Tedori River Alluvial Fan Area, Japan, based on the precise investigation of the reservoir in the actual field. The study was conducted to determine not only the actual control reservoir capacity for the newly developed residential area but also the ideal capacity for all present residential areas and the largest capacity allowable for a maximum rainfall event that recently occurred. The control reservoir effects between individual blocks and the entire basin area were compared by dividing the test basin into 15 blocks (sub-basins). The results showed that the effects on the capacity per unit area of the residential area in blocks have close relationship with the decreasing ratio of peak discharge in blocks. Consequently, the effects of control reservoir capacity and the limitation were clarified. In the future, control reservoirs should be constructed for all of the already developed residential areas, for example, by utilizing underground car parking lot. The results of this research can contribute to the design of the control reservoir for protection against flooding damage in urbanized areas.

Optimal reduction and equilibrium carbon allowance price for the thermal power industry under China’s peak carbon emissions target

As the largest source of carbon emissions in China,the thermal power industry is the only emission-controlled industry in the first national carbon market compliance cycle.Its conversion to clean-energy generation technologies is also an important means of reducing CO_(2)emissions and achieving the carbon peak and carbon neutral commitments.This study used fractional Brownian motion to describe the energy-switching cost and constructed a stochastic optimization model on carbon allowance(CA)trading volume and emission-reduction strategy during compliance period with the Hurst exponent and volatility coefficient in the model estimated.We defined the optimal compliance cost of thermal power enterprises as the form of the unique solution of the Hamilton–Jacobi–Bellman equation by combining the dynamic optimization principle and the fractional It?’s formula.In this manner,we obtained the models for optimal emission reduction and equilibrium CA price.Our numerical analysis revealed that,within a compliance period of 2021–2030,the optimal reductions and desired equilibrium prices of CAs changed concurrently,with an increasing trend annually in different peak-year scenarios.Furthermore,sensitivity analysis revealed that the energy price indirectly affected the equilibrium CA price by influencing the Hurst exponent,the depreciation rate positively impacted the CA price,and increasing the initial CA reduced the optimal reduction and the CA price.Our findings can be used to develop optimal emission-reduction strategies for thermal power enterprises and carbon pricing in the carbon market.

The Peak Current Control of Permanent Magnet Brushless DC Machine with Asymmetric Dual-Three Phases

The asymmetric dual-three phase BLDC motor has two sets of stator windings,in which the back EMF coefficients are different.This paper takes advantage of the asymmetric dual-three phase BLDC motor’s structural features and proposes a new method for the accelerated problem of the BLDC motor operating in the high speed and the constant electromagnetic power.The dual phase windings of the BLDC motor are integrated into the circuit in the starting stage.When the motor’s back EMF value is equal to the terminal voltage value,switch off a set of RST three phase windingswhose back EMF coefficient is bigger and make the other set of stator windingUVWwith smaller back EMF coefficient continue to operate under the rated power.As the motor rotor speed continues to increase,the electromagnetic torque remains unchanged.By using the peak current control strategy,we can deduce that the phase current of the UVW three-phase winding is twice the RSTthree-phase windingwhen the asymmetric dual-three phase BLDC motor operates at high speed and constant power.

基于TQM理论的门诊号源削峰填谷质量控制实践

城区内大型综合医院位置的独特性决定了其空间制约与医疗拓展之间的矛盾成为管理的瓶颈问题。通过全面质量管理理论和持续改进工作模式,对某大型综合医院的出诊安排及出诊单元进行削峰填谷,使专家出诊过于集中在某个工作日上午的情况得到了明显改善,缓解了医院周边公共交通的拥堵;同时通过对门诊质量的内涵建设,切实提升了患者就医获得感。

计及需求响应的光热电站参与深度调峰的分层优化调度策略

从源、荷两侧挖掘系统调峰潜力,建立计及需求响应的光热电站参与深度调峰的分层优化调度模型。上层从负荷侧出发,提出一种基于负荷分类的价格需求响应模型,可有效缓解系统调峰压力;中层从电源侧出发,利用光热电站灵活的调节特性在深度调峰时段协调火电机组参与辅助调峰,构建以运行总成本最小为目标函数的日前调度模型;下层提出一种基于模型预测控制的日内动态调整模型,在滚动优化的同时,通过状态反馈环节实时调整光热电站储热装置充放热修正日前调度计划。仿真结果表明,所提调度策略在降低系统调峰成本的同时能有效抑制风光以及负荷的短时功率波动,在保证系统安全稳定运行的前提下提升风光消纳率。

机器学习驱动锅炉燃烧优化技术的现状与展望

伴随可再生能源发电装机容量快速增加,深度调峰过程中负荷多变、燃烧失稳等不稳定工况对火电机组的燃烧优化控制提出了更高要求,快速发展的人工智能技术与深度学习算法为锅炉参数预测建模及优化提供了重要手段。在机器学习算法方面,总结了特征筛选与建模算法的研究现状,提出了传统统计学方法与线性降维方法的科学解释性较差且不能很好地辨识高维数据,结合深度学习算法的特征筛选方法在处理复杂的火电机组数据时优势更明显;对比了多种神经网络在NO_(x)排放浓度建模中的优缺点,其中长短期记忆神经网络与卷积神经网络在处理时序数据时效果更好、集成模型通过组合不同学习器的优势可提高整个模型的泛化能力和鲁棒性。在预测模型的应用方面,通过对SCR脱硝系统建立预测模型可以方便运行人员模拟并修正可调参数,同时作为软测量手段监测燃烧系统运行状态;引入NO_(x)排放浓度预测模型的前馈控制和模型预测控制等先进控制手段可有效改善火电机组传统PID控制效果较差的问题;在多目标优化中NO_(x)脱除效率通常与锅炉效率或脱硝成本共同作为优化目标,以期实现经济效益与社会效益的和谐统一。

激波/湍流边界层干扰中的自适应控制技术

从激波/湍流边界层干扰机理以及流动控制的迫切需求入手,从自适应涡流发生器、自适应鼓包、自适应微射流以及自适应次流循环四个方面对激波/湍流边界层干扰中的自适应控制技术研究进展进行了总结。分析认为,结合AI技术发展自适应流动控制技术,加速控制方式智能化,可作为新一代高超声速飞行器宽速域飞行的重要技术手段。具体来说,就是通过调节外加激励对高超声速飞行器不同区域实现局部流动加/减速、气动热防护、气动控制等功能,根据流场参数建立控制反馈回路,自适应调整局部流场结构,以满足工程实际需求。

“双碳”目标下“减污降碳协同增效”在生态环境法典中的立法表达

我国生态环境法典编纂既要实现环境立法的体系化,也要吸纳生态文明体制机制改革制度成果,为我国的“双碳”战略提供法治保障。实现“双碳”目标,“降碳”是战略方向,“减污降碳协同增效”是重点路径。“双碳”法治建设应秉持整体论法治理念、重视调整对象的关联性、彰显治理制度的协同性。现行减污降碳法律规范体系未确立减污降碳协同治理的整体性法治理念,未将温室气体排放作为调整对象,减污降碳协同治理制度阙如,亟待予以针对性制度创新,同时也要回应减污降碳协同效应的多层次复合关系。生态环境法典污染控制编应从更新立法理念、完善污染控制一般制度和大气污染控制专章制度等方面实现减污降碳协同治理的制度创新。

稻田控制排水对高邮灌区河道洪水过程的影响

以高邮灌区为例,采用水文-水动力模型,研究稻田控制排水措施对河道洪峰流量、水位和洪水过程的影响。结果表明,雨前通过控制灌溉适当降低田间水位可减轻稻田出流峰值,随着稻田控制水位的增加,稻田径流峰值逐渐降低。通过稻田控制排水,可降低田间出口峰值流量,改变灌区河道洪水过程,降低河道洪峰流量和水位,减轻灌区内部以及附近河道的防洪压力。

基于改进布谷鸟搜索算法的光伏最大功率点跟踪策略

实际工程中,光伏阵列在随机变化的环境中会出现局部遮光的情况,从而导致光伏阵列的功率-电压特性曲线会呈现多峰值状态,传统的最大功率点跟踪(maximum power point tracking, MPPT)算法易陷入局部最优解,追踪速度和精准度无法得到满足。针对这一问题,提出一种基于布谷鸟搜索算法(cuckoo search algorithm, CS)和电导增量法(conductivity increment method, CI)结合的光伏MPPT算法,在算法前期利用布谷鸟搜索算法将大步长和小步长交替使用使得全局搜索能力增强,找到全局最大功率点所处区域附近;在后期,采用步长小、控制精度高的CI进行局部寻优,快速准确地锁定到最大功率点。在MATLAB/Simulink中搭建仿真模型,并与原始布谷鸟搜索算法和粒子群优化(particle swam optimization, PSO)算法进行比较。仿真结果表明,将CS与CI结合的算法使得收敛速度更快,精度更高,稳定状态时功率曲线的波动更小。

针对温控负载变化的虚拟电厂控制策略研究

温控负载是一种变化剧烈、波动频繁、高峰负荷比例较高的负载,对电网的安全产生了极大的影响。为了应对这一问题,系统的输出功率往往会超过90%负荷最大值的调峰限制。针对虚拟电厂(VPP)系统内的超限过程进行了研究,并提出了2种控制策略,以降低超限总电量或者利用超限电量的同时获取收益。在验证策略的控制效果时,选取了2种由温控负载引起的功率需求的典型变化。研究结果表明,温控负载引起的功率需求峰值的变化对策略具有重要影响。在安全模式下,超限比例与峰值的增加呈反比,而与平均功率的增加呈正比;在收益模式下,峰值变化会影响储能放电过程,平均功率变化则会影响储能充电过程。随着功率需求的增加,收益逐渐减小,收益范围为3.62万~3.25万元。

深度调峰工况下超临界机组的干湿态转换策略研究

为寻求深度调峰工况下合适的干湿态转换方式,在2台超临界机组上,采用2种不同的干湿态转换策略,对协调控制方式下的干湿态转换及其对系统稳定性的影响进行了研究。结果表明:2种策略均能够实现协调方式下的干湿态转换,可以通过转态进行进一步的深调工作;通过煤、水协同控制或给水流量控制均可实现干湿态转换,但水煤比变化情况不同;干转湿过程中,受到2种策略的影响,系统稳定性(主汽温度、主汽压力)区别明显;在湿转干过程中,2种策略下的系统都表现出良好的稳定性。

高风电渗透率下液流电池储能系统调峰优化控制策略

【目的】在“双碳”目标背景下,解决高风电渗透率系统建设带来的调峰安全性和经济性问题。【方法】采用电池储能系统削峰填谷的解决方案,提出了一种兼顾技术及经济性的锌溴液流电池(zinc-bromine flow battery,ZBB)储能的调峰优化控制方法。根据实际电池装置,对ZBB储能进行结构解析及数学模型构建。考虑调峰技术性效果,以调峰后的负荷曲线标准差最小为目标函数,提出一种考虑调峰效果的储能双向寻优控制策略。在此基础上,依据电网分时(time of use,TOU)电价政策,以技术性及经济性最优为目标函数,提出一种基于TOU电价机制的储能调峰经济模型,得出储能优化功率时序结果。最后,以东北某地区负荷及风电数据为例,对比验证所提策略的有效性。【结果】所提策略相较于原负荷,在日均负荷峰谷差、峰谷差率指标上分别降低了35.973%和34.205%,在调峰经济性优化方面提高了5.582%,且合并缓解了电网弃风消纳问题。【结论】所提策略在达到一定调峰效果的同时,在其全寿命周期内仍保持较好的调峰经济性。

基于周期性最大功率点检测的风电机组功率备用控制方法

风电机组通常运行于最大功率输出模式,无法为受扰电网提供紧急功率支撑。稳态时预留部分出力可提高风电机组主动电网支撑能力,为此提出一种基于周期性最大功率点(MPP)检测的风电机组功率备用控制(PRC)方法。通过周期性执行最大功率点跟踪程序检测风电机组实时MPP,一旦检测到MPP即可确定PRC模式参考值并切换为直接功率控制。设置伪单调转速-机械功率曲线使风电机组稳定运行在超速功率备用点,并通过储能装置平抑MPP检测产生的峰值功率波动。仿真结果表明提出的控制方法在定风速和变风速情况下均可以准确控制检测风电机组MPP并实现PRC,并且使得风电机组一次调频效果优于传统PRC。

不同暴雨条件下扇形和羽形流域的洪水规律

为了探讨降雨过程时空分布不均匀性对河道径流的影响,以沂河、沭河流域为例,利用瞬时单位线法和马斯京根法计算重现期为10、 20、 50 a的3 d特征暴雨和2019年台风“利奇马”暴雨在2个流域中的洪水流量,得出各防洪控制站在不同暴雨条件下的洪水规律。结果表明:扇形流域内洪水汇流较集中,容易发生洪灾;羽形流域内各支流洪水交错汇入干流,近水先去,远水后去,洪水较缓和,沂河的防汛压力大于沭河的防汛压力;在相同降雨量条件下,沂沭河流域内临沂站在从北向南的降雨过程中更易形成大洪峰,斜午站、石拉渊站和重沟站在从南向北的降雨过程中更易形成大洪峰;莒县站位于沭河上游,控制流域包含多个支流和3个水库,流域形状为属于羽形流域的沭河流域中的扇形流域,具有洪水汇流集中的特点,沭河莒县站的防汛压力大于沭河其他防洪控制站的防汛压力,而且当沭河流域出现大范围同步降雨过程时,莒县站更易形成大洪峰。

数据中心储能型不间断电源系统及其控制技术

随着互联网数据中心IDC的快速发展,为其配备的不间断电源系统UPS规模越来越大,由于UPS的电池系统只有在少数的停电时段应用,造成了大量的资源闲置。在保证备电的前提下,充分挖掘UPS中电池系统的储能功能,是一种经济高效的储能形式。在常规UPS的基础上,提出了储能型不间断电源系统(energy storage type of UPS,EUPS)的实现架构,EUPS多种“备电+储能”应用功能的控制策略,以及EUPS参与电网多场景调节的协调控制策略。最后,基于建成的EUPS示范系统,验证了所提的EUPS系统架构和控制策略的有效性。

基于遗传算法的高峰时段车站协同限流方法

车站限流是缓解城市轨道交通高峰客流拥挤的有效应对措施。然而,目前实际应用的限流措施缺乏对同线路相邻车站的协同配合的考虑,限流效果有待进一步提升。综合考虑乘客、列车、车站三者的交互关系,依据列车在车站的发车时间间隔,对高峰时段的列车时刻表进行时间离散化,将离散化的时段作为基本研究时段,提取对应的车站乘客到达量。从供需双方的角度出发,以乘客总延误时间最小化和旅客周转量最大化为优化目标,在考虑列车运输能力、客流控制强度、车站服务水平的同时,引入列车剩余运输能力作为约束条件,平衡不同车站的客流需求,构建车站协同限流优化模型。针对多目标函数求解的复杂性,设计1种嵌入式遗传算法对模型进行求解,平衡多目标函数之间最优解的冲突。以南京地铁三号线高峰时段为例,与不采取协同限流的情景(先到先服务)进行对比分析。结果表明:在乘客总周转量提升1%的情况下,乘客延误人数下降了2.3%,乘客总延误时间降低了4.3%,拥挤车站的延误人数显著降低,延误人数的时空分布更加平衡。为了验证算法的有效性和模型的稳定性,将遗传算法与Gurobi求解器进行算法对比,并对关键参数列车满载率进行灵敏度分析,提出的遗传算法更能兼顾双优化目标,有利于缓解高峰时段大客流延误。