Design of a Proportional-Integral-Derivative Controller for an Automatic Generation Control of Multi-area Power Thermal Systems Using Firefly Algorithm

Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.

A Novel Cascaded PID Controller for Automatic Generation Control Analysis With Renewable Sources

Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control(AGC) with diverse renewable sources and a modified-cascaded controller are presented in the paper.Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution(hITLBO-DE) algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative(PID), integral double derivative(IDD) and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change.The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5% of the connected load and robustness analysis is shown by modifying essential factors simultaneously by± 30%. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.

Multi-timescale robust dispatching for coordinated automatic generation control and energy storage

The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment such as energy storage.Current dispatch decision-making methods often ignore the intermittent effects of renewable energy.This paper proposes a two-stage robust optimization model in which energy storage is used to compensate for the intermittency of renewable energy for the dispatch of AGC units.This model exploits the rapid adjustment capability of energy storage to compensate for the slow response speed of AGC units,improve the adjustment potential,and respond to the problems of intermittent power generation from renewable energy.A column and constraint generation algorithm is used to solve the model.In an example analysis,the proposed model was more robust than a model that did not consider energy storage at eliminating the effects of intermittency while offering clear improvements in economy and efficiency.

MAS Based Distributed Automatic Generation Control for Cyber-Physical Microgrid System

The microgrid is a typical cyber-physical microgrid system (CPMS). The physical unconventional distributed generators (DGs) are intermittent and inverter-interfaced which makes them very different to control. The cyber components, such as the embedded computer and communication network, are equipped with DGs, to process and transmit the necessary information for the controllers. In order to ensure system-wide observability, controllability and stabilization for the microgrid, the cyber and physical component need to be integrated. For the physical component of CPMS, the droop-control method is popular as it can be applied in both modes of operation to improve the grid transient performance. Traditional droop control methods have the drawback of the inherent trade-off between power sharing and voltage and frequency regulation. In this paper, the global information (such as the average voltage and the output active power of the microgrid and so on) are acquired distributedly based on multi-agent system (MAS). Based on the global information from cyber components of CPMS, automatic generation control (AGC) and automatic voltage control (AVC) are proposed to deal with the drawback of traditional droop control. Simulation studies in PSCAD demonstrate the effectiveness of the proposed control methods. © 2014 Chinese Association of Automation.

A hybrid stochastic fractal search and pattern search technique based cascade PI-PD controller for automatic generation control of multi-source power systems in presence of plug in electric vehicles

A hybrid Stochastic Fractal Search plus Pattern Search （hSFS-PS） based cascade PI-PD controller is suggested in this paper for Automatic Generation Control （AGC） of thermal, hydro and gas power unit based power systems in presence of Plug in Electric Vehicles （PEV）. Firstly, a single area multi-source power system consisting of thermal hydro and gas power plants is considered and parameters of Integral （I） controller is optimized by Stochastic FractaI Search （SFS） algorithm. The superiority of SFS algorithm over some recently proposed approaches such as optimal control, differential evolution and teaching learning based optimization techniques is demonstrated by comparing simulation results for the identical power system. To improve the system performance further, Pattern Search （PS） is subsequently employed. The study is further extended for different controllers like PI, PID, and cascaded PI-PD controller and the superiority of cascade PI-PD controller over conventional controllers is demonstrated. Then, cascade PI- PD controller parameters of AGC searched using the proposed hSFS-PS algorithm in presence of plug in electric vehicles. The study is also extended to an interconnected power system. It is seen from the comparative analysis that hSFS-PS tuned PI-PD controller in single and multi-area with multi sources improves the system frequency stability in complicated situations. Lastly, a three area interconnected system with PEVs with dissimilar cascade PI-PD controller in each area is considered and proposed hSFS- PS algorithm is used to tune the controller parameters in presence of nonlinearities like rate constraint of units, dead zone of governor and communication delay.

面向多源协调互济的AGC指令两阶段分配方法

高比例新能源电力系统的惯量支撑能力弱、随机波动性强,电网频率质量难以得到保障。引入不同品类调频资源共同参与自动发电控制(automatic generation control,AGC)是应对上述问题的有效手段,但这也要求AGC指令分配能够适配不同品类资源的差异化调节特性。对此,提出面向多源协调互济的AGC指令两阶段分配方法。首先,将不同资源分别安排至与自身调节特性相匹配的超前分配阶段和实时分配阶段。其次,在实时分配阶段提出基于资源调节优先级的AGC指令分配策略,根据不同品类资源的调节特性以及电网频率状况对资源调节优先级进行设定,以互补利用各类资源的调节优势。然后,在超前分配阶段,建立优化分配模型以实现不同品类资源的协调最优利用。同时,嵌入与资源剩余调节裕度相关的惩罚项,以保障资源持续调节能力。最后,基于电网实际数据的算例仿真验证了所提方法的有效性。

Automatic Generation Control of Multigeneration Power System

Load frequency Control (LFC) is used for many years as part of Automatic Generation Control (AGC) in power system around the world. In a mixed power system, it is usual to find an area regulated by hydro generation interconnected to another area regulated by thermal generation or in combination of both. In the following study, performance of AGC for Thermal, Hydro and Thermal turbine based power system is examined, including how frequency bias setting influences AGC response and inadvertent interchange. Control performance analysis of three area interconnected systems is simulated and studied through Matlab Simulink software. Integral square error and Integral time absolute error has been used as performance criterion. It is shown that integral time absolute error (ITAE) as performance index leads to faster optimization of controller gain.

基于AGC系统的光伏电站一次调频控制系统设计

在光伏电站的发电过程中,由于太阳光的间歇性和不可预测性,如何保障电网频率的稳定性是一个重要问题。文章详细探讨了基于自动发电控制(Automatic Generation Control,AGC)系统的光伏电站一次调频控制系统的设计方法。首先概述了AGC系统的工作原理和组成,其次提出一个针对光伏电站特定需求的一次调频控制系统设计方案,包括系统架构设计、数据收集与分析、控制算法与模型的开发以及系统稳定性与效率的评估,最后通过系统测试验证所提出设计的有效性与实用性。

AGC调频指标提升关键技术研究

通过重新优化汽机主控、锅炉主控逻辑及自主研发的AGC信号智能自动校正控制装置,消除AGC的调节量、被调量与调度能量管理系统信号之间的误差,实时对其进行动态校正,提高调节速率、调节精度、响应时间等指标,提升AGC综合性能指标。同时在电力辅助服务市场上,通过调节精度的提升,可有效增加机组的AGC调节范围,争取到更多的补偿收益。

新能源电力系统AGC调频容量监测设计

文章提出了用于新能源电力系统自动发电控制(Automatic Generation Control,AGC)的实时调频容量评估方法,以满足控制区的自动发电控制调频能力分析需求。根据AGC调频容量考核标准,整理了影响调频容量的主要因素,并运用历史数据预测调频标准差。以贵州黔源电力镇宁某水电站和光伏站作为例,评估AGC调频容量。实验结果证实,应用所提方法能有效地分配调频容量。

Automatic Generation Control in a Distributed Power Grid Based on Multi-step Reinforcement Learning

The increasing use of renewable energy in the power system results in strong stochastic disturbances and degrades the control performance of the distributed power grids.In this paper,a novel multi-agent collaborative reinforcement learning algorithm is proposed with automatic optimization,namely,Dyna-DQL,to quickly achieve an optimal coordination solution for the multi-area distributed power grids.The proposed Dyna framework is combined with double Q-learning to collect and store the environmental samples.This can iteratively update the agents through buffer replay and real-time data.Thus the environmental data can be fully used to enhance the learning speed of the agents.This mitigates the negative impact of heavy stochastic disturbances caused by the integration of renewable energy on the control performance.Simulations are conducted on two different models to validate the effectiveness of the proposed algorithm.The results demonstrate that the proposed Dyna-DQL algorithm exhibits superior stability and robustness compared to other reinforcement learning algorithms.

Improved Smith prediction monitoring AGC system based on feedback-assisted iterative learning control

The performance of Smith prediction monitoring automatic gauge control(AGC) system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning control strategy, which learned unknown modeling error by using previous control information repeatedly, was introduced into Smith prediction monitoring AGC system. Firstly, conventional Smith predictor and improved Smith predictor with PI-P controller were analyzed. Secondly, on the basis of establishing of feedback-assisted iterative learning control strategy for improved Smith predictor, process control signal update law and control error were deduced, then convergence condition of this strategy was put forward and proved. Finally, after modeling the automatic position control system, the PI-P Smith prediction monitoring AGC system with feedback-assisted iterative learning control was researched through simulation. Simulation results indicate that this system remains stable during model mismatching. The robustness and response of monitoring AGC is improved by development of feedback-assisted iterative learning control strategy for PI-P Smith predictor.

精轧AGC系统仿真实验教学平台设计与开发

在新工科背景下为了培养学生实践创新能力,设计开发了以钢铁企业热连轧精轧自动厚度控制系统(Automatic Gauge Control, AGC)为对象的虚拟仿真实验教学平台。该实验教学平台从本科自动化专业多门实践类课程的教学需求出发,依次设计了精轧系统轧制规程仿真模块和AGC控制系统仿真模块,并细化为6个具体的实验项目,较好地模拟了多机架带钢热连轧精轧的生产控制过程。实践表明,该实验教学平台有效地提升了学生工程实践能力和综合创新能力,为高校新工科卓越人才培养提供了良好的支撑。

基于AGC线性化的谐振式加速度计相位噪声分析

谐振式加速度计系统运行过程中会引入噪声,导致输出信号的相位发生偏移,从而影响测频精度。同时,由于自动增益控制(AGC)回路非线性的影响,噪声的传递无法直接利用传递函数分析。为了减小噪声的影响,根据谐振式加速度计的工作原理与噪声理论,对谐振回路中引入的各种噪声进行了传递路径的线性化分析与数学推导,给出了相位噪声表达式。MATLAB曲线,Simulink噪声模型与谐振式加速度计高速采样的相位噪声一致,验证了相位噪声表达式与噪声模型的正确性。

区域新能源电力系统AGC调频容量实时评估方法

针对高比例可再生能源接入下电力系统惯量水平持续降低、弱频率调节能力会危及电网安全运行等问题,提出一种区域新能源电力系统自动发电控制AGC(automatic generation control)调频容量实时评估方法,以确定控制区的AGC调频能力分析需求。首先,依据AGC调频容量考核标准,梳理调频容量的主要影响因素,并获取调频容量、调频标准差与调频表现间的联系。其次,综合应用传统机组、负荷、新能源、联络线历史数据,基于极限学习机ELM(extreme learning machine)模型预测调频标准差,利用调频表现达标概率分布确定区域电力系统的调频容量。最后,以河北某电网为例进行AGC调频容量的评估,验证了所提方法AGC调频容量更小,调频表现更优,具有更好的安全性和经济性。

一种用于毫米波探测系统的变步长LMS-AGC方案

在毫米波探测系统中,自动增益控制(AGC)是信号处理系统的关键技术之一,其作用是应对大动态范围的中频信号接收。本文阐述了一种数字自动增益控制(DAGC)的实现方案,通过对中频信号的数字采样进行处理,采用基于平均功率参量的变步长LMS-AGC自适应算法,将自适应滤波器的变步长思想应用到AGC方案中,并对其步长算法进行优化。通过对比普通功率检测自动增益控制和固定步长LMS-AGC方案,本文提出的变步长LMS-AGC方案具有更快的收敛速度和更小的稳态误差。

基于AGC调频分区控制的光储联合系统参与市场投标策略

为充分发挥光储联合系统提供调频辅助服务的能力、提高联合系统的收益,提出了一种基于自动发电控制(automaticgenerationcontrol,AGC)调频分区控制的光储联合系统参与市场的投标策略。首先,考虑了光储系统运行特性和电网频率波动不确定性,提出了光储系统参与能量-调频市场的日前-实时两阶段交易方法。其次,提出了光储系统参与AGC的实时调频控制方法,根据区域控制偏差所处控制域动态分配光储系统所承担的调节量。然后,构建了光储联合系统参与电力市场的多时间尺度投标优化模型,其中日前市场考虑了潜在的实时能量偏差,实时市场利用滚动优化方法反馈校正多种不确定因素。最后,通过算例分析验证了该策略在充分考虑电力系统频率安全稳定的前提下,使利润增加了14.9%,显著提高了光储联合系统的收益。

CMOS Automatic Gain Control Circuit with DC Offset Cancellation for FM/cw Ladar

This paper presented an automatic gain control （AGC） circuit suitable for FM/cw ladar. The proposed architecture was based on two-stage variable gain amplifier （VGA） chain with a novel DC offset canceller circuit, which contained an improved Gilbert cell and a Gm-C feedback loop. To keep the VGA with a linearity in dB characteristic, an improved exponential gain control circuit was introduced. The AGC was implemented in 0.18 gm standard CMOS process. Simulation and measurement results verified that its gain ranged from -20 dB to 30 dB, and band- width ranged from 100 kHz to 10 MHz. Its power consumption was 19.8 mW under a voltage supply of 3.3 V.

机组AGC及深度调峰控制性能优化

江苏徐矿综合利用发电有限公司2台300 MW亚临界燃煤发电机组,自2010年投产以来经历多次检修,机组主辅机性能产生变化,且由于机组增加对外供热,原设计控制方式无法协调锅炉能量—汽机需求—电气功率三者的平衡,加剧了AGC、一次调频调节品质的恶化,且无法适应当前电网深调工况需求。通过对机组自动控制系统进行相应逻辑优化、参数调整,在保证各主辅机安全运行的前提下,有效提高机组“两个细则”性能指标,同时实现30%~100%深度调峰下机组稳定经济运行。

Research on Wind Farm Participation in Power Grid AGC Control

Since wind power has the features of being intermittent and unpredictable, and usually needs transmission over long distances, grid integration of large-scale wind power will exert signif icant influence on power grid planning and construction, and will make a heavy impact on the safe and reliable operation of power systems. To deal with the diff iculties of large scale wind power dispatch, this paper presents a new automatic generation control (AGC) scheme that involves the participation of wind farms. The scheme is based on ultra-short-term wind power forecast. The author establishes a generation output distribution optimization mode for the power system with wind farms and verif ies the feasibility of the scheme by an example.