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Model Reference Adaptive Controller for Simultaneous Voltage and Frequency Restoration of Autonomous AC Microgrids
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作者 Farahnaz Ahmadi Yazdan Batmani Hassan Bevrani 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2024年第4期1194-1202,共9页
In an autonomous droop-based microgrid,the system voltage and frequency(VaF)are subject to deviations as load changes.Despite the existence of various control methods aimed at correcting system frequency deviations at... In an autonomous droop-based microgrid,the system voltage and frequency(VaF)are subject to deviations as load changes.Despite the existence of various control methods aimed at correcting system frequency deviations at the secondary control level without any communication network,the challenges associated with these methods and their abilities to simul-taneously restore microgrid VaF have not been fully investigated.In this paper,a multi-input multi-output(MIMO)model reference adaptive controller(MRAC)is proposed to achieve VaF restoration while accurate power sharing among distributed generators(DGs)is maintained.The proposed MRAC,without any communication network,is designed based on two methods:droop-based and inertia-based methods.For the microgrid,the suggested design procedure is started by defining a model reference in which the control objectives,such as the desired settling time,the maximum tolerable overshoot,and steady-state error,are considered.Then,a feedback-feedforward con-troller is established,of which the gains are adaptively tuned by some rules derived from the Lyapunov stability theory.Through some simulations in MATLAB/SimPowerSystem Tool-box,the proposed MRAC demonstrates satisfactory perfor-mance. 展开更多
关键词 AC microgid communication-free secondary control droop-based method inertia-based method model reference adaptive controller(MRAC) simultaneous voltage and frequency restoration
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改进的云自适应粒子群算法 被引量:5
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作者 张锦华 《计算机工程与应用》 CSCD 2012年第5期29-31,共3页
为了提高粒子群算法的寻优速度和精度,提出一种改进的云自适应粒子群算法(MCAPSO)。算法中根据粒子适应度值把种群分为三个子群,分别采用不同的惯性权重生成策略和进化策略,普通子群粒子采用云自适应惯性权重,有效地调整了算法的全局与... 为了提高粒子群算法的寻优速度和精度,提出一种改进的云自适应粒子群算法(MCAPSO)。算法中根据粒子适应度值把种群分为三个子群,分别采用不同的惯性权重生成策略和进化策略,普通子群粒子采用云自适应惯性权重,有效地调整了算法的全局与局部搜索能力。选取了五个基准函数进行测试,与其他PSO算法作了比较。仿真结果表明该方法是有效的。 展开更多
关键词 粒子群算法 云自适应惯性权重 进化策略
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一种云自适应粒子群优化的PID控制器设计与应用 被引量:1
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作者 应明峰 鞠全勇 高峰 《金陵科技学院学报》 2012年第2期41-47,共7页
针对PID控制器应用于实际的自动电压调节器(AVR)系统,为了有效地寻找AVR系统的最佳PID控制器参数,提出一种基于改进的云自适应粒子群算法的PID参数优化策略。通过建立粒子群优化的PID控制器参数模型,在控制过程中将PID参数(比例、积分... 针对PID控制器应用于实际的自动电压调节器(AVR)系统,为了有效地寻找AVR系统的最佳PID控制器参数,提出一种基于改进的云自适应粒子群算法的PID参数优化策略。通过建立粒子群优化的PID控制器参数模型,在控制过程中将PID参数(比例、积分、微分)作为粒子群中的粒子,采用控制误差绝对值时间积分函数作为优化目标,在控制过程中动态调整PID的三个控制参数,从而进行PID控制参数的实时优化。仿真结果表明,该PID控制器可以获得较好的控制性能指标,进而改善AVR系统的瞬时响应特性,具有一定的实用价值。 展开更多
关键词 粒子群 云自适应惯性权重 比例积分微分控制器 自动电压调节器
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