Maximum Power Point Tracking (MPPT) algorithms are now widely used in PV systems independently of the weather conditions. In function of the application, a DC-DC converter topology is chosen without any previous perfo...Maximum Power Point Tracking (MPPT) algorithms are now widely used in PV systems independently of the weather conditions. In function of the application, a DC-DC converter topology is chosen without any previous performance test under normal weather conditions. This paper proposes an experimental evaluation of MPPT algorithms according to DC-DC converters topologies, under normal operation conditions. Four widely used MPPT algorithms <i><i><span>i.e.</span></i><span></span></i> Perturb and Observe (P & O), Hill Climbing (HC), Fixed step Increment of Conductance (INCF) and Variable step Increment of Conductance (INCV) are implemented using two topologies of DC-DC converters <i><span>i.e.</span></i><span> buck and boost converters. As input variables to the PV systems, recorded irradiance and temperature, and extracted photovoltaic parameters (ideality factor, series resistance and reverse saturation current) were used. The obtained results show that buck converter has a lot of power losses when controlled by each of the four MPPT algorithms. Meanwhile, boost converter presents a stable output power during the whole day. Once more, the results show that INCV algorithm has the best performance.</span>展开更多
Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of ...Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of this article lies in the application of a genetic algorithm interval type-2 fuzzy logic controller (GAIT2FLC) in the design of fuzzy controller for the position control of DC Motor. The entire system has been modeled using MATLAB R11a. The performance of the proposed GAIT2FLC is compared with that of its corresponding conventional genetic algorithm type-1 FLC in terms of several performance measures such as rise time, peak overshoot, settling time, integral absolute error (IAE) and integral of time multiplied absolute error (ITAE) and in each case, the proposed scheme shows improved performance over its conventional counterpart. Extensive simulation studies are conducted to compare the response of the given system with the conventional genetic algorithm type-1 fuzzy controller to the response given with the proposed GAIT2FLC scheme.展开更多
为提高静止无功补偿器(static var compensator,SVC)应对直流电弧炉等冲击性负载的闪变抑制性能,文中在改进Takagi-Sugeno(TS)模糊算法的基础上,提出一种SVC滚动预测控制方法。首先,建立直流电弧炉电气模型并仿真分析其无功特性;然后,...为提高静止无功补偿器(static var compensator,SVC)应对直流电弧炉等冲击性负载的闪变抑制性能,文中在改进Takagi-Sugeno(TS)模糊算法的基础上,提出一种SVC滚动预测控制方法。首先,建立直流电弧炉电气模型并仿真分析其无功特性;然后,针对经典TS模糊预测算法应用于波动负荷时出现的输出异常置0情况,提出一种范围自适应修正的改进方法,该方法能消除一类算法应用机理导致的异常值,从而提高TS模糊算法对波动负荷无功功率预测的可靠性和准确性;最后,基于模型训练时间约束,建立无功功率半周期滚动预测控制模型,提前10 ms预测无功功率,改善了SVC传统控制系统响应的滞后特性。仿真结果表明,相比于SVC传统控制方法,所提方法的平均闪变改善率提高了54.17%,验证了所提方法对闪变现象的抑制效果提升显著。展开更多
针对新能源接入、负荷投切所导致的直流微电网电压质量下降与系统呈现低惯性的问题,传统惯性控制随着电网规模的扩大适应性降低,因此提出一种多直流电力弹簧(DC electric springs,DCESs)单元下的直流微网电压协同控制策略,首先采用分布...针对新能源接入、负荷投切所导致的直流微电网电压质量下降与系统呈现低惯性的问题,传统惯性控制随着电网规模的扩大适应性降低,因此提出一种多直流电力弹簧(DC electric springs,DCESs)单元下的直流微网电压协同控制策略,首先采用分布式一致性算法通过稀疏通信网络交换本地信息与相邻信息,求解全局母线电压平均值,并引入积分环节提高传统通信方式的收敛性。接着考虑系统负荷投切以及源侧功率波动导致的电压突变,基于DCES中的双向全桥DC/DC变换器构建预测模型,令各DCES根据系统功率波动状态自适应求解最佳虚拟电容值,平滑直流母线电压,提升了动态响应速度,同时分析了系统电压的收敛性与稳定性。最后通过MATLAB/Simulink在随机波动负荷、实际光伏场景下从电压质量、即插即用性能、系统惯性3个方面验证了模型的有效性,所提出的控制策略在保证系统电压平稳的同时,具有更优的动态响应能力。展开更多
文摘Maximum Power Point Tracking (MPPT) algorithms are now widely used in PV systems independently of the weather conditions. In function of the application, a DC-DC converter topology is chosen without any previous performance test under normal weather conditions. This paper proposes an experimental evaluation of MPPT algorithms according to DC-DC converters topologies, under normal operation conditions. Four widely used MPPT algorithms <i><i><span>i.e.</span></i><span></span></i> Perturb and Observe (P & O), Hill Climbing (HC), Fixed step Increment of Conductance (INCF) and Variable step Increment of Conductance (INCV) are implemented using two topologies of DC-DC converters <i><span>i.e.</span></i><span> buck and boost converters. As input variables to the PV systems, recorded irradiance and temperature, and extracted photovoltaic parameters (ideality factor, series resistance and reverse saturation current) were used. The obtained results show that buck converter has a lot of power losses when controlled by each of the four MPPT algorithms. Meanwhile, boost converter presents a stable output power during the whole day. Once more, the results show that INCV algorithm has the best performance.</span>
文摘Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of this article lies in the application of a genetic algorithm interval type-2 fuzzy logic controller (GAIT2FLC) in the design of fuzzy controller for the position control of DC Motor. The entire system has been modeled using MATLAB R11a. The performance of the proposed GAIT2FLC is compared with that of its corresponding conventional genetic algorithm type-1 FLC in terms of several performance measures such as rise time, peak overshoot, settling time, integral absolute error (IAE) and integral of time multiplied absolute error (ITAE) and in each case, the proposed scheme shows improved performance over its conventional counterpart. Extensive simulation studies are conducted to compare the response of the given system with the conventional genetic algorithm type-1 fuzzy controller to the response given with the proposed GAIT2FLC scheme.
文摘为提高静止无功补偿器(static var compensator,SVC)应对直流电弧炉等冲击性负载的闪变抑制性能,文中在改进Takagi-Sugeno(TS)模糊算法的基础上,提出一种SVC滚动预测控制方法。首先,建立直流电弧炉电气模型并仿真分析其无功特性;然后,针对经典TS模糊预测算法应用于波动负荷时出现的输出异常置0情况,提出一种范围自适应修正的改进方法,该方法能消除一类算法应用机理导致的异常值,从而提高TS模糊算法对波动负荷无功功率预测的可靠性和准确性;最后,基于模型训练时间约束,建立无功功率半周期滚动预测控制模型,提前10 ms预测无功功率,改善了SVC传统控制系统响应的滞后特性。仿真结果表明,相比于SVC传统控制方法,所提方法的平均闪变改善率提高了54.17%,验证了所提方法对闪变现象的抑制效果提升显著。
文摘针对新能源接入、负荷投切所导致的直流微电网电压质量下降与系统呈现低惯性的问题,传统惯性控制随着电网规模的扩大适应性降低,因此提出一种多直流电力弹簧(DC electric springs,DCESs)单元下的直流微网电压协同控制策略,首先采用分布式一致性算法通过稀疏通信网络交换本地信息与相邻信息,求解全局母线电压平均值,并引入积分环节提高传统通信方式的收敛性。接着考虑系统负荷投切以及源侧功率波动导致的电压突变,基于DCES中的双向全桥DC/DC变换器构建预测模型,令各DCES根据系统功率波动状态自适应求解最佳虚拟电容值,平滑直流母线电压,提升了动态响应速度,同时分析了系统电压的收敛性与稳定性。最后通过MATLAB/Simulink在随机波动负荷、实际光伏场景下从电压质量、即插即用性能、系统惯性3个方面验证了模型的有效性,所提出的控制策略在保证系统电压平稳的同时,具有更优的动态响应能力。
