基于变论域模糊控制光伏MPPT算法的仿真研究

doi:10.16180/j.cnki.issn1007-7820.2020.11.004

摘要/Abstract

摘要：

通常采用模糊控制算法设计的控制器对实现光伏系统MPPT控制具有针对性,在光伏系统或控制器参数改变时,会出现跟踪速度慢、稳定性差、甚至跟踪失效等问题。针对此问题,文中采用一种基于变论域模糊控制的MPPT算法,利用电导增量法的跟踪原理设计控制器的模糊规则来提高控制器的普适性。该算法引入伸缩因子实现变论域的设计以降低控制器参数改变对跟踪效果的影响。在MATLAB/Simulink中的仿真结果表明,变论域模糊控制法在跟踪速度上相较于电导增量法提高了近一倍,且在论域失配与光伏系统模型失配情况下,相比于常规模糊控制能够更好地实现光伏系统MPPT控制。

关键词: 光伏发电系统, 最大功率点跟踪, 电导增量法, 伸缩因子, 变论域模糊控制, MATLAB仿真

Abstract:

Generally, the controller designed by the fuzzy control algorithm is targeted to realize the MPPT control of the photovoltaic system. When the PV system or controller parameters change, there will be problems such as slow tracking speed, poor stability, and even tracking failure. In view of this, an MPPT algorithm based on variable universe fuzzy control is adopted in this paper. The fuzzy rule of controller is designed by using the tracking principle of conductance increment method to improve the universality of the controller. In addition, the algorithm introduces a scaling factor to implement the design of the variable universe to reduce the impact of changes in controller parameters on the tracking effect. The simulation model is built in MATLAB/Simulink, and the feasibility of the algorithm is verified. The simulation results show that the algorithm is nearly doubled in tracking speed compared with the conductance increment method. The simulation results show that the variable-domain fuzzy control method is nearly doubled in tracking speed compared with the conductance increment method. Besides, under the mismatch of the domain mismatch and the PV system model, the new method can better realize the MPPT control of the photovoltaic system compared with the conventional fuzzy control.

Key words: photovoltaic power generation system, MPPT, incremental conductance, scaling factor, variable universe fuzzy control, MATLAB simulation

中图分类号:

TP273.4

蒋鹏程,汤占军,刘萍兰. 基于变论域模糊控制光伏MPPT算法的仿真研究[J]. 电子科技, 2020, 33(11): 16-23.

JIANG Pengcheng,TANG Zhanjun,LIU Pinglan. Simulation Study of Photovoltaic MPPT Based on Variable Universe Fuzzy Control[J]. Electronic Science and Technology, 2020, 33(11): 16-23.

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ec e	NB	NS	Z	PS	PB
NB	PB	PB	PS	PS	Z
NS	PB	PS	PS	Z	Z
Z	PS	Z	Z	Z	NS
PS	Z	Z	NS	NS	NB
PB	Z	NS	NS	NB	NB

类别	参数	数值
光伏电池a	短路电流I_sc/A	9.1
	开路电压U_oc/V	36.5
	峰值电流I_m/A	8.2
	峰值电压U_oc/V	30.4
光伏电池b	短路电流I_sc/A	5.9
	开路电压U_oc/V	22.4
	峰值电流I_m/A	5.4
	峰值电压U_oc/V	18.4
系统电路	电感L/mH	0.3
	电容C_pv/mF	10
	电容C/mF	0.1
	电阻R/Ω	20
控制器	模糊输入论域X_e	[-0.01,0.01]
	模糊输入论域X_ec	[-0.005,0.005]
	模糊输出论X_e_,ec	[-0.2,0.2]
	伸缩因子参数λ	0.2
	伸缩因子参数τ	1

环境条件	类别	稳定时间 /s	稳定时电压 /V	稳定功率 /W
T=25 ℃ S=1 000 W·m²	INC	0.08	30.4±0.2	250.6
	文中算法	0.038	30.4±0.2	250.6
	标准值	-	30.5	251.1

环境条件	类别	光照突变阶段			光照持续变化阶段
环境条件	类别	稳定时间/s	稳定时电压/V	稳定时功率/W	光照持续变化阶段
0.11 s时,光照由1 000 W·m^-2突变到500 W·m^-2; 0.15 s时,光照以 500 W·m^-2·s^-1的速度持续上升	INC	0.14	30.1±0.2	122.12	功率下降
	文中算法	0.112	30.1±0.2	122.12	功率持续上升
	标准值	-	30.1	122.12	功率持续上升

环境条件	类别	标准测试条件		光照突变
环境条件	类别	稳定时间/s	稳定功率/W	稳定时间/s	稳定功率/W
开始时,T=25 ℃ S=1 000W·m^-2; 0.07 s时,光照由 1 000 W·m^-2突变到500 W·m^-2	Fuzzy	0.055	250.6	0.102	121.71
	文中算法	0.038	250.6	0.073	122.08
	标准值	-	251.1	-	122.12