Active disturbance rejection control on load frequency of multi-area power systems with high-proportion renewable energy

doi:10.3969/j.issn.2097-0706.2022.10.005

Abstract

Abstract:

Due to the fluctuation and randomness of renewable energy，the load frequency of a multi-area renewable energy power system is varied， complex and difficult to be controlled. In order to improve the stability of power systems，a cascade active disturbance rejection control method based on multi-objective genetic algorithm for the load frequency control of multi-area renewable energy power systems is proposed. The method can boost the anti-disturbance performance of the system by introducing cascade structure to linear active disturbance rejection control， and reduce the deviation of the frequency and tie-line power by taking multi-objective genetic algorithm to optimize the parameters of the designed controller. In addition，the simulation results of the power system under different control strategies are compared. The results show that the designed control system has good dynamic performance，and can quickly eliminate the disturbance and maintain the stability of the system. Simulation results verify the effectiveness of the designed controller.

Key words: renewable energy, multi-area power system, load frequency control, active disturbance rejection control, multi-objective genetic algorithm, new power system, carbon neutrality

CLC Number:

TK01:TP273

LI Pengzhen, LIU Yanhong, WU Zhenlong. Active disturbance rejection control on load frequency of multi-area power systems with high-proportion renewable energy[J]. Integrated Intelligent Energy, 2022, 44(10): 33-41.

Figures/Tables 18

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Table 1

Optimized parameters of the cascaded ADRC

系统	位置	$ω c$	$b$	$ω o$
光伏系统	外环	4.776 4	-96.556 1	0.439 0
光伏系统	内环	0.540 0	16.000 0	33.800 0
火电系统	外环	7.079 7	4.000 0	1.800 0
火电系统	内环	2.000 0	0.600 0	100.000 0
风电系统	外环	0.448 9	-2.565 3	6.478 8
风电系统	内环	3.964 0	4.573 0	0.634 5

Table 1

Fig.6

Fig.7

Fig.8

Table 2

IAE index of the power system without wind power

控制策略	场景	$I A E f 1$	$I A E f 2$	$I A E P t i e$	$I A E t o t a l$
COA:PDn-PI	1	0.018 0	0.022 1	0.006 4	0.046 5
COA:PDn-PI	2	0.063 5	0.231 3	0.108 9	0.403 7
Cascaded ADRC	1	0.013 7	0.013 1	0.009 7	0.036 5
Cascaded ADRC	2	0.007 2	0.132 3	0.056 9	0.196 4
MOGA:CADRC	1	0.010 5	0.010 7	0.008 2	0.029 4
MOGA:CADRC	2	0.007 3	0.141 8	0.039 2	0.188 3

Table 2

Fig.9

Fig.10

Fig.11

Table 3

IAE index of the wind power integrated power system

控制策略	场景	$I A E f 1$	$I A E f 2$	$I A E P t i e$	$I A E t o t a l$
COA:PDn-PI	1	0.011 2	0.010 4	0.001 7	0.023 3
COA:PDn-PI	2	0.151 2	0.158 7	0.037 2	0.347 1
Cascaded ADRC	1	0.013 6	0.012 6	0.009 8	0.036 0
Cascaded ADRC	2	0.007 2	0.132 3	0.056 9	0.196 4
MOGA:CADRC	1	0.010 5	0.010 9	0.008 3	0.029 7
MOGA:CADRC	2	0.007 3	0.141 8	0.039 2	0.188 3

Table 3

Fig.12

Fig.13

Fig.14

Fig.15

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