Global Maximum Power Point Tracking Using Genetic Algorithm Combined with PSO Tuned PID Controller

被引:0
作者
Bouakkaz, Mohammed Salah [1 ]
Boukadoum, Ahmed Hcene [1 ]
Boudebbouz, Omar [1 ]
Bouchaala, Abdel Djabar [1 ]
Boutasseta, Nadir [2 ]
Attoui, Issam [2 ]
Bouraiou, Ahmed [3 ]
Motahhir, Saad [4 ]
机构
[1] Univ 20 Aout 1955, Dept Elect Engn, Lab Electrotech Skikda LES, Skikda 21000, Algeria
[2] Res Ctr Ind Technol CRTI, POB 64, Algiers, Algeria
[3] Ctr Dev Energies Renouvelables CDER, Unite Rech Energies Renouvelables Milieu Saharien, Adrar 01000, Algeria
[4] SMBA Univ, ENSA, Fes, Morocco
来源
DIGITAL TECHNOLOGIES AND APPLICATIONS, ICDTA 21 | 2021年 / 211卷
关键词
Maximum power point tracking (MPPT); Genetic algorithm (GA); PID controller; Particle Swarm Optimization (PSO); FAULT-DIAGNOSIS; INDUCTION GENERATOR; SYSTEM; ENERGY; PERFORMANCE; MPPT; INC;
D O I
10.1007/978-3-030-73882-2_107
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Several techniques have been proposed to track the global maximum power point (GMPP) in the presence of multiple local peaks introduced when the PV generator is affected by partial shading. Such methods include scanning methods and advanced optimization-based strategies. In this paper, a Genetic Algorithm based MPPT, combined with PID controller tuned using PSO, is proposed to track the MPP. The GA algorithm is applied to give the reference voltage and measured PV voltage to the PID controller that its parameters were tuned using PSO. The obtained results give a good tracking performance of the GMPP under STC conditions and partial shading scenarios.
引用
收藏
页码:1171 / 1180
页数:10
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