Robust maximum power point tracking scheme for PV systems based on attractive ellipsoid method

被引:10
作者
Cortes-Vega, David [1 ]
Alazki, Hussain [2 ]
机构
[1] Univ Michoacana, Fac Elect Engn, Morelia, Michoacan, Mexico
[2] Univ Autonoma Carmen, Fac Engn, Campeche, Mexico
关键词
DC-DC converter; MPPT; PV systems; Robust control; CONDUCTANCE MPPT ALGORITHM; MODEL-PREDICTIVE CONTROL; PHOTOVOLTAIC SYSTEMS; CONTROLLER; DESIGN; SIMULATION; UNIFORM;
D O I
10.1016/j.segan.2020.100410
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The Photovoltaic (PV) systems have arisen as one of the best alternatives to electrical power generation based on renewable sources. However, such systems lack on energy transformation efficiency that gets worse in weather changing conditions. Hence, the application of Maximum Power Point Tracking (MPPT) methods that can extract the maximum power even for varying weather conditions is an essential task in PV systems. This paper proposes the design of a robust MPPT system composed by a regression plane to generate the voltage references that obtain the maximum PV power and a robust feedback controller based on the Attractive Ellipsoid Method (AEM) to track such reference applied to a PV array that supplies a load through a buck-boost converter. AEM is a methodology to design robust controllers for a specific class of systems satisfying a boundedness condition even in the case of incomplete system information. The stability of the system even under uncertainties and external disturbances is guaranteed by solving an optimization problem which generates the optimal controller gains using Linear Matrix Inequalities (LMI). (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:9
相关论文
共 39 条
[21]   Simulation and experimental design of a new advanced variable step size Incremental Conductance MPPT algorithm for PV systems [J].
Loukriz, Abdelhamid ;
Haddadi, Mourad ;
Messalti, Sabir .
ISA TRANSACTIONS, 2016, 62 :30-38
[22]  
Lyden S., 2012, em AUPEC - 22nd Australasian Universities Power Engineering Conference, P1
[23]   MPPT in PV systems under partial shading conditions using artificial vision [J].
Martin, Aranzazu D. ;
Vazquez, Jesus R. ;
Cano, J. M. .
ELECTRIC POWER SYSTEMS RESEARCH, 2018, 162 :89-98
[24]   Backstepping Controller Design to Track Maximum Power in Photovoltaic Systems [J].
Martin, Aranzazu D. ;
Vazquez, Jesus R. .
AUTOMATIKA, 2014, 55 (01) :22-31
[25]   A new variable step size neural networks MPPT controller: Review, simulation and hardware implementation [J].
Messalti, Sabir ;
Harrag, Abdelghani ;
Loukriz, Abdelhamid .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 68 :221-233
[26]   MPPT of Photovoltaic Systems Using Sensorless Current-Based Model Predictive Control [J].
Metry, Morcos ;
Shadmand, Mohammad B. ;
Balog, Robert S. ;
Abu-Rub, Haitham .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2017, 53 (02) :1157-1167
[27]   Novel MPPT techniques for photovoltaic systems under uniform irradiance and Partial shading [J].
Mirza, Adeel Feroz ;
Ling, Qiang ;
Javed, M. Yaqoob ;
Mansoor, Majad .
SOLAR ENERGY, 2019, 184 :628-648
[28]   Efficient maximum power point tracking using model predictive control for photovoltaic systems under dynamic weather condition [J].
Mosa, Mostafa ;
Shadmand, Mohammad B. ;
Balog, Robert S. ;
Abu Rub, Haitham .
IET RENEWABLE POWER GENERATION, 2017, 11 (11) :1401-1409
[29]   Backstepping based non-linear control for maximum power point tracking in photovoltaic system [J].
Naghmash ;
Armghan, Hammad ;
Ahmad, Iftikhar ;
Armghan, Ammar ;
Khan, Saud ;
Arsalan, Muhammad .
SOLAR ENERGY, 2018, 159 :134-141
[30]   MPPT control design of PV system supplied SRM using BAT search algorithm [J].
Oshaba, A. S. ;
Ali, E. S. ;
Abd Elazim, S. M. .
SUSTAINABLE ENERGY GRIDS & NETWORKS, 2015, 2 :51-60