Nonlinear Control Strategy of Single Phase Half Bridge Shunt Active Power Filter Interfacing Renewable Energy Source and Grid

Hekss, Zineb; Lachkar, I.; Abouloifa, A.; Echalih, Salwa; Aourir, M.; Giri, F.

doi:10.23919/acc.2019.8814428

Cited by 13 publications

(9 citation statements)

References 11 publications

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“…Dai et al 118 to demand balance as power constraints, through the analysis of the indicators of the hybrid energy storage system, we design a hybrid energy storage system to charge and discharge control mode of secondary revision control, however, the constraint condition of demand balance did not have the ideal effect, and the convergence speed and precision of algorithm also did not meet the design requirements. Hekss et al 119 studied a sliding filter algorithm to improve grid connection reliability, but the filter parameters used in the algorithm are fixed values, and the adaptability of the system is not fully demonstrated. Simmons et al 120 studied an adaptive control that takes the charge and discharges the power of the batteries as the objective function.…”

Section: Lithium Batteries and Supercapacitors Energy Storage Systemmentioning

confidence: 99%

The control of lithium‐ion batteries and supercapacitors in hybrid energy storage systems for electric vehicles: A review

Shen

2021

Intl J of Energy Research

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Summary This article discusses control solutions for hybrid energy systems composed of lithium‐ion batteries and supercapacitors for electric vehicles. The advantages and disadvantages of the respective systems of lithium‐ion batteries and supercapacitors as well as hybrid systems are discussed. This article summarizes the research on behavior modeling, optimal configuration, energy management, and so on from the two levels of energy storage components and energy storage systems, and provides theoretical and methodological support for the application and management of hybrid energy storage systems for electric vehicles. First, it summarizes the research progress of the hybrid energy system of lithium‐ion batteries and supercapacitors and its research significance for the development of electric vehicles. Then the circuit models of lithium‐ion batteries and supercapacitors are analyzed, and the control results of the respective systems and hybrid systems under different research methods are introduced to optimize resource allocation. Then based on the energy management and control strategy, the deficiencies of the respective research methods are analyzed. Finally, we emphasized and summarized some key issues for future research in this field. Therefore, the control optimization of hybrid systems has become the focus of the long‐term development of electric vehicles. An overview of the lithium battery‐supercapacitor hybrid system. Analyze the optimization strategy of lithium battery‐supercapacitor hybrid system from energy management. Summarize the circuit research of the hybrid system.

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Section: Lithium Batteries and Supercapacitors Energy Storage Systemmentioning

confidence: 99%

The control of lithium‐ion batteries and supercapacitors in hybrid energy storage systems for electric vehicles: A review

Shen

2021

Intl J of Energy Research

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“…In the first topology, a DC‐DC converter is used for tracking maximum power from solar PV panels, and a SAPF is used to improve power quality 4,7 . In the second topology, the PV source is connected to the power grid via a SAPF to ensure the MPPT functionality and the power quality requirement by compensating for harmonic currents and reactive power 8,9 . Among the more usual MPPT algorithms are the perturb‐and‐observe (PO) algorithm and incremental conductance (IC) algorithm 10,11 .…”

Section: Introductionmentioning

confidence: 99%

“…The half‐bridge SAPF topology offers interesting practical benefits compared to the conventional full‐bridge converter. For instance, it allows the reduction of the switching losses of the given power semiconductors, thus increasing the reliability of the system 8,9,18 …”

Section: Introductionmentioning

confidence: 99%

“…Among the more usual MPPT algorithms are the perturb‐and‐observe (PO) algorithm and incremental conductance (IC) algorithm 10,11 . The single‐phase SAPF has attracted the attention of many researchers because of its simple design and low cost 8,9,12‐14 . In a three‐phase system, the SAPF can be inserted at each phase of the nonlinear load and this way proves to be much suitable than implementing a higher power three‐phase SAPF 15‐17 .…”

Section: Introductionmentioning

confidence: 99%

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Advanced nonlinear controller of single‐phase shunt active power filter interfacing solar photovoltaic source and electrical power grid

Hekss

Abouloifa

Lachkar

et al. 2021

Int Trans Electr Energ Syst

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This paper addresses the nonlinear controller design and the stability analysis of a shunt active power filter (SAPF) interfacing a solar photovoltaic (PV) system that consists of a couple of PV panels, a single-phase two-stage IGBT half-bridge SAPF and two identical DC link capacitors. We seek for the considered system the fulfillment of three control objectives: (a) extracting the maximum PV power using an appropriate maximum power point tracking (MPPT) algorithm; (b) regulation of the DC link capacitor voltages to the reference provided by the MPPT controller hence ensuring the exchange of power between the PV source and the AC power grid; (c) compensation for reactive power and undesired harmonics caused by the nonlinearity of electronic power loads, that is, performing power factor correction (PFC). The control objectives are achieved using a new two-loop cascaded controller. The Backstepping approach is applied in the inner loop to perform PFC. A filtered proportional-integral (PI) controller is applied in the outer loop to ensure tight regulation of the PV voltage. The MPPT control is implemented using a perturb-and-observe (PO) algorithm. The performance of the closed-loop system under the two-loop control strategy is formally analyzed through the Lyapunov approach applied to the averaged model. Numerical simulations are performed in MATLAB/SimPowerSystems environment to validate the design methodology and to confirm the theoretically predicted performances of the system under the proposed nonlinear controller.average analysis, Lyapunov stability analysis, nonlinear control, power factor correction, shunt active power filter, solar photovoltaic system List of Symbols and Abbreviations: L g , grid inductor; r g , grid resistor; R, load resistor; L, load inductor; C pv , filter capacitor; r f , filter resistor; L f , filter inductor; N s ,N p , number of connected modules in series and in parallel respectively; G, irradiance; T, temperature; μ, binary switching signal; i g , grid current; v go , grid voltage; i f , filtering current; i L , load current; i pv1 , i pv2 , PV output currents; v pv1 , v pv2 , PV output voltages; u, continuous control input; β, external control signal; P pv , PV panels power; v f , inverter output voltage; v g , voltage at point of common coupling; I f , peak value of output filter current; V f , peak value of inverter output voltage; θ 1 , phase of the voltage at point of common coupling; θ 2 , phase of the output filter current; χ, square of the PV voltage; u Ã , Steady state value of u; V , Lyapunov function candidate; f PWM , switching frequency; Q g , reactive power; T g , grid period; P g , active power; c 1 ,c 2 , c 3 , c 4 , controller parameters; ω g , angular frequency; IC, incremental conductance; IGBT, insulated-gate bipolar transistor; MPP, maximum power point; MPPT, maximum power point tracking; PCC, point of common coupling; PFC, power factor correction; PI, proportional-integral; PO, perturb and observe; PV, photovoltaic; PWM, pulse width modulation principle; SAP...

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“…A way to increase the performance of the active filtering system is the synthesis and implementation of new control algorithms, which are simple to implement and allow for high sampling frequencies. The literature illustrates the implementation of adaptive controllers [11,14,16], sliding mode [17][18][19][20][21][22][23], fuzzy [24], or combining these techniques with each other, or with neural techniques [25][26][27][28][29], both in regulating the DC-capacitor voltage and compensation current.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Control of DC Voltage in Three-Phase Three-Wire Shunt Active Power Filters Systems

et al. 2020

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This paper is focused on an adaptive controller for the direct current (DC) voltage in three-phase three-wire shunt active power filters systems. Although the controller structure of the proportional-integral (PI) type is determined off-line and does not change, the prescribed DC voltage and the controller parameters are calculated in an adaptation block, depending on the non-active power to be compensated. The adaptive control is based on the design expressions for the DC circuit of the shunt active power filter found by the authors, based on the detailed analysis of its operation, during the active filtering. The performances of the proposed adaptive control and its advantages compared to the classical control (where the prescribed DC voltage and the controller parameters are constant) were first determined on the virtual model of a laboratory setup. Then, the adaptive control was implemented on the dSPACE 1103 control board, which allowed the experimental determinations that prove and support the results obtained on the virtual model.

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Nonlinear Control Strategy of Single Phase Half Bridge Shunt Active Power Filter Interfacing Renewable Energy Source and Grid

Cited by 13 publications

References 11 publications

The control of lithium‐ion batteries and supercapacitors in hybrid energy storage systems for electric vehicles: A review

The control of lithium‐ion batteries and supercapacitors in hybrid energy storage systems for electric vehicles: A review

Advanced nonlinear controller of single‐phase shunt active power filter interfacing solar photovoltaic source and electrical power grid

Adaptive Control of DC Voltage in Three-Phase Three-Wire Shunt Active Power Filters Systems

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