Bidirectional Buck-boost Converter Research Articles

A Proposed Supercapacitor Integrated with an Active Power Filter for Improving the Performance of a Wind Generation System under Nonlinear Unbalanced Loading and Faults

This study proposes the integration of a supercapacitor (SC) with the DC link of a three-phase four-wire active power filter (APF) by using an interfaced three-level bidirectional buck-boost converter controlled by the fuzzy control approach. APF is a flexible alternating current transmission system (FACTS) device that enhances power quality in the electrical network by reducing the load current harmonics and compensating the reactive power. Regulating the DC voltage of the APF’s DC link and absorbing fluctuations in compensated reactive power during disturbances are the major objectives of the integration of an SC circuit to APF. The studied model is a wind farm of Gabal El-Zeit with a total capacity of 580 MW, connected to unbalanced nonlinear loads. The Gabal El-Zeit wind farm is divided into three projects with a capacity of 240 MW, 220 MW, and 120 MW. The model is simulated by the MATLAB/SIMULINK program, and the effectiveness of the proposed methodology is proved by applying different types of faults such as single-line-to-ground, double-line-to-ground, and three-line-to-ground faults. In addition, an additional SC circuit with a two-level converter is connected to the generators coupled to the wind turbines to enhance the performance of the wind farm during disturbances. The results show that SC-integrated APF can reduce the harmonic distortion and compensate the reactive power for high or low inductive loads. Also, it can regulate the DC voltage and absorb the fluctuations in the reactive power during faults. Finally, the performance and the stability of the overall electric system are improved.

Implementation of artificial neural network based control for power quality enhancement of proton exchange membrane fuel cell powered distributed generation system

In this paper, a fuel cell and battery-based distributed generation system is demonstrated. A proton exchange membrane fuel cell is the primary power generator in this decentralized system, with a lead-acid battery providing backup power. A boost converter regulates the fuel cell’s output power to ensure its optimal performance. A bidirectional buck-boost converter has been employed to integrate battery using slope compensated current control. 5-level cascaded H-Bridge inverter is used to convert available DC power into AC power while integrating DG systems with the grid and improving power quality. The artificial neural network has been trained and used to generate the estimated reference current for sinusoidal pulse width modulation techniques. The artificial neural network has been fine-tuned using the scaled conjugate gradient with the performance value 0.094056. The THD of grid current has been reduced by 12.5% and 8.14% approximately for 30 Ω resistive, 30 mH inductive load and 20 Ω resistive, 15 mH inductive load respectively. The system has been simulated in Matlab/Simulink, and the findings have been validated. The results demonstrate the effectiveness of the methodology.

Hybrid Control and Energy Management of a Residential System Integrating Vehicle-to-Home Technology

Electric vehicles (EV) and photovoltaic (PV) systems are increasingly becoming environmentally friendly and more affordable solutions for consumers. This article discusses the integration of PV and EV in a residential system to meet the requirements of residential loads taking into account the PV supplied power, availability and the state of charge (SOC) of EVs. A hybrid control model has been proposed to control the residential system. The combined PI-Fuzzy logic controller is employed to control the buck-boost bi-directional converter. The DC-AC grid-side converter is controlled by the ADRC controller. The effectiveness of PI-Fuzzy logic controller in reducing voltage and current ripples and ADRC controller in rejecting disturbances is demonstrated in each case. A rule-based energy management strategy has been proposed to control the flow of energy between the components of the residential system. The suggested energy management system (EMS) covers every scenario that might occur. Whether the EV is linked to the home or not, and also takes into account the owner using the EV in an emergency situation. The EV operates in two modes, Home-to-Vehicle (H2V) mode and Vehicle-to-Home (V2H) mode, depending on the power produced by the PV and the conditions related to the EV. All possible scenarios are tested and validated. The simulation results show that the proposed EMS is a reliable solution that can reduce the power grid intervention.

Robust adaptive nonlinear control of plugin hybrid electric vehicles for vehicle to grid and grid to vehicle power flow with hybrid energy storage system

Plugin hybrid electric vehicles (PHEVs) can solve the concerns of toxic gases emissions from fossil fuel. The PHEV under consideration consists of an on-board smart charger and a hybrid energy storage system (HESS) composed of the battery as a primary power source and an ultracapacitor (UC) as a secondary power source conjoined with two DC–DC bidirectional buck-boost converters. The on-board charging unit comprises of an AC–DC boost rectifier and DC–DC buck converter. The entire system’s state model has been derived. An adaptive supertwisting sliding mode controller (AST-SMC) has been proposed for the unitary power factor correction at the grid side, tight voltage regulation of the charger and the DC bus, adaptation of time varying parameters and tracking of the currents involving the variation in the load profile. A genetic algorithm has been applied for optimizing the cost function of the controller gains. Key results refers reduction of chattering, adaptation of parametric variations, nonlinearities and external disturbances of the dynamical system. HESS results presents negligible convergence time and overshoots/undershoots even at the transients, and no steady state error. For the driving mode, the switching between dynamic and static behaviors and for parking mode, vehicle to grid (V2G) and grid to vehicle (G2V) operations have been proposed. In order to make nonlinear controller intelligent to achieve the V2G and G2V functionality, a state of charge based high-level controller has also been proposed. A standard Lyapunov stability criteria has been used to ensure asymptotic stability of the entire system. The proposed controller has been compared with sliding mode control (SMC) and finite time synergetic control (FTSC) by the simulation results using MATLAB/Simulink. Also, the hardware in loop setup has been used to validate the performance in real-time.

Electric Vehicle Battery Charging Station based on Bipolar dc Power Grid with Grid-to-Vehicle, Vehicle-to-Grid and Vehicle-to-Vehicle Capabilities

An electric vehicle (EV) battery charging station (EV-BCS) based on a bipolar dc power grid is presented in this paper, which is capable of delivering power to the grid (vehicle-to-grid – V2G mode), and directly exchange power between different EVs connected to the EV-BCS (vehicle-to-vehicle – V2V mode), besides the traditional battery charging operation (grid-to-vehicle – G2V mode). The presented EV-BCS is based on three-level bidirectional buck-boost dc-dc converters and has a modular structure. Simulation results are presented with the aim of validating the aforementioned operation modes, being considered two EVs for simplicity reasons, since it is enough to validate the proposed operation modes. The presented results comprise both balanced and unbalanced operation in terms of power from the EVs viewpoint, with the purpose of considering a real scenario of operation, where a balanced consumption or power injection from the bipolar dc power grid side is always guaranteed.

Bidirectional Buck–Boost Converter With Reduced Power Loss and No Right-Half-Plane Zero

This article presents a novel hybrid bidirectional buck–boost converter (HBBC) for lithium-ion battery management. Unlike the conventional four-switch buck–boost converter (FBBC), whose power efficiency is greatly limited at heavy loads mainly due to high conduction loss from a high dc resistance (DCR) inductor, the proposed HBBC adopts assisted capacitive paths to reduce the current stress on the main inductive path. Thus, the conductive loss of inductor's DCR is greatly reduced in both the buck and boost modes. To verify the effectiveness of the proposed structure, detailed analyses on both the loop performance and conduction loss are provided. Compared with FBBC, the conversion efficiency of the proposed HBBC is increased by 23.3% in the boost mode, and the peak efficiency is up to 97.8% with an adopted inductor with a DCR of 270 mΩ.

Bidirectional Buck-Boost Converter Using Cascaded Energy Storage Modules Based on Cell Voltage Equalizers

Ordinary modular energy storage systems require cell- and module-level equalizers, in addition to a main bidirectional converter, increasing the system complexity and cost. This article proposes a bidirectional buck-boost converter using cascaded energy storage modules. Each module contains a cell-level equalizer with a half-bridge cell. The half-bridge cell in each module is utilized not only for the cell-level equalizer but also for the cascaded buck-boost converter. Module voltages are equalized by adjusting duty cycles of the half-bridge cells, allowing the elimination of dedicated module-level equalizers. Furthermore, the cascaded structure equivalently increases the switching frequency and reduces the inductor current ripple. An experimental charge-discharge cycling test using the prototype was performed for three electric double-layer capacitor modules. Cell and module voltages were gradually equalized during cycling, demonstrating the bidirectional power conversion and cell- and module-voltage equalization capabilities of the proposed converter.

Adaptive Aquila Optimization Controlled Deep Convolutional Neural Network for Power Management in Supercapacitors/Battery of Electric Vehicles

Electric Vehicles (EVs) may be a viable solution to reduce the huge energy consumption and greenhouse emissions of global transportation. However, the cost and range of batteries are two major obstacles for EV. An efficient Power management system for EVs, which includes Supercapacitor (SC) and battery with an optimized converter, is proposed in this paper. An optimal Direct Current (DC)-DC Bi-directional Buck-Boost Converter (BBBC) with a Proportional Integral Derivative (PID) controller is used for the optimal flow of power from the energy source to the drive during EV acceleration. The regenerative braking energy is allowed to return through the same bidirectional converter and retained in the Hybrid Energy Storage System (HESS) during the deceleration mode. A novel optimization is attained in the converter controller circuit using a Deep Convolution Neural Network (DCNN) and Adaptive Aquila Optimization Algorithm (AAqOA). The proposed strategy is validated using the results compared to conventional algorithms. In particular, the settling time of the suggested AAqOA model is 55.44%, 96.94%, 97.03%, and 91.87% better than the extant PI, DA, SSA, and AOA methods, respectively.

Large-signal stable composite control for the source DC–DC converter of onboard DC microgrid

In a modern electrified aircraft, fuel cells, batteries, and supercapacitors are promising power sources to supply the onboard electric loads, such as flight control actuators, avionics, etc. These loads are mainly regulated power converters and motor drive systems, which behave as constant power loads (CPLs) that can significantly affect the system’s stability. The system may become unstable and cannot operate at rated power. This paper proposes a composite controller composed of a passivity-based controller (PBC) and an extended high-gain state observer (EHGSO) for the terminal DC–DC converters of source units of an onboard DC microgrid. The PBC can guarantee system stability in all load types, while the EHGSO can improve control performances by accurately estimating system disturbances, including unmolded dynamics and parameter uncertainties. A test-rig setup, which consists of a CPL fed by two source units through two parallel-connected bidirectional Buck-Boost converters, is developed in the lab. The effectiveness of the proposed composite controller is verified by the experimental results performed by it.

Bidirectional Buck-Boost converter as an Active Power Decoupling schema for Single-Phase Power Inverters

The power ripple in the DC-link of photovoltaic and energy storage systems interconnected to the AC mains can drastically impact the lifespan of the photovoltaic panel and the system in general. This problem can be easily solved by using DC-link electrolytic capacitors as a passive decoupling method; however, this implies significant drawbacks such as increased volume and cost of the capacitor and a significant reduction in efficiency and reliability. This can be compensated by replacing electrolytic capacitors with active power decoupling methods based on power electronic converters. Thus, a Bidirectional Buck-Boost converter as an active power decoupling scheme is proposed. First, a power decoupling overview is addressed. Afterward, the operation of the Buck-Boost converter is detailed. Therefore, the control strategy is also explained. Finally, some simulations and preliminary experimental results to verify the integrated operation of the power converter are given.

Model Control and Digital Implementation of the Three Phase Interleaved Parallel Bidirectional Buck–Boost Converter for New Energy Electric Vehicles

In recent years, the imminent environmental problems and increasing attention to the global energy crisis have prompted the need for new opportunities and technologies to meet higher demands for clean and sustainable energy systems. As a result, new energy electric vehicles have been developed to replace fossil fuel cars. Therefore, this paper presents a three-phase interleaved parallel bidirectional buck–boost converter, which is the core factor of electrical energy flow regulation and management between the battery pack and motor drive inverter within the high voltage direct current bus and converts the voltage from two directions. Corresponding circuit topology, mathematical model, and control strategy are analyzed in three operation states: charge buck, discharge boost, and electric energy interaction modes. The digital implementation with double closed loop, power feedforward compensation, and bidirectional switching logic are realized by XDPTM Digital Power Controllers XDPP1100-Q040 of Infineon Technologies AG. Finally, the experimental results of the proposed converter clearly show that it achieves the objectives, namely, the feasibility and practicality of the system.

Power Quality Improvement of a Fuel Cell-Powered Filterless Distributed Generation System Using Sinusoidal Pulse Width Modulation

This paper proposes a distributed generation system based on fuel cells and batteries. The primary energy source for thedistributed generation system is a proton exchange membrane fuel cell, with a lead-acid battery serving as the energystorage medium. A boost converter regulates the output power of a fuel cell to guarantee smooth operation. The battery isconnected with the fuel cell to meet the power demand of the distributed generation system. A buck-boost bidirectionalconverter is employed as an interface between the battery and the DC link capacitor. The bidirectional converter operates onthe slope compensated current control approach. Two 5-level cascaded H-bridge inverters have been installed to improve thepower quality of distributed generation systems. The power flow between the source, grid, and nonlinear load is controlledusing a sinusoidal pulse width modulation approach. Nonlinear current compensation and capacitor voltage balancing aretwo features that improve power quality.

A New Continuous Input Current Nonisolated Bidirectional Interleaved Buck-Boost DC-DC Converter

In this paper, a new interleaved bidirectional buck-boost DC-DC converter is proposed. The input current of this converter is continuous and has a low ripple, that cause reduction in the size of the input filter of the converter. Because of these features, this converter is appropriate for renewable applications such as fuel cells and photovoltaic (PV) panels for obtaining maximum power in which the continuity of the input current is essential. The operation principle of this converter is detailed, and its power losses calculation shows the positive effects of the low input current ripple on its efficiency. The input current ripple of the proposed converter and conventional interleaved buck-boost converter has been calculated in detail. In addition, the comparison results of this converter with conventional interleaved buck-boost converters and other similar structures confirm that the proposed converter without utilizing extra components achieves continuous input current with low ripple. Compared with other buck-boost structures, the low input current ripple in the presented converter causes an improvement in its efficiency. An experimental prototype is implemented in the laboratory to confirm the correctness of theoretical analyses.

Increase Stability and Efficiency in PV-Battery-Grid Systems Using PSO Algorithm

In this article, the meta-heuristic algorithm PSO with PI fuzzy logic controller is proposed to develop a new control strategy of bidirectional converter (CSBC), in order to improve the stability and increase the efficiency of energy flow exchange in grid-connected photovoltaic generator (PVG) Battery hybrid system. The proposed command aims to satisfy the DC Motor load demand, manages the power flows from different parts, injects surplus energy into the grid as and when need, ensure charge-discharge battery operation even under the fluctuating condition of power generation, and stabilize the DC bus voltage. This new control has been placed in the network topology, which consists of a PVG Photovoltaic Generator, grid-connected DC/AC converter, storage battery and DC motor load. A bidirectional buck-boost converter is used for optimum exploit of power from PVG along with battery charging/discharging control, and for feeding DC motor load. The effectiveness of the proposed control scheme is demonstrated by using MATLAB / Simulink program. The results obtained, show that the proposed control provided the system with the stability of Vdc voltage, and contributed to improving the speed produced by the DC motor load. The results have been compared with the conventional control.

Simulation of a bi-directional buck-boost converter and application for the vehicle to grid, grid to vehicle

This paper presents a bidirectional buck-boost converter for bidirectional power flow, electric vehicle applications, and for power flow from source to load and load to source. Which is a vehicle to grid and grid to vehicle in terms of electric vehicle applications. The simulation has been done on a bidirectional buck-boost converter in MATLAB software using a hybrid energy storage system. Simulation proves the suitability for usage in electric vehicle applications and a hardware prototype has been created of the bidirectional buck-boost converter to verify the results of the converters working. In this converter soft switching can be used to reduce switching losses at many parts and to increase the overall efficiency of the bidirectional buck-boost converter.

Optimization and Power Management of Solar PV-based Integrated Energy System for Distributed Green Hydrogen Production

Photovoltaic-based integrated energy systems act as a possible modern technological solution for clean and affordable green hydrogen production. However, research attempts are required from the scientific community to develop power management, control, optimization algorithms, and new techniques for these integrated energy systems effective and economical operation. The integrated energy system considered in this work consists of a solar photovoltaic, battery, grid and proton exchange membrane (PEM) electrolyzer. PEM electrolyzer with a power rating of 100 kW is modelled as a controlled current sink to interfere with the DC bus directly. This work proposes a power management and control algorithm for the photovoltaic-based integrated energy system considering different parameters like availability of solar photovoltaic power, DC link voltage, battery state of charge (SOC), tariff and availability of grid power. Effective power-sharing among the different power sources increases system reliability and stability. Optimization is performed for optimal sizing and costing to achieve economical operation such that these photovoltaic-based integrated energy systems become affordable and are encouraged for wide use. The photovoltaic system operates at the maximum power point through a neural network-based control strategy; in addition to this, stacking in neural network topologies is also discussed for improving system accuracy in tracking the reference voltage for MPPT operation. The DC link voltage is controlled by interfacing the battery with the DC link via a bidirectional buck-boost power converter. The contribution of the work is to highlight the role of renewable energy sources for continuous green hydrogen production. Green hydrogen will be a critical driving force for the future transportation system, fuel cell-based power generation, and industries utilizing hydrogen in direct or indirect forms-that will help transition towards a carbon-free society. Optimization and time-domain simulation results indicated the economic and technical feasibility of the proposed photovoltaic-based integrated energy system for green hydrogen production with the best optimal configuration producing hydrogen at the cost of $ 4.806/kg and total net present cost of $749904.

Hybrid Renewable Power Generation for Modeling and Controlling the Battery Storage Photovoltaic System

A major portion of the global energy demand was likely to be fulfilled by an extensive supply of renewable power. Renewable energy outputs, on the other hand, are changeable due to the dynamic nature of their sources. The integration of these variable sources of power into current power grids is proving difficult for electrical power system operators all around the world. The fundamental issue with renewable energy systems is that, due to the stochastic nature of renewable power, electricity production varies from period to period. Recent research and development on renewable technologies can ensure the islands’ long-term electricity supply. Renewable energy sources, on the other hand, are limited by their unpredictable nature and significant reliance on weather conditions. To offset this disadvantage, several renewable energy sources and converters must be joined. To balance the power generation and load power, a hybrid renewable power generation for standalone application is proposed. The solar plant model is made up of a 170 W photovoltaic (PV) panel connected in series, and conversion of energy is done using the maximum power point tracking (MPPT) algorithm, which regulates a buck-boost converter modulation. The MPPT method used in the converter’s control step is based on perturb and observe (P&O) and enhanced with a PI controller. The bidirectional buck-boost DC-DC converters (BBDC) are utilized to preserve a DC-link voltage stable. This is also storing additional hybrid energy in a large battery and is distributed to the system load; then there is a shortage of hybrid power. The load current power is regulated in terms of the frequency and enables it to be achieved using three vector control technique voltage source inverters (VSI). The results were offered to demonstrate a hybrid performance of this organization.

Bi-directional buck-boost voltage converter for low-voltage uninterruptible power supply systems

Bi-directional buck-boost voltage converter for low-voltage uninterruptible power supply systems

Analysis of the PV-to-PV architecture with a bidirectional Buck-Boost converter under shading conditions

Differential power processing (DPP) architectures have been emerging as a promising strategy for mitigating the harmful effects of the photovoltaic (PV) string mismatches. In this strategy, DPP converters are connected in parallel with the PV string to improve the energy harvesting. However, in some situations, the position, intensity of shading, and the length of the string negatively influence the performance of such architectures. In this context, this work presents a novel mathematical approach that enables analyzing the effect of such aspects in the output power and efficiency of the PV-to-PV architecture. The set of derived equations allows determining the values of the currents flowing through the DPP converters that compose the PV-to-PV architecture. An important aspect is validated by the mathematical analysis, proving that the shading position on the PV-to-PV architecture directly impacts the phenomenon known as diverted current accumulation. To the best of the authors’ knowledge, this issue has not yet been assessed in the literature. Besides, this study is of major importance because it influences the losses in the power converters of the DPP structure. The assessment of various shading positions on the PV-to-PV architecture reveals that, in specific positions, the currents that flow through the converters are significantly reduced. For the set of situations analyzed, an improved energy harvesting from the PV-to-PV architecture and efficiency over 95% are verified.

A Low-Cost Cell-Level Differential Power Processing CMOS IC for Single Junction Photovoltaic Cells

This article presents a cell-level differential power processing IC to maximize the power yield under partial shading and mismatch condition in series-connected single junction photovoltaic (PV) cells. A 3-MHz bidirectional buck-boost converter is employed to realize voltage equalization technique forcing the PV cells to constantly operate close to their maximum power points. A novel and simple low-power low-area analog control circuit is proposed to maintain the high system efficiency at low and high levels of mismatch by obviating the need for power hungry blocks such as analog to digital converters, digital to analog converters, op-amps, saw-tooth generator, and regulators. The voltage of adjacent PV cells is used to drive the high-side switches through bootstrap supplies eliminating the need for voltage regulators. The performance of the proposed IC, fabricated in 130 nm CMOS process, is validated through simulation and experimental results. The converter is capable of processing mismatch currents up to 4 A while the control circuitry consumes less than 40 mW and a system efficiency above 95% is achieved.