A new RBFN based MPPT controller for grid-connected PEMFC system with high step-up three-phase IBC

Extraction of maximum power from a proton exchange membrane fuel cell (PEMFC) power source is necessary for its economical and optimal utilization. In this paper, a neural network based maximum power point tracking (MPPT) controller is proposed for the grid-connected PEMFC system. Radial basis function network (RBFN) algorithm is implemented in the neural network controller to extract the maximum power from PEMFC. A high step-up three-phase interleaved boost converter (IBC) is also designed in order to reduce the current ripples coming out from the PEMFC. Interleaving technique provides high power capability and reduces the voltage stress on the power semiconductor devices. The performance analysis of the proposed RBFN MPPT controller is analyzed in MATLAB/Simulink platform for both standalone as well as for the grid-connected PEMFC system.     

Modeling and performance analysis of renewable hydrogen energy hub connected to an ac/dc hybrid microgrid

This paper proposes a system modeling and performance analysis of a renewable hydrogen energy hub (RHEH) connected to an ac/dc hybrid microgrid (MG). The proposed RHEH comprises a photovoltaic (PV)-based renewable energy source (RES) as the primary source, a proton exchange membrane fuel cell (PEMFC) as the secondary power source, and a proton exchange membrane electrolyzer (PEMELZ) that can generate and store hydrogen in a hydrogen tank. All these resources are directly connected at the dc bus of the ac/dc microgrids. The PEMFC operates and utilizes the hydrogen from the hydrogen tank when the energy generated by RES cannot meet the load demand. A coordinated power flow control approach has been developed for the RHEH to mitigate the mismatch between generation and demand in the ac/dc microgrid and produce renewable hydrogen when renewable power is in excess. The paper also proposes a modified hybrid Perturb & Observe-Particle Swarm Optimization (Hybrid PO-PSO) algorithm to ensure the maximum power point tracking (MPPT) operation of the PV and the PEMFC. The operation of the proposed RHEH is validated through simulations under various critical conditions. The results show that the proposed RHEH is effective to maintain the system power balance and can provide power-to-hydrogen and hydrogen-to-power when required.     

An adaptive sliding mode observer based near-optimal OER tracking control approach for PEMFC under dynamic operation condition

Tracking control of oxygen excess ratio (OER) is crucial for dynamic performance and operating efficiency of the proton exchange membrane fuel cell (PEMFC). OER tracking errors and overshoots under dynamic load limit the PEMFC output power performance, and also could lead oxygen starvation which seriously affect the life of PEMFC. To solve this problem, an adaptive sliding mode observer based near-optimal OER tracking control approach is proposed in this paper. According to real time load demand, a dynamic OER optimization strategy is designed to obtain an optimal OER. A nonlinear system model based near-optimal controller is designed to minimize the OER tracking error under variable operation condition of PEMFC. An adaptive sliding mode observer is utilized to estimate the uncertain parameters of the PEMFC air supply system and update parameters in near-optimal controller. The proposed control approach is implemented in OER tracking experiments based on air supply system of a 5 kW PEMFC test platform. The experiment results are analyzed and demonstrate the efficacy of the proposed control approach under load changes, external disturbances and parameter uncertainties of PEFMC system.     

Maximum power point tracking of a proton exchange membrane fuel cell system using PSO-PID controller

Fuel cells output power depends on the operating conditions, including cell temperature, oxygen partial pressure, hydrogen partial pressure, and membrane water content. In each particular condition, there is only one unique operating point for a fuel cell system with the maximum output. Thus, a maximum power point tracking (MPPT) controller is needed to increase the efficiency of the fuel cell systems. In this paper an efficient method based on the particle swarm optimization (PSO) and PID controller (PSO-PID) is proposed for MPPT of the proton exchange membrane (PEM) fuel cells. The closed loop system includes the PEM fuel cell, boost converter, battery and PSO-PID controller. PSO-PID controller adjusts the operating point of the PEM fuel cell to the maximum power by tuning of the boost converter duty cycle. To demonstrate the performance of the proposed algorithm, simulation results are compared with perturb and observe (P&O) and sliding mode (SM) algorithms under different operating conditions. PSO algorithm with fast convergence, high accuracy and very low power fluctuations tracks the maximum power point of the fuel cell system.     

Performance improvement of PEM fuel cell power system using fuzzy logic controller-based MPPT technique to extract the maximum power under various conditions

Power generation of a fuel cell (FC) is mostly dependent upon operational variables such as cell temperature and membrane water content. There is an individual maximum power point (MPP) on the P-I curve of the FC. The location of the MPP varies with respect to the MPP position. Thus, an MPP tracking (MPPT) system should exist to guarantee that the FC works at the MPP in order to maximize the functionality. Due to their straightforward structure, prevalent MPPT methods had strong functionality. However, their primary limitations include fluctuations around the MPP and inefficiency under abrupt variations of operating conditions. The primary objective of this paper is to maintain the PEMFCs operation at an efficient power point. To this purpose, the efficiency of PEM-FC is tested and enhanced using a variety of MPPT-based smart controller techniques. To determine the appropriate MPPT controller parameters, the modified fluid search optimization (MFSO) approach and fuzzy logic controller (FLC) are employed. Furthermore, the MFSO method is deployed to adjust the membership functions (MFs) of the FLC. The MFSO is an excellent approach for coping with the stochastic behavior of the PEM-FC system when the temperature and water content of the membrane change. In terms of improved dynamic behavior, better convergence rate, reduced oscillations, and better tracking of the MPP, the results obtained by employing the suggested strategy demonstrate the superior functionality of the system compared to case using other methods. Moreover, the power generated by the PEMFC system is less than the nominal capacity for the temperature's rated capacity. Therefore, the deficit in power would be covered by transacting power with the grid.     

Hydrogen consumption minimization method based on the online identification for multi-stack PEMFCs system

The proton exchange membrane fuel cell (PEMFC) stacks are not widely used in the field of transportation industry, due to their limited power. Thus, the PEMFC stacks usually connected in parallel or series to meet the load demand power in high-power applications. The hydrogen consumption of multi-stack fuel cells (MFCs) system is related to the efficiency and output power. In addition, the efficiency of PEMFC depends on the applied voltage and other parameters. Consequently, the hydrogen consumption of system changes with varying load, because the system parameters are also varying. It makes reducing the fuel consumption of system a challenging assignment. In order to achieve the goal of minimizing fuel consumption of parallel-connected PEMFCs system, this paper proposes a novel power distribution strategy based on forgetting factor recursive least square (FFRLS) online identification. The FFRLS algorithm is based on data-driven and uses real-time data of the system to improve the estimation accuracy of PEMFC system parameters. On the test bench of parallel-connected PEMFCs system consists of two 300 W PEMFC stacks, PEMFC stack controller, DC/DC converters, and DSP controller etc., a multi-index performance test and comparative analysis are carried out. The results showed that, the performance of proposed power allocation strategy has been successfully validated. In addition, compared with the power average and daisy chain algorithms, the proposed online identification power distribution method can get more satisfactory results. Such as, reducing the hydrogen consumption and improving efficiency.     

Modeling and control of photovoltaic and fuel cell based alternative power systems

Photovoltaic (PV) systems and fuel cells (FCs) represent interesting solutions as being alternative power sources with high performance and low emission. This work presents a modeling and control study of two power generators; photovoltaic array and fuel cell based systems. An MPPT approach to optimize the PV system performances is proposed. The PV system consists of a PV array connected to a DC-DC buck converter and a resistive load. A maximum power point tracker controller is required to extract the maximum generated power. Based on Incremental Conductance (INC) principle, the idea of the proposed control is to use a Fuzzy Logic Controller (FLC) that allows the choice of the duty cycle step size which is used to be fixed in conventional MPPT algorithms. The variable step is computed according to the value of the PV power-voltage characteristic slope. The second working system comprises a controlled DC-DC converter fed by a proton exchange membrane fuel cell (PEMFC) and supplies a DC bus. The mathematical model of the PEMFC system is given. The converter duty cycle is adjusted in order to regulate the DC bus voltage. Obtained simulation results validate the control algorithms for both of studied power systems.     

Continuous bubble humidification and control of relative humidity of H2 for a PEMFC system

The proton conductivity of perfluorinated ionomer membrane used in a proton exchange membrane fuel cell (PEMFC) depends largely on the extent of hydration state of the membrane. Sufficient membrane hydration is achieved typically through the humidification of gases prior to feeding them into the fuel cell. Further, hydrogen humidification is known to have a larger impact on the performance of a PEMFC than the oxygen humidification. Bubble humidification has been a widely used method to externally humidify hydrogen. However, to-date a continuous bubble humidification system, which is essential to the continuous operation of the PEMFC system, has not been implemented. The main contributions of this work are (i) a design for continuous humidification of hydrogen for the PEMFC system and (ii) a method to maintain the RH of hydrogen between 93 and 95% (at desired temperature) over a wide range of gas flow rates. One of the key advantages of the proposed design is the flexibility of using recirculated stack coolant water to increase the energy efficiency of the PEMFC system. The design is first tested off-line and then online with a 1 kW stack. Results obtained from both the off-line and online tests indicate that the design successfully meets the demands of an online operation. It is observed that with the use of the proposed humidification scheme, the stack efficiency in terms of power output increases by about 6–19% of the power obtained under dry hydrogen conditions.     

Optimization of fuzzy-based MPPT controller via metaheuristic techniques for stand-alone PV systems

Due to the alteration of power-voltage characteristics of solar module output under multiple environmental conditions such as solar irradiation and ambient temperature, these systems hardly function at maximum power point (MPP). However, maximum power point tracking (MPPT) plays a significant role in their efficiency. On the other hand, solar module characteristics are extremely nonlinear and their slope on either side of MPP is asymmetric. Thus using a nonlinear control method which has the potential of adapting the operating point of the system to MPP seems useful. This has motivated authors to present MPPT method which maximizes PV's output power by tracking MPP continuously. In the present study, a fuzzy logic controller (FLC) is presented for MPPT in photovoltaic systems. Four optimization algorithms are presented in this paper for optimizing fuzzy membership functions (MFs) and generating proper duty cycle for MPPT. The presented algorithms include: Teaching Learning Based Optimization (TLBO), Firefly Algorithm (FFA), Biogeography based optimization (BBO), and Particle Swarm Optimization (PSO), which are all described and simulated. Finally, to validate performance of the proposed optimized FLC, it is compared with other algorithms such as symmetrical fuzzy logic controller (SFLC) and conventional Perturbation and Observation (P&O). According to the simulation results, P&O algorithm shows significant oscillations, energy loss, and in some cases, it cannot obtain MPP. Simulation results also indicate that TLBO and FFA based asymmetric fuzzy MFs not only increase MPPT convergence speed but also enhance tracking accuracy in comparison with symmetric fuzzy MFs and asymmetric fuzzy MFs based on BBO and PSO.     

Effect of flight level to maximum power utilization for PEMFC/supercapacitor hybrid uav with switched reluctance motor thruster

In this study, the performance of a fixed-wing PEMFC/SC hybrid UAV with an SRM thruster is investigated by different flight levels. Flight levels negatively affect the PEMFC due to changing ambient conditions such as air temperature and pressure. Hence, the international standard atmosphere (ISA) model for PEMFC voltage-current-power ratings is derived with 100 m intervals for 0–7500 m. The demanded electrical power by UAV increases at high altitudes due to the compressor used for air pressurization of PEMFC. Therefore, a maximum power point tracking (MPPT) model of PEMFC should be utilized in case of overshooting the maximum power level that can be provided. While the main power source of the UAV is PEMFC, the auxiliary power source is SC. The SC is preferred for DC bus voltage stabilization, avoiding maximum power point overshoot, and preventing high instantaneous current that shortens the lifespan of PEMFC. The proposed UAV model is verified at MATLAB/Simulink and the results prove that the system is satisfying.     

A novel self-tuning type-2 fuzzy maximum power point tracking technique for efficiency enhancement of fuel cell based battery chargers

Given the uncertainties associated with proton-exchange membrane fuel cell systems and relatively low efficiency of the fuel cell stacks for low-power applications, designing a high-efficiency maximum power point tracking (MPPT) controller for the fuel cell electric vehicles is an important and also technically challenging issue. For this purpose, in this article, aiming to develop a high-efficiency and low cost battery charger, a novel self-tuning type-2 fuzzy MPPT controller is presented. The main task of the controller is to provide the better performance and regulate the switching duty cycle of the used power converter under the system's uncertainty conditions in order to dynamically extract the maximum power from the fuel cell system and maintain the battery at its highest possible state of charge while protecting it from overcharging. For the sake of computational efficiency, an improved invasive weed optimization algorithm, called elitist invasive weed optimization (EIWO), is also presented to tune the type-2 fuzzy set parameters, whose improvement is demanding due to the limited human experience and knowledge. All data processing and simulations are conducted in the MATLAB software. Finally, the performance of the proposed MPPT controller is examined through using experimental tests with a prototype device.     

Improvement of proton exchange membrane fuel cell overall efficiency by integrating heat-to-electricity conversion

Proton exchange membrane fuel cells (PEMFCs) have shown to be well suited for distributed power generation due to their excellent performance. However, a PEMFC produces a considerable amount of heat in the process of electrochemical reaction. It is desirable to use thermal energy for electricity generation in addition to heating applications. Based on the operating characteristics of a PEMFC, an advanced thermal energy conversion system using “ocean thermal energy conversion” (OTEC) technology is applied to exploit the thermal energy of the PEMFC for electricity generation. Through this combination of technology, this unique PEMFC power plant not only achieves the combined heat and power efficiency, but also adequately utilizes heat to generate more valuable electricity. Exergy analysis illustrates the improvement of overall efficiency and energy flow distribution in the power plant. Analytical results show that the overall efficiency of the PEMFC is increased by 0.4-2.3% due to the thermal energy conversion (TEC) system. It is also evident that the PEMFC should operate within the optimal load range by balancing the design parameters of the PEMFC and of the TEC system.     

Design of proton exchange membrane fuel cell grid-connected system based on resonant current controller

Because of its high efficiency, low pollution and good stability, proton exchange membrane fuel cell (PEMFC) is considered as one of the most promising technologies for a wide range of applications, such as distributed power generation, transportation, portable power source and automobile. In a PEMFC grid-connected system, the proportion integration (PI) regulator can achieve zero error for the dc components in the rotating frame, but cannot achieve zero error for the ac components in the rotating frame. Hence, the PEMFC grid-connected system will produce a large number of harmonics. In order to overcome this shortcoming, a proportion integration resonant (PIR) controller is utilized to realize zero magnitude error and selective disturbance rejection. Instead of the PIR controller, a vector proportion integration (VPI) controller is designed to quickly and accurately regulate current which achieve zero both amplitude and phase frequency response at the resonant frequency simultaneously. In this paper, the PEMFC grid-connected system based on PIR and VPI controllers are developed according to the operating characteristics of a PEMFC generation system, then analyze and compare the performance of compensation harmonics between them. The total harmonic distortion (THD) of grid-connected voltage and current are measured by means of the criterion of IEEE Std1547-2003. This proposed grid-connected method will provide a novel approach for the design of advanced PEMFC grid-connected control system.     

Maximum power tracking for photovoltaic power system: Development and experimental comparison of two algorithms

This work presents an experimental comparison of two algorithms developed in order to maximize the output power from a photovoltaic (PV) system for the same given set of conditions. The maximum power point tracking (MPPT) methods proposed in this study are two extended algorithms: Perturb and Observe and Incremental Conductance. The numerical modelling of the PV system shows the MPPT interest and then the extended MPPT algorithms are highlighted. In this paper, a PV system based on a boost converter as MPPT device is considered. A programmable DC electronic load is fed by two identical PV systems in which the MPPT control converter algorithms are different. This experimental platform operates under the same conditions such as changing solar radiation and cell temperature. The experimental results obtained with a dSPACE controller board show the MPPT energy efficiency of the proposed algorithms.     

Implementation of photovoltaic array MPPT through fixed step predictive control technique

This paper proposes the implementation of Photovoltaic (PV) array Maximum Power Point Tracker (MPPT) through Fixed Step-Model Predictive Controller (FS MPC). The proposed controller scheme is based on the modified INcremental Conductance (INC) algorithm combined with the two-step horizon FS MPC. The current based INC algorithm is subject to major modifications in order to be capable of real time interaction between the MPPT and the controller obtaining sufficient information in one sampling time. The developed technique has been incorporated into a model for the overall simulation of the performance of a PV array for solar energy exploitation and is compared to the conventional approach under solar radiation variation improving PV system utilization efficiency and enabling to optimize system performance. This study also illustrates the effectiveness of the proposed controller scheme under various sky conditions with a simulation model employing real solar radiation data.     

Dynamic modelling of PEM fuel cell system for simulation and sizing of marine power systems

This article presents a model of a proton exchange membrane fuel cell (PEMFC) system for marine power systems. PEMFC in marine hybrid power sources can have various power ranges and capacities in contrast with vehicle applications. Investigating PEMFCs behaviour and performance for various conditions and configurations is demanded for proper sizing and feasibility studies. Hence, modelling and simulation facilitate understanding the performance of the PEMFC behaviour with various sizes and configurations in power systems. The developed model in this work has a system level fidelity with real time capabilities, which can be utilized for simulator approaches besides quasi-static studies with a power-efficiency curve. Moreover, the model can be used for scaling the PEMFC power range by considering transient responses and corresponding efficiencies. The Bond graph approach as a multi-disciplinary energy based modelling strategy is employed for the PEMFC as a multi domains system. In the end, various PEMFC cell numbers and compressor sizes have been compared with power-efficiency curves and transient responses in a benchmark.     

Polar coordinated fuzzy controller based real-time maximum-power point control of photovoltaic system

It is crucial to improve the photovoltaic (PV) system efficiency and to develop the reliability of PV generation control systems. There are two ways to increase the efficiency of PV power generation system. The first is to develop materials offering high conversion efficiency at low cost. The second is to operate PV systems optimally. However, the PV system can be optimally operated only at a specific output voltage and its output power fluctuates under intermittent weather conditions. Moreover, it is very difficult to test the performance of a maximum-power point tracking (MPPT) controller under the same weather condition during the development process and also the field testing is costly and time consuming. This paper presents a novel real-time simulation technique of PV generation system by using dSPACE real-time interface system. The proposed system includes Artificial Neural Network (ANN) and fuzzy logic controller scheme using polar information. This type of fuzzy logic rules is implemented for the first time to operate the PV module at optimum operating point. ANN is utilized to determine the optimum operating voltage for monocrystalline silicon, thin-film cadmium telluride and triple junction amorphous silicon solar cells. The verification of availability and stability of the proposed system through the real-time simulator shows that the proposed system can respond accurately for different scenarios and different solar cell technologies.     

An on-line MPPT algorithm for rapidly changing illuminations of solar arrays

Maximum power point tracking (MPPT) is usually used for a solar power system. Many maximum power tracking techniques have been considered in the past. The microprocessors with appropriate MPPT algorithms are favored because of their flexibility and compatibility with different solar arrays. Although the efficiency of MPPT algorithms is usually high, it drops noticeably in case of rapidly changing illumination conditions. The authors have proposed an improved MPPT algorithm based on the fact that the maximum power point (MPP) of solar arrays can be tracked accurately. The principle of energy conservation is used to develop the large- and small-signal model and transfer function for the solar power system. The work was carried out by both simulation and experiment on a current converter, by the digital signal processor (DSP) control, in MPPT mode under different illuminations. The results show that the proposed MPPT algorithm has successfully tracked the MPP in rapidly changing illumination conditions.     

A comparative study of maximum power point tracking methods for a photovoltaic-based water pumping system

In this paper the performance of the proposed fuzzy-based maximum power point tracking (MPPT) is investigated and compared with incremental conductance and constant voltage controller for a photovoltaic (PV) pumping system. A fuzzy logic controller with a mamdani inference engine using only nine rules is designed to track the optimum power point. An induction motor has been used to drive the centrifugal pump. The system performance is analysed for different weather conditions. A detailed comparative study presenting the merits and demerits of each technique is also presented in order to develop a relative relationship. Simulation results obtained indicate better performance of the fuzzy-based MPPT algorithm for the PV pumping system.     

Model-based decoupling control for the thermal management system of proton exchange membrane fuel cells

As one of the most promising sustainable energy technologies available today, proton exchange membrane fuel cell (PEMFC) engines are becoming more and more popular in various applications, especially in transportation vehicles. However, the complexity and the severity of the vehicle operating conditions present challenges to control the temperature distribution in single cells and stack, which is an important factor influencing the performance and durability of PEMFC engines. It has been found that regulating the input and output coolant water temperature can improve the temperature distribution. Therefore, the control objective in this paper is regulating the input and output temperature of coolant water at the same time. Firstly, a coupled model of the thermal management system is established based on the physical structure of PEMFC engines. Then, in order to realize the simultaneous control of the inlet and outlet cooling water temperature of the PEMFC stack, a decoupling controller is proposed and its closed-loop stability is proved. Finally, based on the actual PEMFC engine platform, the effectiveness, accuracy and reliability of the proposed decoupling controller are tested. The experimental results show that with the proposed decoupling controller, the inlet and outlet temperatures of the PEMFC stack cooling water can be accurately controlled on-line. The temperature error range is less than 0.2 °C even under the dynamic current load conditions.