基于fuzzy-PI双模控制的光伏发电系统最大功率点跟踪仿真研究

为了提高太阳电池阵列的工作效率和整个光伏发电系统的稳定性,在光伏发电系统中需要对光伏电池的最大功率点进行跟踪。为了消除常规模糊跟踪算法在最大功率点附近出现的振荡问题,在分析光伏电池伏安特性的基础上,提出了fuzzy-PI双模控制策略,分析了该控制算法的原理,并对控制系统做了设计。Matlab/Simulink仿真表明fuzzy-PI双模控制能够快速、准确地跟踪最大功率点,避免了最大功率点处的振荡,提高了系统稳定性和能量转换效率,从而使整个双模控制兼有了MPPT精确性与快速性。     

Enhancing the operation of fuel cell-photovoltaic-battery-supercapacitor renewable system through a hybrid energy management strategy

It is necessary to have an energy management system based on one or more control strategies to sense, monitor, and control the behavior of the hybrid energy sources. In renewable hybrid power systems containing fuel cells and batteries, the hydrogen consumption reduction and battery state of charge (SOC) utilizing are the main objectives. These parameters are essential to get the maximum befits of cost reduction as well as battery and hydrogen storage lifetime increasing. In this paper, a novel hybrid energy management system (HEMS) was designed to achieve these objectives. A renewable hybrid power system combines: PV, PEMFC, SC, and Battery was designed to supply a predetermined load with its needed power. This (REHPS) depends on the PV power as a master source during the daylight. It uses the FC to support as a secondary source in the night or shading time. The battery is helping the FC when the load power is high. The supercapacitor (SC) is working at the load transient or load fast change. The proposed energy management system uses fuzzy logic and frequency decoupling and state machine control strategies working together as a hybrid strategy where the switching over between both strategies done automatically based on predetermined values to obtain the minimum value of hydrogen consumption and the maximum value of SOC at the same time. The proposed HEMS achieves 19.6% Hydrogen consumption saving and 5.4% increase in SOC value compared to the results of the same two strategies when working as a stand-alone. The load is designed to show a surplus power when the PV power is at its maximum value. This surplus power is used to charge the battery. To validate the system, the results were compared with the results of each strategy if working separately. The comparison confirms the achievement of the hybrid energy management system goal.     

Experimental study of energy management of FC/SC hybrid system using the Passivity Based Control

Nowadays, the energy management of the hybrid system is becoming an interesting and the challenging topic for several researchers. The wise choice of the energy management strategy allows not only the best distribution of power between different sources but also reduce system consumption, increase the lifetime of the used sources and ensure the energy demand that involve the autonomy of the electrical vehicle. In this paper, the control and the energy management using the passivity control is adopted to the multiconverters multisources system, in particularly, Fuel Cell/SuperCapacitor (FC/SC) hybrid system. In the proposed system, the FC represents the main source and the SC is used for the transient of power where they can absorb or supply powers peaks. The proposed system is validated by experimental results. The obtained results prove the efficacy and the feasibility of the proposed approach for a real electrical vehicle.     

A fuel-cell/battery hybrid DC backup power system via a new high step-up three port converter

In this paper, a fuel-cell (FC)/battery hybrid direct-current (DC) backup power system is proposed for high step-up applications. This system is composed of a newly developed non-isolated three-port converter, which achieves a high voltage gain by taking the advantage of a quasi Z-source network and an energy transfer capacitor. After analyzing the converter, a comprehensive comparison study and a design procedure are provided. Moreover, the controllers regulating the source power levels while smoothing the FC power profile according to the proposed energy management strategy (EMS) are designed based on the developed small-signal model of the proposed converter. Both hardware and controller design procedures are validated through the PSIM model of the whole system. As a result, it is shown that the proposed system can effectively couple FC and battery while transferring their energies to a high voltage DC bus according to the offered EMS.     

Techno-economic study of off-grid hybrid photovoltaic/battery and photovoltaic/battery/fuel cell power systems in Kunming,China

The objective of this study is to evaluate the technical and economic feasibility of stand-alone hybrid photovoltaic (PV)/battery and PV/battery/fuel cell (FC) power systems for a community center comprising 100 households in Kunming by using the Hybrid Optimization Model for Electric Renewable (HOMER) software. HOMER is used to define the optimum sizing and techno-economic feasibility of the system equipment based on the geographical and meteorological data of the study region. In this study, different hybrid power systems are analyzed to select the optimum energy system while considering total net present cost (NPC) and levelized cost of energy (COE). The results showed that the optimal hybrid PV/battery system comprised 500 kW PV modules, 1200 7.6-kWh battery units, and 500 kW power converters. The proposed system has an initial cost of $6,670,000, an annual operating cost of $82,763/yr, a total NPC of $7,727,992, and a levelized COE of $1.536/kWh. While the PV/battery/FC power system is possible, the cost increases were due to the investment cost of the FC system. The optimal PV/battery/FC system has an initial cost of $6,763,000, an annual operating cost of $82,312/yr, a total NPC of $7,815,223, and a levelized COE of $1.553/kWh.     

Optimal energy management system for stand-alone wind turbine/photovoltaic/hydrogen/battery hybrid system with supervisory control based on fuzzy logic

This paper presents a novel hourly energy management system (EMS) for a stand-alone hybrid renewable energy system (HRES). The HRES is composed of a wind turbine (WT) and photovoltaic (PV) solar panels as primary energy sources, and two energy storage systems (ESS), which are a hydrogen subsystem and a battery. The WT and PV panels are made to work at maximum power point, whereas the battery and the hydrogen subsystem, which is composed of fuel cell (FC), electrolyzer and hydrogen storage tank, act as support and storage system. The EMS uses a fuzzy logic control to satisfy the energy demanded by the load and maintain the state-of-charge (SOC) of the battery and the hydrogen tank level between certain target margins, while trying to optimize the utilization cost and lifetime of the ESS. Commercial available components and an expected life of the HRES of 25 years were considered in this study. Simulation results show that the proposed control meets the objectives established for the EMS of the HRES, and achieves a total cost saving of 13% over other simpler EMS based on control states presented in this paper.     

Experimental investigation of power management and control of a PV/wind/fuel cell/battery hybrid energy system microgrid

This paper presents an experimental study of a standalone hybrid microgrid system. The latter is dedicated to remote area applications. The system is a compound that utilizes renewable sources that are Wind Generator (WG), Solar Array (SA), Fuel Cell (FC) and Energy Storage System (ESS) using a battery. The power electronic converters play a very important role in the system; they optimize the control and energy management techniques of the various sources. For wind and solar subsystem, the speed and Single Input Fuzzy Logic (SIFL) controllers are used respectively to harvest the maximum power point tracking (MPPT). To maintain a balance of energy in the hybrid system, an energy management strategy based on the battery state of charge (SOC) has been developed and implemented experimentally. The AC output voltage regulation was achieved using a Proportional Integral (PI) controller to supply a resistive load with constant amplitude and frequency. According to the obtained performances, it was concluded that the proposed system is very promising for potential applications in hybrid renewable energy management systems.     

A coupled power-voltage equilibrium strategy based on droop control for fuel cell/battery/supercapacitor hybrid tramway

In order to improve the robustness of the energy management system (EMS) and avoid the influence of demand power on the design of EMS, a coupled power-voltage equilibrium strategy based on droop control (CPVE-DC) is proposed in this paper. Making use of the principal that the DC bus can directly reflect the changes of load power, the proposed strategy couples DC bus voltage with output powers through droop control to achieve self-equilibrium. The proposed EMS is applied into a hybrid tramway model configured with multiple proton exchange membrane fuel cell (PEMFC) systems, batteries and super capacitors (SCs). FC systems and SC systems are responsible for satisfying most of the demand power, therefore the CPVE-DC strategy generates FCs and SCs reference power through power-voltage droop control on the primary control. Then batteries supplement the rest part of load power and generate DC bus voltage reference value of the next sampling time. With the gambling between output power and DC bus voltage, the hybrid system achieves self-equilibrium and steps into steady operation by selecting appropriate droop coefficients. Then the secondary control of the proposed strategy allocates power between every single unit. In addition, a penalty coefficient is introduced to balance SOC of SCs. The proposed strategy is tested under a real drive cycle LF-LRV on RT-LAB platform. The results demonstrate that the proposed strategy can achieve self-equilibrium and is effective to allocate demand power among these power sources,achieve active control for the range of DC bus voltage and SOC consensus of SCs as well. In addition, some faults are simulated to verify the robustness of the proposed strategy and it turns out that the CPVE-DC strategy possesses higher robustness. Finally, the CPVE-DC strategy is compared with equivalent consumption minimization strategy (ECMS) and the results shows that the proposed strategy is able to get higher average efficiency and lower equivalent fuel consumption.     

Modeling,optimization and control of a FC/battery hybrid locomotive based on ADVISOR

This paper presents a hybrid locomotive system which combines proton exchange membrane fuel cell (PEMFC) as primary energy source for its advantages of high efficiency and low emissions, and Pb acid battery as secondary energy storage (ESS) to supplement the output of FC during acceleration or whenever else needed and to absorb regenerative energy during braking. Advanced Vehicle Simulator (ADVISOR), a vehicle simulating software, is secondly developed in this paper for the locomotive modeling and simulation. An analysis of simulation is conducted to verify the effectiveness of the proposed model. Then the power of FC, battery and motor are optimized by adopting bisection algorithm under certain constraints. It is confirmed that the dynamic performance and economy performance are improved after optimization. An advanced energy management system is extremely necessary to contribute the demand power of locomotive between energy sources in a suitable way, therefore a fuzzy logic based control strategy is proposed for the hybrid locomotive. With advantages of easy understanding, flexibility and capability to deal with imprecise data, fuzzy logic methodology is suitable for the control of hybrid locomotive. The simulation results demonstrate the superiority of fuzzy logic energy management system in terms of dynamic and economy performance.     

Demonstration and assessment of dynamic performance of a hybrid power system based electric passenger cart

Fuel cell (FC) technology is showing excellent promise for many applications ranging from portable devices to vehicular systems. A stand-alone FC may not always satisfy the fast and transient load demands of a vehicular power system. As a result, FC units are usually hybridized with supplementary sources to meet the total power demand of the vehicle. In this paper, the energy demands of a light vehicle (a passenger cart) is developed using a hybrid power supply system involving a photovoltaic (PV) panel, a proton exchange membrane fuel cell (PEMFC) and a battery based energy storage system (ESS). In addition, the details of the physical construction of the modified hybrid cart are given. The most critical feature of an energy management strategy for a multiple-source based hybrid vehicle is the sharing of fast and transient load demands among the available power sources. For this purpose, a 300-s drive cycle is created in this paper to test the effectiveness of the load sharing strategy between FC, battery pack and PV panel. It is found that PEMFC dominates slow and moderate dynamic behaviors of the vehicle, while fast response of the battery group governs the rapid dynamic behaviors. The results also show that the integrating PV panel contributes noticeably to the dynamic behaviors of the system. Furthermore, a control-oriented simulation model for a PEMFC unit is verified with experimental data to test the success of the proposed technique.     

Observer-based type-2 fuzzy approach for robust control and energy management strategy of hybrid energy storage systems

In this paper, an observer-based type-2 fuzzy method is proposed for control and energy management strategy (EMS) of the hybrid energy storage system (HESS) which can be composed of the fuel cell (FC), battery (BA), and supercapacitor (SC). The objective and main contribution of the suggested strategy is to provide: 1) Appropriate tracking performance of power sources by an observer-based control method in the presence of noise and signal ripples. 2) An observer-based composite adaptive type-2 fuzzy (OCAT2F) to approximate the voltage of power sources. 3) A dynamical model of DC-bus to guarantee the stability of closed-loop system. 4) An intelligent EMS. To have a high-power supply, the proposed EMS includes two parts; a type-2 fuzzy logic control rule table (T2FLCRT), and an observer-based robust adaptive fuzzy type-2 fuzzy (ORAT2F). Furthermore, stability analyses of the closed-loop system are provided by the input-output linearization (I-OL) approach and based on the Lyapunov theorem. The simulation results of the proposed control scheme under MATLAB/Simulink indicate that the suggested strategy can provide a suitable control performance, and stability of the whole system is achieved.     

Modeling,control and simulation of a photovoltaic /hydrogen/ supercapacitor hybrid power generation system for grid-connected applications

Hybrid renewable energy systems (HRES) should be designed appropriately with an adequate combination of different renewable sources and various energy storage methods to overcome the problem of intermittency of renewable energy resources. Focusing on the inevitable impact on the grid caused by strong randomicity and apparent intermittency of photovoltaic (PV) generation system, modeling and control strategy of pure green and grid-friendly hybrid power generation system based on hydrogen energy storage and supercapacitor (SC) is proposed in this paper. Aiming at smoothing grid-connected power fluctuations of PV and meeting load demand, the alkaline electrolyzer (AE) and proton exchange membrane fuel cell (PEMFC) and SC are connected to DC bus of photovoltaic grid-connected generation system. Through coordinated control and power management of PV, AE, PEMFC and SC, hybrid power generation system friendliness and active grid-connection are realized. The validity and correctness of modeling and control strategies referred in this paper are verified through simulation results based on PSCAD/EMTDC software platform.     

Maximum photovoltaic power tracking for the PV array using the fractional-order incremental conductance method

This paper proposes maximum photovoltaic power tracking (MPPT) for the photovoltaic (PV) array using the fractional-order incremental conductance method (FOICM). Since the PV array has low conversion efficiency, and the output power of PV array depends on the operation environments, such as various solar radiation, environment temperature, and weather conditions. Maximum charging power can be increased to a battery using a MPPT algorithm. The energy conversion of the absorbed solar light and cell temperature is directly transferred to the semiconductor, but electricity conduction has anomalous diffusion phenomena in inhomogeneous material. FOICM can provide a dynamic mathematical model to describe non-linear characteristics. The fractional-order incremental change as dynamic variable is used to adjust the PV array voltage toward the maximum power point. For a small-scale PV conversion system, the proposed method is validated by simulation with different operation environments. Compared with traditional methods, experimental results demonstrate the short tracking time and the practicality in MPPT of PV array.     

基于模糊自适应PI控制的光伏发电MPPT

介绍了光伏发电过程中最大功率点跟踪(MPPT)原理,并简要分析了常规控制算法在最大功率跟踪控制中的优缺点,提出将模糊自适应PI控制算法应用到光伏系统最大功率点跟踪的控制中,该控制方法能快速响应外界环境的变化,获得系统最大功率点,且可以有效消除系统在最大功率点附近的振荡现象,提高系统的稳定性。仿真结果表明,该方法能使系统稳定地工作在最大功率点,并且控制精度高,能灵敏反应外界环境的变化。     

An improved energy management strategy for FC/UC hybrid electric vehicles propelled by motor-wheels

The hybridization of the fuel-cell electric-vehicle (FCEV) by a second energy source has the advantage of improving the system's dynamic response and efficiency. Indeed, an ultra-capacitor (UC) system used as an energy storage device fulfills the FC slowest dynamics during fast power transitions and recovers the braking energy. In FC/UC hybrid vehicles, the search for a suitable power management approach is one of the main objectives. In this paper, an improved control strategy managing the active power distribution between the two energy sources is proposed. The UC reference power is calculated through the DC link voltage regulation. For the FC power demand, an algorithm with five operating modes is developed. This algorithm, depending on the UC state of charge (SOC) and the vehicle speed level, minimizes the FC power demand transitions and therefore ameliorates its durability. The traction power is provided using two permanent magnetic synchronous motor-wheels to free more space in the vehicle. The models of the FC/UC vehicle system parts and the control strategy are developed using MATLAB software. Simulation results show the effectiveness of the proposed energy management strategy.     

Energy management strategy of Supercapacitor/Fuel Cell energy storage devices for vehicle applications

This paper addresses the management of a Fuel Cell (FC) – Supercapacitor (SC) hybrid power source for Electric Vehicle (EV) applications. The FC presents the main energy source and it is sustained with SCs energy storages in order to increase the FC source lifespan by mitigating harmful current transients. For this aim, the reported work proposes a Grey Wolf Optimizer (GWO) for an efficient power management of the studied hybrid power system. The key idea of the proposed approach is to incorporate the benefit of the GWO in terms of fast optimization and convergence accuracy, in order to achieve efficient energy sources exploitation and provide the desired driving performances. Simulations and experimental results verify the validity of the proposed management algorithm.     

Optimized rule-based energy management for a polymer electrolyte membrane fuel cell/battery hybrid power system using a genetic algorithm

The polymer electrolyte membrane fuel cell (PEMFC) coupled with the battery is a promising hybrid power system for future energy supply application. Fuel cell durability, battery charge sustenance, and fuel consumption strongly rely on the energy management strategy (EMS). This paper puts forward an optimized rule-based EMS using genetic algorithm (GA) to optimally allocate the power between the fuel cell and the battery system. Control variables in real-time rule-based EMS are optimally adjusted with single objective of battery charge sustenance considering the fuel cell durability and efficiency. The proposed optimized rule-based EMS is simulated and experimentally verified via MATLAB/Simulink and LabVIEW-based experimental rig, respectively. The conventional rule-based EMS, fuzzy logic EMS, and dynamic programming (DP) EMS are also examined for comparison. The comparison results elucidate that the optimized rule-based EMS realizes a large performance improvement over the conventional rule-based and fuzzy logic EMSs. Near optimal performance is verified compared with DP EMS in terms of fuel economy, battery charge sustenance, fuel cell efficiency, and system durability. The combination of rule-based EMS and GA optimization algorithm has the advantage of having expert experience and global optimization properties, realizing optimal power allocation in real-time application with lower computation burden, which could be applied easily to other EMS system without loss of validity.     

Enhanced control strategies for a hybrid battery/photovoltaic system using FGS-PID in grid-connected mode

This paper suggests improved control strategies using Fuzzy Gain Scheduling of Proportional-Integral-Derivative (FGS-PID) controller for a hybrid Photovoltaic (PV) and Battery Energy Storage (BES) system under different weather conditions. The proposed scheme is implemented using a two-level control system structure, combining the benefits of the PID as well as the fuzzy logic controller (FLC) for maximum power point tracking (MPPT). Ziegler-Nichols tuning method is also employed to select the initial values of PID gains. Within the period of steady-states and transients, FGS-PID adopts the gains to ensure the stability of the control scheme. It also damps out transient fluctuations and reduces settling time. Also, BES could be employed to provide a stable and reliable power from the output of PV sources to loads. It can enhance the performance of the entire power system during the grid-connected mode. The simulation results under Matlab/Simulink show that the suggested control strategies are robustness, fast transient response and proper steady-state performance in the grid-connected mode in comparison other presented methods.     

Comparative study of artificial intelligence techniques for sizing of a hydrogen-based stand-alone photovoltaic/wind hybrid system

As non-polluting reliable energy sources, stand-alone photovoltaic/wind/fuel cell (PV/wind/FC) hybrid systems are being studied from various aspects in recent years. In such systems, optimum sizing is the main issue for having a cost-effective system. This paper evaluates the performance of different artificial intelligence (AI) techniques for optimum sizing of a PV/wind/FC hybrid system to continuously satisfy the load demand with the minimal total annual cost. For this aim, the sizing problem is formulated and four well-known heuristic algorithms, namely, particle swarm optimization (PSO), tabu search (TS), simulated annealing (SA), and harmony search (HS), are applied to the system and the results are compared in terms of the total annual cost. It can be seen that not only average results produced by PSO are more promising than those of the other algorithms but also PSO has the most robustness. As another investigation, the sizing is also performed for a PV/wind/battery hybrid system and the results are compared with those of the PV/wind/FC system.     

A hierarchical energy management strategy for fuel cell/battery/supercapacitor hybrid electric vehicles

In this paper, a hierarchical energy management strategy (EMS) based on low-pass filter and equivalent consumption minimization strategy (ECMS) is proposed in order to lift energy sources lifespan, power performance and fuel economy for hybrid electrical vehicles equipped with fuel cell, battery and supercapacitor. As for the considered powertrain configuration, fuel cell serves as main energy source, and battery and supercapacitor are regarded as energy support and storage system. Supercapacitor with high power density and dynamic response acts during great power fluctuations, which relives stress on fuel cell and battery. Meanwhile, battery is used to lift the economy of hydrogen fuel. In higher layer strategy of the proposed EMS, supercapacitor is employed to supply peak power and recycle braking energy by using the adaptive low-pass filter method. Meantime, an ECMS is designed to allocate power of fuel cell and battery such that fuel cell can work in a high efficient range to minimize hydrogen consumption in lower layer. The proposed EMS for hybrid electrical vehicles is modeled and verified by advisor-simulink and experiment bench. Simulation and experiment results are given to confirm effectiveness of the proposed EMS of this paper.