A new approach of sizing battery energy storage system for smoothing the power fluctuations of a PV/wind hybrid system

In this paper, a new approach for optimally sizing the storage system employing the battery banks for the suppression of the output power fluctuations generated in the hybrid photovoltaic/wind hybrid energy system. At first, a novel multiple averaging technique has been used to find the smoothing power that has to be supplied by the batteries for the different levels of smoothing of output power. Then the battery energy storage system is optimally sized using particle swarm optimization according to the level of smoothing power requirement, with the constraints of maintaining the battery state of charge and keeping the energy loss within the acceptable limits. Two different case studies have been presented for different locations and different sizes of the hybrid systems in this work. The results of the simulation studies and detailed discussions are presented at the end to portrait the effectiveness of the proposed method for sizing of the battery energy storage system. Copyright © 2016 John Wiley & Sons, Ltd.     

超级电容器-蓄电池应用于独立光伏系统的储能设计

建立了混合储能系统的数学模型,对模型系统进行了稳定性分析,从应用角度出发,设计了一套超级电容器-蓄电池混合储能装置应用在独立光伏系统,使用PSPICE软件仿真分析了系统的运行特性,结果表明系统在光伏输入功率大幅波动以及负载突变时具有很好的稳定性,可为超级电容器应用于可再生能源发电和电能质量改善等领域提供较好的参考。     

Power management system for a fuel cell/battery hybrid vehicle incorporating fuel cell and battery degradation

Optimization of fuel cell/battery hybrid vehicle systems has primarily focused on reducing fuel consumption. However, it is also necessary to focus on fuel cell and battery durability as inadequate lifespan is still a major barrier to the commercialization of fuel cell vehicles. Here, we introduce a power management strategy which concurrently accounts for fuel consumption as well as fuel cell and battery degradation. Fuel cell degradation is quantified using a simplified electrochemical model which provides an analytical solution for the decay of the electrochemical surface area (ECSA) in the fuel cell by accounting for the performance loss due to transient power load, start/stop cycles, idling and high power load. The results show that the performance loss based on remaining ECSA matches well with test data in the literature. A validated empirical model is used to relate Lithium-ion battery capacity decay to C-rate. Simulations are then conducted using a typical bus drive cycle to optimize the fuel cell/battery hybrid system. We demonstrate that including these degradation models in the objective function can effectively extend the lifetime of the fuel cell at the expense of higher battery capacity decay resulting in a lower average running cost over the lifetime of the vehicle.     

Model construction and energy management system of lithium battery,PV generator,hydrogen production unit and fuel cell in islanded AC microgrid

The external electrical characteristics of the lithium battery, PV generator, hydrogen production unit (HPU) and fuel cell in islanded AC microgrid are well analyzed with mathematic models, based on which an energy management system among the abovementioned elements is proposed by using the bus frequency signaling. Specifically, the functions of lithium battery with the variables of the residual capacity and instantaneous working power are well designed to deliver its operation information to other units. The P-f droop control strategy is designed for the PV generator to make it adaptively work off from the maximum power point to the reference power point. The control strategy of HPU can make it work from the maximum efficiency point mode to the allowable maximum power point mode to absorb PV output power as much as possible when the lithium battery is almost getting full charged. Similarly, the fuel cell controller can regulate its power generation from the maximum efficiency point mode to the maximum power point to supply the local load as much as possible when the lithium battery is almost getting full discharged. Finally, the proposed energy management system is verified based on RTLAB experimental platform to show the effectiveness of the proposed coordination control strategy.     

Improved fuzzy logic control-based energy management strategy for hybrid power system of FC/PV/battery/SC on tourist ship

An improved fuzzy-based energy management strategy (EMS) is proposed for a tourist ship used hybrid power system with multiple power sources consisting of fuel cell(FC)/photovoltaic cell(PV)/battery(BAT)/super-capacitor(SC). The power demand from propeller and user terminal is afforded by the power sources connecting to power converters. To obtain more superior performance of the power system, the maximum power point tracking (MPPT) algorithm is employed to optimize the PV. Meanwhile, the improved fuzzy logic control based on dynamic programming (DP) associated with wavelet analysis and PI control are employed to achieve the output power optimal distribution and online control. In particular, the MPPT algorithm can improve the utilization of solar energy, and the SC can well absorb the high frequency power and reduce the fluctuation of the battery and FC that exhibits the potential of their lifetime extension. The FC outputs the high and stable power satisfying the ship's power demand even under the extreme work conditions. The developed model is able to illustrate well in the operation process of the hybrid power system governed by the proposed EMS. In addition, compared with the rule-based strategy, the improved fuzzy-based EMS can reduce 14.39% hydrogen consumption and keep the consistency of battery SOC.     

Multi-objective optimization of hybrid PEMFC/Li-ion battery propulsion systems for small and medium size ferries

Hybrid Polymer Electrolyte Membrane Fuel Cells/Lithium-ion battery powertrains are a promising solution for zero-local-emissions marine propulsion. The present study aims to optimize the design and operation of such hybrid powertrain for small-size passenger ferries, taking into account the performance degradation of both fuel cells and batteries. A Mixed-Integer Linear-Programming approach and a hierarchical method are adopted to concurrently minimize the fuel cells degradation, the capital expenditure and the operating expenditure, while constraints are included in the model to limit the battery degradation. The results show that the proposed multi-objective optimization can lead to a reduction of fuel cells degradation by up to 65% compared to a cost-minimization only. However, this can imply an increase in the battery capacity by up to 136%. The proposed method has general validity, and it is a useful tool for both preliminary design and choice of the optimal energy management strategy for ships energy systems.     

Long-term optimization based on PSO of a grid-connected renewable energy/battery/hydrogen hybrid system

This paper presents and evaluates three energy management systems (EMSs) based on Particle Swarm Optimization (PSO) for long-term operation optimization of a grid-connected hybrid system. It is composed of wind turbine (WT) and photovoltaic (PV) panels as primary energy sources, and hydrogen system (fuel cell –FC–, electrolyzer and hydrogen storage tank) and battery as energy storage system (ESS). The EMSs are responsible for making the hybrid system produce the demanded power, deciding on the energy dispatch among the ESS devices. The first PSO-based EMS tries to minimize the ESS utilization costs, the second one to maximize the ESS efficiency, and the third one to optimize the lifetime of the ESS devices. Long-term simulations of 25 years (expected lifetime of the hybrid system) are shown in order to demonstrate the right performance of the three EMSs and their differences. The simulations show that: 1) each EMS outperforms the others in the designed target; and 2) the third EMS is considered the best EMS, because it needs the least ESS devices, and presents the lowest total acquisition cost of hybrid system, whereas the rest of parameters are similar to the best values obtained by the other EMSs.     

Control design and power management of a stationary PEMFC hybrid power system

This paper develops robust control and power management strategies for a 6 kW stationary proton exchange membrane fuel cell (PEMFC) hybrid power system. The system consists of two 3 kW PEMFC modules, a Li–Fe battery set, and electrical components to form a parallel hybrid power system that is designed to supply uninterruptible power to telecom base stations during power outages. The study comprises three parts: PEMFC control, power management, and system integration. First, we apply robust control to regulate the hydrogen flow rates of the PEMFC modules in order to improve system stability, performance, and efficiency. Second, we design a parallel power train that consists of two PEMFC modules and one Li–Fe battery set for the uninterruptible power supply (UPS) requirement. Lastly, we integrate the system for experimental verification. Based on the results, the proposed robust control and power management are deemed effective at improving the stability, performance, and efficiency of the stationary power system.     

Analysis of a solar PV/battery/DG set-based hybrid system for a typical telecom load: a case study

This paper analyses the technical and economic feasibility of using a hybrid renewable energy source for a typical telecom load in the state of Qatar. The hybrid system considered in this work consists of a solar photovoltaic with storage battery and diesel generator set. For this particular hybrid system, the meteorological data of solar irradiance in Doha city (latitude 25.15 ° North and longitude 51.33 ° East) are taken from NASA surface meteorology and solar energy websites. The solar irradiance in Doha is 5.33?kWh/m²/day on an annual average scale. The data are also taken through the study of load consumption of Qatar telecommunication hybrid power system. The system is designed and its techno-economic analysis is carried out using the Hybrid Optimization Model for Electrical Renewable software. The results show both technical and economic viability of replacing the conventional DG sets with the proposed renewable energy source.     

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.     

Sizing optimization,dynamic modeling and energy management strategies of a stand-alone PV/hydrogen/battery-based hybrid system

This paper presents a sizing method and different control strategies for the suitable energy management of a stand-alone hybrid system based on photovoltaic (PV) solar panels, hydrogen subsystem and battery. The battery and hydrogen subsystem, which is composed of fuel cell (FC), electrolyzer and hydrogen storage tank, act as energy storage and support system. In order to efficiently utilize the energy sources integrated in the hybrid system, an appropriate sizing is necessary. In this paper, a new sizing method based on Simulink Design Optimization (SDO) of MATLAB was used to perform a technical optimization of the hybrid system components. An analysis cost has been also performed, in that the configuration under study has been compared with those integrating only batteries and only hydrogen system. The dynamic model of the designed hybrid system is detailed in this paper. The models, implemented in MATLAB-Simulink environment, have been designed from commercially available components. Three control strategies based on operating modes and combining technical-economic aspects are considered for the energy management of the hybrid system. They have been designed, primarily, to satisfy the load power demand and, secondarily, to maintain a certain level at the hydrogen tank (hydrogen energy reserve), and at the state of charge (SOC) of the battery bank to extend its life, taking into account also technical-economic analysis. Dynamic simulations were performed to evaluate the configuration, sizing and control strategies for the energy management of the hybrid system under study in this work. Simulation results show that the proposed hybrid system with the presented controls is able to provide the energy demanded by the loads, while maintaining a certain energy reserve in the storage sources.     

Design and simulation of the PV/PEM fuel cell based hybrid energy system using MATLAB/Simulink for greenhouse application

In this study, design and optimization of the hybrid renewable energy system consisting of Photovoltaic (PV)/Electrolyzer/Proton Exchange Membrane Fuel Cell (PEMFC) was investigated to provide electricity and heat for Greenhouse in ?anl?urfa (Turkey). The coupling of a photovoltaic system with PEMFC was preferred to supply continuous production of electric energy throughout the year. Additionally, produced heat from PEMFC was used to heating of the greenhouse by micro cogeneration application. The MATLAB/Simulink was applied to the design and optimization of the proposed hybrid system. In the designed system, solar energy was selected to produce the Hydrogen (H₂) required to run the electrolyzer. In cases where the solar energy is not sufficient and cannot meet the electricity requirement for the electrolyzer; the H₂ requirement for the operation of the PEMFC was met from the H₂ storage tanks and energy continuity was ensured. The electrolyzer was designed for H₂ demand of the 3 kW PEMFC which were met the greenhouse energy requirement. PEMFC based hybrid system has 48% electrical and 45% thermal efficiencies. According to optimization results obtained for the proposed hybrid system, the levelized cost of energy was found 0.117 $/kWh. The obtained results show the proposed PV/Electrolyzer/PEMFC hybrid power system provides an applicable option for powering stand-alone application in a self-sustainable expedient.     

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.     

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.     

Online management of lithium-ion battery based on time-triggered controller area network for fuel-cell hybrid vehicle applications

This paper introduces a state of charge (SOC) estimation algorithm that was implemented for an automotive lithium-ion battery system used in fuel-cell hybrid vehicles (FCHVs). The proposed online control strategy for the lithium-ion battery, based on the Ah current integration method and time-triggered controller area network (TTCAN), incorporates a signal filter and adaptive modifying concepts to estimate the Li₂MnO₄ battery SOC in a timely manner. To verify the effectiveness of the proposed control algorithm, road test experimentation was conducted with an FCHV using the proposed SOC estimation algorithm. It was confirmed that the control technique can be used to effectively manage the lithium-ion battery and conveniently estimate the SOC.     

Modeling of hydrogen and electrical energy storages in wind/PV energy system on the Lake Baikal coast

The paper presents a research on a green power supply system (producing no carbon dioxide and other harmful emissions) in the area of Baikal Lake, for the maximum loads of 10 kW and 100 kW. The system includes photovoltaic converters, wind turbines, batteries for electric energy storage and a system for hydrogen production, storage and energy use. Calculations based on the optimization mathematical model demonstrated the efficiency of the combined use of wind and solar energy in the considered areas, as well as the simultaneous storage of electric energy and hydrogen. The electric energy storage is most efficient for short-term time intervals whereas an increase in the duration of continuous energy “standstills” up to several days makes the storage of hydrogen more cost-effective.     

An energy management strategy based on dynamic power factor for fuel cell/battery hybrid locomotive

In order to efficiently absorb more regenerative braking energy which sustains much longer compared with the conventional vehicle, and guarantee the safety of the hybrid system under the actual driving cycle of locomotive, an energy management control based on dynamic factor strategy is proposed for a scale-down locomotive system which consists of proton exchange membrane fuel cell (PEMFC) and battery pack. The proposed strategy which has self-adaption function for different driving cycles aims to achieve the less consumption of hydrogen and higher efficiency of the hybrid system. The experimental results demonstrate that the proposed strategy is able to maintain the charge state of battery (SOC) better than Equivalent Consumption Minimization Strategy (ECMS), and the proposed strategy could keep the change trend of SOC, which the final SOC is closed to the target value regardless of the initial SOC of battery. Moreover, the hydrogen consumption has been reduced by 0.86g and the efficiency of overall system has been raised of 2% at least than ECMS under the actual driving cycle through the proposed strategy. Therefore, the proposed strategy could improve the efficiency of system by diminishing the conversion process of energy outputted by fuel cell.     

Thermodynamic analysis of a new renewable energy based hybrid system for hydrogen liquefaction

In this paper, a parametric study of the triple effect absorption cooling system (TEACS) integrated with solar photo-voltaic/thermal (PV/T), geothermal, and Linde–Hampson cycle is conducted. The effect of different operating parameters on the COPs, ratio ‘n’, amount of hydrogen gas pre-cooled, amount of hydrogen liquefied, and utilization factor of the integrated system are studied. It is found that when mass flow rate of air increases the energetic and exergetic COPs decrease in an exponential form from 2.6 to 1.9, and 0.4 to 0.3, respectively. The amounts of hydrogen gas pre-cooled and hydrogen liquefied decrease from 0.39 kg/s to 0.32 kg/s and 0.082 kg/s and 0.066 kg/s, respectively with increase in mass flow rate of air. Moreover, the amounts of hydrogen gas pre-cooled and hydrogen liquefied decrease from 0.42 to 0.27, and 0.088 to 0.066, respectively with increase in mass flow rate of geothermal. In addition, energetic and exergetic utilization factors of integrated system decrease from 0.059 to 0.037, and 0.21 and 0.13, respectively with increase in mass flow rate of geothermal.     

Synthesis and evaluation of polythiocyanogen (SCN)x as a rechargeable lithium-ion battery electrode material

Polythiocyanogen, (SCN)_x, is a promising lithium-ion battery electrode material due to its high theoretical capacity (462 mAh g⁻¹), safe operation, inexpensive raw materials, and a simple and less energy-intensive manufacturing process. The (SCN)_x was prepared from the solution of trithiocyanate (SCN)₃⁻ in methylene dichloride (MDC), which was prepared by electrochemical oxidation of ammonium thiocyanate (NH₄SCN) in a two-phase electrolysis medium of 1.0 M NH₄SCN in 0.50 M H₂SO₄ + MDC. The (SCN)₃⁻ underwent auto catalytic polymerization to (SCN)_x during MDC removal. Battery electrodes with (SCN)_x as the active material were prepared, and tested in Swagelok cells using lithium foil as the counter and reference electrode. The cells delivered capacities in the range of 200-275 mAh g⁻¹ at the discharge-charge rate of 0.2 C. The cells were tested up to 20 cycles and showed repeatable performance with a coulombic efficiency of 97% at the 20th cycle. The results presented here indicate that (SCN)_x is a promising lithium-ion battery electrode-material candidate for further studies.     

Simulation based size optimization of a PV/wind hybrid energy conversion system with battery storage under various load and auxiliary energy conditions

In this paper, size of a PV/wind integrated hybrid energy system with battery storage is optimized under various loads and unit cost of auxiliary energy sources. The optimization is completed by a simulation based optimization procedure, OptQuest, which integrates various heuristic methods. In the study, the main performance measure is the hybrid energy system cost. And the design parameters are PV size, wind turbine rotor swept area and the battery capacity. The case study is realized for Izmir Institute of Technology Campus Area, Urla, Turkey. The simulation model of the system is realized in ARENA 12.0, a commercial simulation software, and is optimized using the OptQuest tool in this software. Consequently, the optimum sizes of PV, wind turbine and battery capacity are obtained under various auxiliary energy unit costs and two different loads. The optimum results are confirmed using Loss of Load Probability (LLP) and autonomy analysis. And the investment costs are investigated how they are shared among those four energy sources at the optimum points.