Application of artificial neural networks (ANN) for modeling of industrial hydrogen plant

A back propagation feed forward artificial neural network (ANN) with three layers is used for modeling of industrial hydrogen plant. The required operating data for training of ANN is obtained by modeling and simulation of an industrial hydrogen plant. The operating data are calculated by changing effective parameters such as feed temperature, reformer pressure, steam to carbon ratio and carbon dioxide to methane ratio in feed stream. Tangent sigmoid transfer function is used in the hidden and output layer and the proposed neural network is trained with a gradient descent algorithm. The optimum number of neurons in hidden layer is determined as optimum value with minimizing of the mean square error (MSE). With changing of effective parameters, the model predicts temperature, pressure and mole fraction of hydrogen and carbon monoxide in the product of the hydrogen plant. The result can be used to gain better knowledge and optimize of the hydrogen production plants.     

Molten carbonate fuel cell (MCFC)-based hybrid propulsion systems for a liquefied hydrogen tanker

This study proposes a molten carbonate fuel cell (MCFC)-based hybrid propulsion system for a liquefied hydrogen tanker. This system consists of a molten carbonate fuel cell and a bottoming cycle. Gas turbine and steam turbine systems are considered for recovering heat from fuel cell exhaust gases. The MCFC generates a considerable propulsion power, and the turbomachinery generates the remainder of the power. The hybrid systems are evaluated regarding system efficiency, economic feasibility, and exhaust emissions. The MCFC with a gas turbine has higher system efficiency than that with a steam turbine. The air compressor consumes substantial power and should be mechanically connected to the gas turbine. Although fuel cell-based systems are less economical than other propulsion systems, they may satisfy the environmental regulations. When the ship is at berth, the MCFC systems can be utilized as distributed generation that is connected to the onshore-power grid.     

Simulation and multi-objective optimization of an integrated process for hydrogen production from refinery off-gas

Hydrogen production from internal refinery sources such as refinery off-gas (ROG) is one of the most cost-effective solutions to a refinery's hydrogen supply. To maximize the value of such resource, this paper proposes an integrated hydrogen production process based on coupled feed of ROG and natural gas. A rigorous process model is developed and simulated using the commercial process simulator Aspen Plus. To simultaneously maximize hydrogen and steam production, a non-dominated sorting genetic algorithm-II (NSGA-II) is employed to solve the constrained multi-objective optimization problem. A modular framework of the process simulator and multi-objective genetic algorithm is also developed to obtain sets of Pareto-optimal operating conditions, making it easier to optimize the integrated hydrogen production process. The optimization results reveal that the performance of the integrated process can be significantly improved.     

Development of the once-through hybrid sulfur process for nuclear hydrogen production

The Once-through Hybrid Sulfur (Ot-HyS) process, proposed in this work, produces hydrogen using the same Sulfur dioxide Depolarized water Electrolysis (SDE) process found in the original Hybrid Sulfur cycle (HyS). In the process proposed here, the Sulfuric Acid Decomposition (SAD) process in the HyS procedure is replaced with the well-established sulfur combustion process. First, a flow sheet for the Ot-HyS process was developed by referring to existing facilities and to the work done by the Savannah River National Laboratory (SRNL) under their reasonable assumptions. The process was then simulated using Aspen Plus with appropriate thermodynamic models. It was demonstrated that the Ot-HyS process has higher net thermal efficiency, as well as other advantages, over competing benchmark processes. The net thermal efficiency of the Ot-HyS process is 47.1% (based on LHV) and 55.7% (based on HHV) assuming 33.3% thermal-to-electric conversion efficiency of a nuclear power plant with no consideration given to the work for the air separation. Hydrogen produced through the Ot-HyS process would be used as off-peak electricity storage, to relieve the burden of load-following and could help to expand applications of nuclear energy, which is regarded as a ’sustainable development’ technology.     

The development of a PEMFC hybrid power electric vehicle with automatic sodium borohydride hydrogen generation

This paper describes the development of a hybrid Proton Exchange Membrane Fuel Cell (PEMFC) electric vehicle consisting of a 3 kW PEMFC, PV arrays, secondary battery sets, and a chemical hydrogen generation system. We first integrate a hybrid PEMFC electric vehicle and design power management strategies. The on-board hydrogen generation system can provide sufficient hydrogen for continuous operation of the PEMFC, and the performance tests demonstrate the effectiveness of the integrated system in providing sustainable power for driving. We then use Matlab/SimPowerSystem? to develop a simulation model and adjust the model parameters using experimental data. The results indicated that the model can effectively predict system responses and can be used for performance evaluation. We also use the simulation model to estimate the mileage and costs of the developed electric vehicle, and we discuss the impacts of component sizes on system costs and travelling ranges.     

Mathematical modeling and optimization of hydrogen distribution network used in refinery

In the present investigation, mathematical models have been developed to optimize hydrogen distribution in the refinery. Five models, Model-0, Model-1, Model-2, Model-3 and Model-4, have been formulated to determine the optimal hydrogen network. Amongst these, Model-0 and Model-1 are NLP networks, whereas the remaining three are MINLP networks. The NLP models are improved gradually to develop MINLP models which incorporate new compressor and PSA. The model considers pressure constraints, source flow balance, sink flow balance, compressor flow balance, sink purity constraint, operating cost, capital cost associated with new equipment, payback period and export cost. Amongst five models, Model-4 is predicted as optimal network which is MINLP model incorporating new compressor and PSA. It predicts reduction in hydrogen by 21.74% and annual profit of $ 16.57 million. The present work selects the optimal type of new compressor based on different capital cost functions. Further, the reliability of the present work is checked through comparison of its results with published models.     

A model for investigation of optimal hydrogen pathway,and evaluation of environmental impacts of hydrogen supply system

In order to achieve a hydrogen economy, developing widespread hydrogen supply systems are vitally important. A large number of technological options exist and are still in development for hydrogen production, storage, distribution…, which cause various pathways for supplying hydrogen. Besides the technical factors, there are other effective parameters such as cost, operability, reliability, environmental impacts, safety and social implications that should be considered when assessing the different pathways as optimal and viable long-term alternatives. To aid this decision-making process, we have developed a generic optimization-based model for the long-range energy planning and design of future hydrogen supply systems. By applying Linear Dynamic Programming techniques, the model is capable of identifying optimal investment strategies and integrated supply system configurations from the many alternatives. Also, the environmental impacts of hydrogen supply system can be evaluated through scenario analysis. The features and capabilities of the model are illustrated through application to Iran as a case study.     

Design and simulation of the power control system of a plant for the generation of hydrogen via electrolysis, using photovoltaic solar energy

The gradual exhaustion of natural resources, particularly energy sources, and the various problems involved in their life-cycle, makes it necessary to promote a renewably derived hydrogen economy, in which hydrogen is produced from clean sources.

In this paper, the control system for an installation for producing hydrogen via electrolysis using only a 250 kWp photovoltaic generator is presented. Computer simulation was used to design and confirm its correct performance.

The results obtained ensure the installation's high energy yield.     

Artificial neural networks and neuro-fuzzy inference systems as virtual sensors for hydrogen safety prediction

Hydrogen is increasingly investigated as an alternative fuel to petroleum products in running internal combustion engines and as powering remote area power systems using generators. The safety issues related to hydrogen gas are further exasperated by expensive instrumentation required to measure the percentage of explosive limits, flow rates and production pressure. This paper investigates the use of model based virtual sensors (rather than expensive physical sensors) in connection with hydrogen production with a Hogen^®20 electrolyzer system. The virtual sensors are used to predict relevant hydrogen safety parameters, such as the percentage of lower explosive limit, hydrogen pressure and hydrogen flow rate as a function of different input conditions of power supplied (voltage and current), the feed of de-ionized water and Hogen^®20 electrolyzer system parameters. The virtual sensors are developed by means of the application of various Artificial Intelligent techniques. To train and appraise the neural network models as virtual sensors, the Hogen^®20 electrolyzer is instrumented with necessary sensors to gather experimental data which together with MATLAB neural networks toolbox and tailor made adaptive neuro-fuzzy inference systems (ANFIS) were used as predictive tools to estimate hydrogen safety parameters. It was shown that using the neural networks hydrogen safety parameters were predicted to less than 3% of percentage average root mean square error. The most accurate prediction was achieved by using ANFIS.     

Modelling and simulation of a zero-emission hybrid power plant for a domestic ferry

This paper presents a simulation tool for marine hybrid power-plants equipped with polymer exchange membrane fuel cells and batteries. The virtual model, through the combination of operational data and dynamically modelled subsystems, can simulate power-plants of different sizes and configurations, in order to analyze the response of different energy management strategies. The model aims to replicate the realistic behavior of the components included in the vessel's grid, to asses if the hardware selected by the user is capable of delivering the power set-point requested by the energy management system. The model can then be used to optimize key factors such as hydrogen consumption. The case study presented in the paper demonstrates how the model can be used for the evaluation of a retrofitting operation, replacing a diesel electric power-plant with fuel cells and batteries. The vessel taken into consideration is a domestic ferry, operating car and passenger transport in Denmark. The vessel is outfitted with a diesel electric plant and an alternative hybrid power-plant is proposed. The hybrid configuration is tested using the model in a discrete time-domain.     

Modeling and control design of hydrogen production process for an active hydrogen/wind hybrid power system

This paper gives a control oriented modeling of an electrolyzer, as well as the ancillary system for the hydrogen production process. A Causal Ordering Graph of all necessary equations has been used to illustrate the global scheme for an easy understanding. The model is capable of characterizing the relations among the different physical quantities and can be used to determine the control system ensuring efficient and reliable operation of the electrolyzer. The proposed control method can manage the power flow and the hydrogen flow. The simulation results have highlighted the variation domains and the relations among the different physical quantities. The model has also been experimentally tested in real time with a Hardware-In-the-Loop Simulation before being integrated in the test bench of the active wind energy conversion system.     

Covalent hybrid of hemin and mesoporous carbon as a high performance electrocatalyst for oxygen reduction

A high performance hemin and mesoporous carbon hybrid electrocatalyst for the oxygen reduction reaction (ORR) is developed by using hemin as the Fe–N-containing precursor to control the chemistry of the metal and the chemical composition of the carbon surface. As a first step, Hemin is used as the Fe–N-containing precursor to prepare the Fe–N-doped mesoporous carbon (H-MC) via a nano-casting process by using sucrose as a carbon source and mesoporous silica as a hard template. Hemin is then used as the Fe–N₄-containing precursor to prepare H-MC supported hybrid catalyst. The Fe-doped and N-doped mesoporous carbons are also prepared and the catalytic properties of the prepared catalysts for ORR in alkaline media are investigated. The results show that as compared with the much more expensive Pt/C catalyst, the hybrid catalyst obtained in this work exhibits not only a higher onset potential, but also a higher current density.     

Comparative performance analysis of a grid connected PV system for hydrogen production using PEM water,methanol and hybrid sulfur electrolysis

This paper presents comparative performance analysis of photovoltaic (PV) hydrogen production using water, methanol and hybrid sulfur (SO₂) electrolysis processes. Proton exchange membrane (PEM) electrolysers are powered by grid connected PV system. In this system design, electrical grid is considered as a virtual energy storage system (VESS) where the surplus of PV production can be injected and subsequently taken to support the electrolyser. Methanol (ME) and hybrid sulfur (HSE) electrolysis are compared to the conventional water electrolysis (WE) in term of operating cell voltage. Based on the experimental results reported in the literature, semi-empirical models describing the relationship between the hydrogen production rate and the electrolyser cell power input are proposed. Furthermore, power and hydrogen management strategy (PHMS) is developed. Case study is carried out to show the impact of each type of electrolysis on the system component sizes and evaluate the hydrogen production potentialities. Results show that the use of ME allows to produce 65% more hydrogen than with using WE. Moreover, the amount of hydrogen produced is almost double in the case of HSE. At Algiers city, based on a grid connected PV/Electrolyser system, it is possible to produce about 25 g/m² d and 29 g/m² d of hydrogen, respectively, through ME and HSE compared to 15 g/m² d of hydrogen when using WE.     

Application of artificial neural networks to the condition monitoring and diagnosis of a combined heat and power plant

The objective of this study has been to create an online system for condition monitoring and diagnosis of a combined heat and power plant in Sweden. The system in question consisted of artificial neural network models, representing each main component of the combined heat and power plant, connected to a graphical user interface. The artificial neural network models were integrated on a power generation information manager server in the computer system of the combined heat and power plant, and the graphical user interface was made available on workstations connected to this server.     

Original hybrid membrane-catalytic reactor for the Co-Production of syngas and ultrapure hydrogen in the processes of dry and steam reforming of methane,ethanol and DME

An original hybrid membrane-catalytic reactor (HMCR) was developed for the co-production of syngas and ultrapure hydrogen from fossil and renewable organic sources (methane and ethanol), as well as from synthetic feedstock (dimethyl ether) via dry and steam reforming. HMCR is a facility in which a porous ceramic catalytic converter prepared by self-propagating high-temperature synthesis (SHS) is integrated with a hydrogen-selective palladium-containing membrane. Due to separation of hydrogen from the reaction site and according to Le Chatelier-Brown principle it enables reforming to proceed effectively under milder temperature conditions as compared to a conventional reactor with a stationary bulk catalyst bed. On the basis of HMCR there can be developed mobile and small-size ultrapure hydrogen production units for fine processes of organic synthesis and electricity generation.     

Optimal sizing for a wind-photovoltaic-hydrogen hybrid system considering levelized cost of storage and source-load interaction

Hydrogen energy storage system (HESS) has excellent potential in high-proportion renewable energy systems due to its high energy density and seasonal storage characteristics. After detailing the volatility of wind speed, irradiance and load, this paper proposes a bi-level optimization model to analyze the economic operation of the wind-photovoltaic-hydrogen hybrid system (WPH-HS). First, the relationship between the source-load output matching and operating conditions of HESS is studied, two evaluation indicators are described, which can be adjusted by wind-solar complementarity on the source side and demand response on the load side. Second, considering the levelized cost of storage (LCOS), the total annual cost (TAC) calculation method of WPH-HS is presented, and this paper provides a new hybrid optimization technology of chaotic search, particle swarm optimization and non-dominated sorting genetic algorithm2. Finally, the system is simulated with the MATLAB software to determine the optimal sizing of components and minimize the LCOS while ensuring the optimal TAC. The simulation results are elaborated in detail. In particular, the added source-load interaction reduces the TAC and LCOS by 7.3% and 10.3%. When two indicators reach 0.03 and 0.1745, the system is economically viable with the LCOS of 0.276 USD/kWh. The hybrid optimization algorithm can achieve better result in fewer iterations.     

A comprehensive method for optimal power management and design of hybrid RES-based autonomous energy systems

The power management strategy (PMS) plays an important role in the optimum design and efficient utilization of hybrid energy systems. The power available from hybrid systems and the overall lifetime of system components are highly affected by PMS. This paper presents a novel method for the determination of the optimum PMS of hybrid energy systems including various generators and storage units. The PMS optimization is integrated with the sizing procedure of the hybrid system. The method is tested on a system with several widely used generators in off-grid systems, including wind turbines, PV panels, fuel cells, electrolyzers, hydrogen tanks, batteries, and diesel generators. The aim of the optimization problem is to simultaneously minimize the overall cost of the system, unmet load, and fuel emission considering the uncertainties associated with renewable energy sources (RES). These uncertainties are modeled by using various possible scenarios for wind speed and solar irradiation based on Weibull and Beta probability distribution functions (PDF), respectively. The differential evolution algorithm (DEA) accompanied with fuzzy technique is used to handle the mixed-integer nonlinear multi-objective optimization problem. The optimum solution, including design parameters of system components and the monthly PMS parameters adapting climatic changes during a year, are obtained. Considering operating limitations of system devices, the parameters characterize the priority and share of each storage component for serving the deficit energy or storing surplus energy both resulted from the mismatch of power between load and generation. In order to have efficient power exploitation from RES, the optimum monthly tilt angles of PV panels and the optimum tower height for wind turbines are calculated. Numerical results are compared with the results of optimal sizing assuming pre-defined PMS without using the proposed power management optimization method. The comparative results present the efficacy and capability of the proposed method for hybrid energy systems.     

A system dynamics approach to scenario analysis for urban passenger transport energy consumption and CO2 emissions: A case study of Beijing

With the accelerating process of urbanization, developing countries are facing growing pressure to pursue energy savings and emission reductions, especially in urban passenger transport. In this paper, we built a Beijing urban passenger transport carbon model, including an economy subsystem, population subsystem, transport subsystem, and energy consumption and CO₂ emissions subsystem using System Dynamics. Furthermore, we constructed a variety of policy scenarios based on management experience in Beijing. The analysis showed that priority to the development of public transport (PDPT) could significantly increase the proportion of public transport locally and would be helpful in pursuing energy savings and emission reductions as well. Travel demand management (TDM) had a distinctive effect on energy savings and emission reductions in the short term, while technical progress (TP) was more conducive to realizing emission reduction targets. Administrative rules and regulations management (ARM) had the best overall effect of the individual policies on both energy savings and emission reductions. However, the effect of comprehensive policy (CP) was better than any of the individual policies pursued separately. Furthermore, the optimal implementation sequence of each individual policy in CP was TP→PDPT→TDM→ARM.     

Architecture design and performance analysis of a hybrid hydrogen fuel cell system for unmanned aerial vehicle

The flight endurance of UAV systems is an important issue that restricts the operational capabilities. Thus, different energy systems and alternative onboard energy generation systems have been tested for the UAVs. Within these systems, fuel cells provide high energy density that can increase flight endurance greatly. In this study, a PEM fuel cell – Li-Po battery hybrid system has been developed by evaluating three architecture models. In the guide of the experimental power demand data of a fixed-wing UAV, modeling and testing procedures were performed. Battery voltage and fuel cell current variations observed during the ground tests were evaluated. It has been observed that approximately 160–170 W of the 250 W power is met by the fuel cell since no preconditioning has been applied and the temperature values at which the fuel cell exhibits its optimum performance. In the case where the fuel cell could provide 7.8 An under conditions where the humidification effects were not included in the model, the required current was over 7.8 A between approximately 400-1200 s. The fuel cell and battery behavior in response to the sudden power changes and to the uncertainties corresponding to the changes in the motor power during the flight are also detailed.     

The effects of hydrogen addition on engine power and emission in DME premixed charge compression ignition engine

Premixed-charge compression-ignition (PCCI) combustion of dimethyl-ether (DME) with double injection strategy was investigated in a single-cylinder compression-ignition engine. DME main-injection was replaced by hydrogen to reduce carbon dioxide emissions. To study the effect of hydrogen, the injected amount of hydrogen was increased. Engine performance and emission of DME PCCI combustion were compared to those of hydrogen–DME PCCI combustion. In the DME PCCI engine operation, DME was injected directly into the cylinder at −120 crank angle degrees (°CA) after top dead center (aTDC) to simulate homogeneous charge at first, and then DME was injected secondly with varied second injection timing. In this case, DME injection timing in the second stage affected the engine performance and emissions. Delayed combustion phase showed a higher indicated mean effective pressure (IMEP), while it increased NO_x emission when DME second injection is retarded. In the hydrogen–DME PCCI, hydrogen was injected at intake port with fixed injection timing. DME injection timing in hydrogen–DME PCCI combustion was also varied from −120 °CA to TDC, as in the DME PCCI engine operation. The total supplied heating value was fixed at 400 J for all cases. DME injection timing determined the start of combustion for the hydrogen–DME PCCI. With increasing the amount of hydrogen, exhaust emissions were reduced. Hydrogen–DME PCCI engine was operated with minimum amount of DME via the hydrogen addition and DME injection timing control. The optimized DME injection timing, −30 °CA aTDC, resulted in a lower exhaust emission-operation, while maintaining a higher IMEP.