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.     

Simulation-based optimization and design of refinery hydrogen networks with hydrogen sulfide removal

Hydrogen consumption in oil refineries increases sharply because of more and more heavy and sour crude oil processing, which also makes hydrogen sulfide a considerable contaminant in off-gases of hydrotreaters. This work presents a simulation-based optimization model for synthesis of hydrogen networks with H₂S removal. Aspen HYSYS is employed for rigorous process and thermodynamic modeling of the H₂S removal unit. The proposed model is solved using the genetic algorithm combined with the linprog and fmincon solvers in the Matlab platform. The optimal hydrogen sources and the recirculated absorbent fed into the H₂S removal unit as well as the optimal design of the hydrogen network can be determined simultaneously. A case study is performed to illustrate the application and effectiveness of the proposed model. The result shows that the introduction of H₂S removal can decrease the fresh hydrogen consumption by 43% and the total annualized cost by 17%.     

Simulation-based modeling and optimization for refinery hydrogen network integration with light hydrocarbon recovery

Purge gases from hydrocrackers and hydrotreaters and refinery off-gases are important hydrogen sources. Some of these hydrogen sources are also rich in light hydrocarbons that are valuable energy resources and chemical materials. In this work, a systematic method is proposed to integrate hydrogen networks considering light hydrocarbon recovery. This work first develops a hydrogen network superstructure with light hydrocarbon recovery. Aspen HYSYS is employed for rigorous process and thermodynamic modeling of the light hydrocarbon recovery process, and a simulation-optimization model is then developed. To solve the simulation-optimization model efficiently, the genetic algorithm is used as the global solver to determine the feed to light hydrocarbon recovery unit, and the linprog and fmincon solvers are combined to determine the optimal hydrogen network design. The application and effectiveness of the proposed method is validated through a case study. The results show that fresh hydrogen consumption decreases by 13% and the total annualized cost reduces to 72% because of light hydrocarbon recovery. This method could provide useful guides for the management of hydrogen and light hydrocarbons in refineries.     

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.     

A P-Graph approach for the synthesis of hydrogen networks with pressure and impurity constraints

The increasing demand for hydrogen in refineries and petrochemical plants is challenging these facilities to minimise their hydrogen utility without incurring high capital and operating costs. As environment-related fuel specifications become more stringent, the demand for hydrogen increases, especially for the operation of hydrodesulphurisation in refineries. A P-graph model is developed in this paper for the synthesis of hydrogen networks. The model is capable of generating optimal and near-optimal solutions for the hydrogen network. The proposed methodology is computationally efficient and require minimal understanding of programming language. The developed model includes both direct recycle/reuse and regeneration schemes; and accounts for pressure and impurity constraints in the hydrogen network. In addition, the application of hydrogen header can also be handled by the P-graph model. The methodology is illustrated with three literature examples and the results obtained match those reported in literature.     

Quantitative valuation of hydrogen blending in European gas grids and its impact on the combustion process of large-bore gas engines

The approach of fossil fuel substitution requires alternative strategies in the progressing sector coupling of energy storage, distribution and conversion. Promising solutions are flexibly supply chain models of green and blue hydrogen which is fed into the natural gas network (HNG). Prerequisite for a successful implementation is the functional capability of end-use applications for which different volumetric hydrogen thresholds are documented in literature. A clear research gap is thereby evident for HNG fired medium-speed large-bore gas engines typical used for stationary power generation. For solving this problem, generic single cylinder tests with focus on operating window, NO_x formation and hydro-carbon emissions have been carried out. The results are analysed and compared to available publications of HNG fired high-speed gas engines to derive general insights of the combustion characteristics. Under rising blending share, an in literature described, general shifting of the possible operating window and an increase of NO_x formation are detected. In terms of unburned hydrocarbons, a NO_x-neutral reduction potential through hydrogen blending is only visible under very lean operating conditions. This result deviates from expected literature values of high-speed engine setups. The experimental study demonstrates the NO_x neutral combustion capability of medium-speed large-bore gas engines under 20% hydrogen admixture.     

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.     

Dispersion and behavior of hydrogen for the safety design of hydrogen production plant attached with nuclear power plant

Development of nuclear energy and hydrogen energy both as renewable energy open up a vast range of prospects. The scheme for hydrogen generation station in nuclear power plant has been carried out in china. However, Nuclear Energy is expected to encourage a safety culture that prevents serious accidents while dispersion of hydrogen from a container produces a risk of combustion. The dispersion and behavior of hydrogen production plant attached with nuclear power plant are still poorly understood. In this paper, a dispersion of hydrogen model is established and is calculated under two typical condition with corrected ideal gas state equation. The flammability of hydrogen after dispersion is studied. The range of flammability of dispersion of hydrogen production plant with different pressures, positions and temperatures is obtained. This work could contribute to the marginal hydrogen safety design for hydrogen production station and lay the foundation for the establishment of a safe distance standard that it's necessary to prevent hydrogen explosion.     

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.     

The economic and environmental impact of power to hydrogen/power to methane facilities on hybrid power-natural gas energy systems

The curtailment of renewable energy would be reduced by converting it to hydrogen or methane using power to hydrogen (P2H) facilities or power to methane (P2M) facilities. Both hydrogen and methane can be injected into the existing natural gas system which has significant potential to unlock the inherent flexibility of integrated energy systems. The coordinated operation strategy of the hybrid power-natural gas energy systems considering P2H and P2M is proposed aiming to minimize the operational cost. In addition, a method to calculate the higher heating value of hydrogen-natural gas mixture is presented along with a strategy for handling the constraints of hydrogen mixture level limits. The simulation results of three case studies demonstrate the economic and environmental benefits of P2H/P2M in terms of reductions in cost, CO₂ emissions and wind power curtailment. The differences in benefits between P2H and P2M have also been compared and analyzed.