An efficient parameter estimation algorithm for proton exchange membrane fuel cells

The proton exchange membrane fuel cell (PEMFC) is a favorable renewable energy source to overcome environmental pollution and save electricity. However, the mathematical model of the PEMFC contains some unknown parameters which have to be accurately estimated to build an accurate PEMFC model; this problem is known as the parameter estimation of PEMFC and belongs to the optimization problem. Although this problem belongs to the optimization problem, not all optimization algorithms are suitable to solve it because it is a nonlinear and complex problem. Therefore, in this paper, a new optimization algorithm known as the artificial gorilla troops optimizer (GTO), which simulates the collective intelligence of gorilla troops in nature, is adapted for estimating this problem. However, the GTO is suffering from local optima and low convergence speed problems, so a modification based on replacing its exploitation operator with a new one, relating the exploration and exploitation according to the population diversity in the current iteration, has been performed to improve the exploitation operator in addition to the exploration one. This modified variant, named the modified GTO (MGTO), has been applied for estimating the unknown parameters of three PEMFC stacks, 250 W stack, BCS-500W stack, and SR-12 stack, used widely in the literature, based on minimizing the error between the measured and estimated data points as the objective function. The outcomes obtained by applying the GTO and MGTO on those PEMFC stacks have been extensively compared with those of eight well-known optimization algorithms using various performance analyses, best, average, worst, standard deviation (SD), CPU time, mean absolute percentage error (MAPE), and mean absolute error (MAE), in addition to the Wilcoxon rank-sum test, to show which one is the best for solving this problem. The experimental findings show that MGTO is the best for all performance metrics, but CPU time is competitive among all algorithms

Tree Growth Algorithm for Parameter Identification of Proton Exchange Membrane Fuel Cell Models

Demonstrating an accurate mathematical model is a mandatory issue for realistic simulation, optimization and performance evaluation of proton exchange membrane fuel cells (PEMFCs). The main goal of this study is to demonstrate a precise mathematical model of PEMFCs through estimating the optimal values of the unknown parameters of these cells. In this paper, an efficient optimization technique, namely, Tree Growth Algorithm (TGA) is applied for extracting the optimal parameters of different PEMFC stacks. The total of the squared deviations (TSD) between the experimentally measured data and the estimated ones is adopted as the objective function. The effectiveness of the developed parameter identification algorithm is validated through four case studies of commercial PEMFC stacks under various operating conditions. Moreover, comprehensive comparisons with other optimization algorithms under the same study cases are demonstrated. Statistical analysis is presented to evaluate the accuracy and reliability of the developed algorithm in solving the studied optimization problem

A Comprehensive Review and Application of Metaheuristics in Solving the Optimal Parameter Identification Problems

For many electrical systems, such as renewable energy sources, their internal parameters are exposed to degradation due to the operating conditions. Since the model’s accuracy is required for establishing proper control and management plans, identifying their parameters is a critical and prominent task. Various techniques have been developed to identify these parameters. However, metaheuristic algorithms have received much attention for their use in tackling a wide range of optimization issues relating to parameter extraction. This work provides an exhaustive literature review on solving parameter extraction utilizing recently developed metaheuristic algorithms. This paper includes newly published articles in each studied context and its discussion. It aims to approve the applicability of these algorithms and make understanding their deployment easier. However, there are not any exact optimization algorithms that can offer a satisfactory performance to all optimization issues, especially for problems that have large search space dimensions. As a result, metaheuristic algorithms capable of searching very large spaces of possible solutions have been thoroughly investigated in the literature review. Furthermore, depending on their behavior, metaheuristic algorithms have been divided into four types. These types and their details are included in this paper. Then, the basics of the identification process are presented and discussed. Fuel cells, electrochemical batteries, and photovoltaic panel parameters identification are investigated and analyzed

Role of Metaheuristics in Optimizing Microgrids Operating and Management Issues::A Comprehensive Review

The increased interest in renewable-based microgrids imposes several challenges, such as source integration, power quality, and operating cost. Dealing with these problems requires solving nonlinear optimization problems that include multiple linear or nonlinear constraints and continuous variables or discrete ones that require large dimensionality search space to find the optimal or sub-optimal solution. These problems may include the optimal power flow in the microgrid, the best possible configurations, and the accuracy of the models within the microgrid. Metaheuristic optimization algorithms are getting more suggested in the literature contributions for microgrid applications to solve these optimization problems. This paper intends to thoroughly review some significant issues surrounding microgrid operation and solve them using metaheuristic optimization algorithms. This study provides a collection of fundamental principles and concepts that describe metaheuristic optimization algorithms. Then, the most significant metaheuristic optimization algorithms that have been published in the last years in the context of microgrid applications are investigated and analyzed. Finally, the employment of metaheuristic optimization algorithms to specific microgrid issue applications is reviewed, including examples of some used algorithms. These issues include unit commitment, economic dispatch, optimal power flow, distribution system reconfiguration, transmission network expansion and distribution system planning, load and generation forecasting, maintenance schedules, and renewable sources max power tracking

Fuel Cell Renewable Hybrid Power Systems

Climate change is becoming visible today, and so this book—through including innovative solutions and experimental research as well as state-of-the-art studies in challenging areas related to sustainable energy development based on hybrid energy systems that combine renewable energy systems with fuel cells—represents a useful resource for researchers in these fields. In this context, hydrogen fuel cell technology is one of the alternative solutions for the development of future clean energy systems. As this book presents the latest solutions, readers working in research areas related to the above are invited to read it

Effect of the air pressure on electro-Fenton process

Electro-Fenton process is considered a very promising tool for the treatment of waste waters contaminated by organic pollutants refractant or toxic for microorganisms used in biological processes [1-6]. In these processes H2O2 is continuously supplied to an acidic aqueous solution contained in an electrolytic cell from the two-electron reduction of oxygen gas, directly injected as pure gas or bubbled air. Due to the poor solubility of O2 in aqueous solutions, two dimensional cheap graphite or carbon felt electrodes give quite slow generation of H2O2, thus resulting in a slow abatement of organics. In this context, we report here a series of studies [7-9] on the effect of air pressure on the electro-generation of H2O2 and the abatement of organic pollutants in water by electro-Fenton process. The effect of air pressure, current density, mixing and nature of the organic pollutant was evaluated. [1] E. Brillas, I. Sirés, M.A. Oturan, Chem. Rev., 109 (2009) 6570-6631. [2] C.A. Martínez-Huitle, M.A. Rodrigo, I. Sirés, O. Scialdone, Chem. Rev. 115 (2015) 13362–13407. [3] M. Panizza, G. Cerisola, Chem. Rev. 109 (2009) 6541–6569. [4] I. Sirés, E. Brillas, M.A. Oturan, M.A. Rodrigo, M. Panizza, Environ. Sci. Pollut. Res. 21 (2014) 8336–8367. [5] C.A. Martínez-Huitle, S. Ferro, Chem. Soc. Rev. 35 (2006) 1324–1340. [6] B.P.P. Chaplin, Environ. Sci. Process. Impacts. 16 (2014) 1182–1203. [7] O. Scialdone, A. Galia, C. Gattuso, S. Sabatino, B. Schiavo, Electrochim. Acta, 182 (2015) 775-780. [8] J.F. Pérez, A. Galia, M.A. Rodrigo, J. Llanos, S. Sabatino, C. Sáez, B. Schiavo, O. Scialdone, Electrochim. Acta, 248 (2017) 169-177. [9] A.H. Ltaïef, S. Sabatino, F. Proietto, A. Galia, O. Scialdone, O. 2018, Chemosphere, 202, 111-118

Pressurized CO2 Electrochemical Conversion to Formic Acid: From Theoretical Model to Experimental Results

To curb the severely rising levels of carbon dioxide in the atmosphere, new approaches to capture and utilize this greenhouse gas are currently being investigated. In the last few years, many researches have focused on the electrochemical conversion of CO2 to added-value products in aqueous electrolyte solutions. In this backdrop, the pressurized electroreduction of CO2 can be assumed an up-and-coming alternative process for the production of valuable organic chemicals [1-3]. In this work, the process was studied in an undivided cell with tin cathode in order to produce formic acid and develop a theoretical model, predicting the effect of several operative parameters. The model is based on the cathodic conversion of pressurized CO2 to HCOOH and it also accounts for its anodic oxidation. In particular, the electrochemical reduction of CO2 to formic acid was performed in pressurized filter press cell with a continuous recirculation of electrolytic solution (0.9 L) at a tin cathode (9 cm2) for a long time (charge passed 67’000 C). It was shown that it is possible to scale-up the process by maintaining good results in terms of faradaic efficiency and generating significantly high concentrations of HCOOH (about 0.4 M) [4]. It was also demonstrated that, for pressurized systems, the process is under the mixed kinetic control of mass transfer of CO2 and the reduction of adsorbed CO2 (described by the Langmuir equation), following our proposed reaction mechanism [5]. Moreover, the theoretical model is in good agreement with the experimental results collected and well describes the effect of several operating parameters, including current density, pressure, and the type of reactor used. 1. Ma, S., & Kenis, P. J. (2013). Electrochemical conversion of CO2 to useful chemicals: current status, remaining challenges, and future opportunities. Current Opinion in Chemical Engineering, 2(2), 191-199. 2. Endrődi, B., Bencsik, G., Darvas, F., Jones, R., Rajeshwar, K., & Janáky, C. (2017). Continuous-flow electroreduction of carbon dioxide. Progress in Energy and Combustion Science, 62, 133-154. 3. Dufek, E. J., Lister, T. E., Stone, S. G., & McIlwain, M. E. (2012). Operation of a pressurized system for continuous reduction of CO2. Journal of The Electrochemical Society, 159(9), F514-F517. 4. Proietto, F., Schiavo, B., Galia, A., & Scialdone, O. (2018). Electrochemical conversion of CO2 to HCOOH at tin cathode in a pressurized undivided filter-press cell. Electrochimica Acta, 277, 30-40. 5. Proietto, F., Galia, A., & Scialdone, O. (2019) Electrochemical conversion of CO2 to HCOOH at tin cathode: development of a theoretical model and comparison with experimental results. ChemElectroChem, 6, 162-172

Investigation of novel ammonia production options using photoelectrochemical hydrogen

Hydrogen and ammonia are two of the most significant clean fuels, energy carriers and storage media in the near future. Production of these chemicals are desired to be environmentally friendly. Renewable energy, in particular solar energy-based hydrogen and ammonia production technologies bring numerous attractive solutions for sustainable energy production, conversion and utilization. The energy of the sun is endless and the water is a substance which is always accessible and renewable. Ammonia is currently one of the mostly used chemicals throughout the world due to many applications, such as fertilizers, cooling agents, fuel, etc. The Haber-Bosch process is the most dominant ammonia synthesis process which requires very high temperatures and pressures to operate and consumes massive amounts of fossil fuels mainly natural gas leading a non-sustainable process in the long-term. Therefore, alternative methods for ammonia production are in urgent need of development. This study theoretically and experimentally investigates the photoelectrochemical production of hydrogen and electrochemical synthesis of ammonia in a cleaner and integrated manner. In this respect, the main objective of this thesis is to develop a novel solar energy based ammonia production system integrated to photoelectrochemical hydrogen production. The hybrid system enhances the utilization of sunlight by splitting the spectrum and combining the photovoltaic and photoelectrochemical processes for electricity, hydrogen and ammonia production. The photoelectrochemical reactor is built by electrodeposition of the photosensitive semiconductor (copper oxide) on the photocathode. The characterization of the reactor under solar simulator light, ambient irradiance and concentrated light is accomplished. Furthermore, an electrochemical ammonia synthesis reactor is built using molten salt electrolyte, nickel electrodes and iron-oxide catalyst. The electrochemical synthesis of ammonia is succeeded using hydrogen and nitrogen feed gases above 180??C and at ambient pressures. The photoelectrochemically produced hydrogen is then reacted with nitrogen in the electrochemical reactor to produce clean ammonia. The comprehensive thermodynamic, thermoeconomic, electrochemical and life cycle models of the integrated system are developed and analyses are performed. The results obtained through models and experiments are comparatively assessed. The spectrum of solar light can be separated for various applications to enhance the overall performance of energy conversion from solar to other useful commodities such as electricity, fuels, heating and cooling. The results of this thesis show that under concentrated and split spectrum, the photoelectrochemical hydrogen production rates and efficiencies are improved. The overall integrated system exergy efficiencies are found to be 7.1% and 4.1% for hydrogen and ammonia production, respectively. The total cost rate of the experimental system for hydrogen and ammonia production is calculated to be 0.61 $/h from exergoeconomic analyses results. The solar-to-hydrogen conversion efficiency of the photoelectrochemical process increases from 5.5% to 6.6% under concentrated and split spectrum. Similarly, the photovoltaic module efficiency can be increased up to 16.5% under concentrated light conditions. Furthermore, the maximum coulombic efficiency of electrochemical ammonia synthesis process is calculated as 14.2% corresponding to NH3 formation rate of 4.41??10-9 mol s-1 cm-2

STUDY OF STRATEGIES FOR AN OPTIMAL ENERGY MANAGEMENT ON ELECTRIC AND HYBRID VEHICLES

Questa tesi di dottorato è focalizzata sull’identificazione di strategie di gestione dell’energia a bordo di veicoli elettrici e ibridi, con l’obiettivo di ottimizzare la gestione dell’energia e, quindi, consentire un risparmio di risorse. Infatti, l’ottimizzazione della fase d’uso del veicolo, attraverso una più efficiente gestione dell’energia, consente di dimensionare in modo ridotto i principali componenti, come il pacco batterie. Innanzitutto, viene presentato un tool di simulazione denominato TEST (Target-speed EV Simulation Tool). Questo strumento consente di effettuare simulazioni di dinamica longitudinale per veicoli completamente elettrici o ibridi e, quindi, di monitorare tutti i dati rilevanti necessari per effettuare un corretto dimensionamento del gruppo propulsore, inclusi il/i motore/i elettrico/i ed il pacco batterie. Inoltre, è possibile testare anche diversi layout di propulsori, compresi quelli che utilizzano celle a combustibile, le cosiddette “fuel cell”. Viene poi presentata una strategia di frenata rigenerativa, adatta per veicoli FWD, RWD e AWD. L’obiettivo principale è quello di recuperare la massima energia frenante possibile, mantenendo il veicolo stabile, con buone prestazioni in frenata. La strategia è stata testata sia attraverso un consolidato software di simulazione della dinamica del veicolo (VI-CarRealTime), sia attraverso simulazioni “driver-in-the-loop” utilizzando un simulatore di guida. Inoltre, la strategia proposta è stata integrata nel tool TEST per valutarne l’influenza sull’autonomia e sui consumi del veicolo. Gli strumenti sopra menzionati sono stati utilizzati per studiare uno scenario di casi reali, per valutare la fattibilità dell’utilizzo di una flotta alimentata a fuel cell a metano per svolgere attività di raccolta rifiuti porta a porta. I risultati mostrano un’elevata fattibilità in termini di autonomia del veicolo rispetto alle missioni standard di raccolta dei rifiuti, a condizione che i componenti siano adeguatamente dimensionati. Il dimensionamento dei componenti è stato effettuato attraverso iterazioni, utilizzando diversi componenti nelle stesse missioni. Infine, è stata riportata un’analisi approfondita degli studi LCA (Life Cycle Assessment) relativi ai veicoli elettrici, con particolare attenzione al pacco batterie, evidenziando alcune criticità ambientali. Questo studio sull’LCA sottolinea quindi l’importanza di una corretta gestione dell’energia per ridurre al minimo l’impatto ambientale associato al consumo stesso di energia.This PhD thesis is focused on identifying energy management strategies on board electric and hybrid vehicles, to optimize energy management and thus allow for resource savings. In fact, vehicle’s operational phase optimisation through a more efficient energy management allows main components downsizing, such as battery pack. First of all, a simulation tool called TEST (Target-speed EV Simulation Tool), is presented. This tool allows to carry out longitudinal dynamics simulations on pure electric or hybrid-electric vehicles, and therefore monitoring all the relevant data needed to carry out a proper powertrain sizing, including the electric motor(s) and the battery pack. Furthermore, several powertrain layouts can be also tested, including those using fuel cells. Then a regenerative braking strategy, suitable for FWD, RWD and AWD vehicles, is presented. Its main target is to recover the maximum possible braking energy, while keeping the vehicle stable with good braking performance. The strategy has been tested both through a state-of-art vehicle dynamics simulation software (VI-CarRealTime) and through driver-in-the-loop simulations using a driving simulator. Furthermore, the proposed strategy has been integrated into TEST to evaluate its influence on vehicle range and consumptions. The above-mentioned tools have been used to evaluate a real-world case scenario to assess the feasibility of using a methane fuel cell powered fleet to carry out door to door waste collection activities. Results show high feasibility in terms of vehicle range compared to standard waste collection missions, provided that components are properly sized. Components sizing has been done through iterations using different components on the same missions. Finally, an in-depth analysis of the LCA (Life Cycle Assessment) studies related to electric vehicles has been reported, with particular focus to the battery pack, highlighting some environmental critical issues. This LCA study therefore emphasizes the importance of a correct energy management to minimize the environmental impact associated with energy consumption