Decentralized Control of Solid Oxide Fuel Cells

Sendjaja, Antonius Yudi; Kariwala, Vinay

doi:10.1109/tii.2010.2097601

Cited by 44 publications

(31 citation statements)

References 33 publications

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“…SOFC has been used in this study, which enjoys high efficiency and thermal robustness for high power systems. A perfect model of solid oxide fuel cell described in [24] is utilized in this study. The relationships between these parameters are given in [25].…”

Section: Fuel Cellmentioning

confidence: 99%

Optimized Fuzzy-Cuckoo Controller for Active Power Control of Battery Energy Storage System, Photovoltaic, Fuel Cell and Wind Turbine in an Isolated Micro-Grid

2017

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This paper presents a new control strategy for isolated micro-grids including wind turbines (WT), fuel cells (FC), photo-voltaic (PV) and battery energy storage systems (BESS). FC have been used in parallel with BESSs in order to increase their lifetime and efficiency. The changes in some parameters such as wind speed, sunlight, and consumption, lead to improper performance of droop. To overcome this challenge, a new intelligent method using a combination of fuzzy controller and cuckoo optimization algorithm (COA) techniques for active power controllers in isolated networks is proposed. In this paper, COA is compared with genetic algorithm (GA) and particles swarm optimization algorithm (PSO). In order to show efficiency of the proposed controller, this optimal controller has been compared with droop, optimized droop, and conventional fuzzy methods, the dynamic analysis of the island is implemented to assess the behavior of isolated generations accurately and simulation results are reported.

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Section: Fuel Cellmentioning

confidence: 99%

Optimized Fuzzy-Cuckoo Controller for Active Power Control of Battery Energy Storage System, Photovoltaic, Fuel Cell and Wind Turbine in an Isolated Micro-Grid

2017

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“…The dynamic model adopted for the SOFC [17,18] is based on the relationship between the FC output voltage Vfc and the partial pressures of hydrogen, oxygen, and water PH2, PO2, PH2O, respectively. The SOFC terminal voltage Vfc is determined using the Nernst's equation and Ohm's law as [17,18]:…”

Section: Modeling the Solid Oxide Fuel Cellmentioning

confidence: 99%

Adaptive Neural Network-Based Control of a Hybrid AC/DC Microgrid

Chettibi

Mellit

Sulligoi

et al. 2016

IEEE Trans. Smart Grid

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-In this paper, the behavior of a grid-connected hybrid AC/DC Microgrid has been investigated. Different Renewable Energy Sources -photovoltaics modules and a wind turbine generator -have been considered together with a Solid Oxide Fuel Cell and a Battery Energy Storage System. The main contribute of this work is the design and the validation of an innovative online-trained artificial neural network based control system for a hybrid microgrid. Adaptive Neural Networks are used to track the Maximum Power Point of renewable energy generators and to control the power exchanged between the Front-End Converter and the electrical grid. Moreover, a fuzzy logic based Power Management System is proposed in order to minimize the energy purchased from the electrical grid. The operation of the hybrid microgrid has been tested in the Matlab/Simulink environment under different operating conditions. The obtained results demonstrate the effectiveness, the high robustness and the self-adaptation ability of the proposed control system. OWADAYS, the wide diffusion of distributed RES presents a new scenario for the regulation of distribution networks and the availability of new technologies for storage systems encourages their use in power systems [1]. In general, a hybrid AC/DC MG integrates different Distributed Generators (e.g. solar power sources, wind power generators, cogenerators, etc.), a energy storage system and a number of AC and DC loads. A FEC can interface the MG with the electric grid and can operate either in a grid-connected or islanded mode. The use of a PMS is crucial to optimize the power flow through the different components of the MG and the exchange of energy with the electric grid. Moreover, since the power produced by RESs depends on the climatic conditions, MPPT algorithms are needed in order to harvest the maximum available energy. The intermittent nature of RESs with the time-varying loads demand make the use of advanced control structures fundamental in order to make the operation of the MG reliable, economic, and secure under different operating conditions. The MG must also guarantee a high quality power supply to both local loads and electrical grid. Index TermsMany works have focused on hybrid microgrids and have proposed a number of control schemes for different mode of operations [2]- [8]. A multiagent-based energy management system to optimizes the economic operation of a MG is presented in [2]. A reactive power sharing algorithm in hierarchical droop control is developed in [3]. A novel coordinated voltage control scheme with islanding capability for a MG is proposed in [4]. adapt to uncertainties and they can be used also when the model of the system to be controlled is not available. Recently, the NNs with the learning capability are widely applied for the control of complex power systems. In [9], a back-propagation NN is applied for the real-time estimation of the wind speed. A novel discrete-time NN controller for the control of DC distribution system is designed in [10]. In [11], a...

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“…Sendjaja et al [3] systematically designed a simple and reliable decentralized proportional-integral-derivative (PID) controller based on a benchmark nonlinear dynamic model of SOFC. The controlled variables were maintained at constant setpoints so as to facilitate constraint satisfaction for all key variables.…”

Section: A Pid Controllersmentioning

confidence: 99%

Recent advances in industrial control

Xie

Wilamowski

2011

IECON 2011 - 37th Annual Conference of the IEEE Industrial Electronics Society

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The paper presents the state-of-the-art study on the recently published literatures subjected to industrial control in various industrial applications. Controllers are classified into several types according to different control technologies, including PID algorithm, Kalman filter, least squares regression, network-based automation, fuzzy inference systems, neural networks, radial basis function networks, sliding-mode based control and so on. For each paper, a brief summary is given to introduce the related control technologies and applications.

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Decentralized Control of Solid Oxide Fuel Cells

Cited by 44 publications

References 33 publications

Optimized Fuzzy-Cuckoo Controller for Active Power Control of Battery Energy Storage System, Photovoltaic, Fuel Cell and Wind Turbine in an Isolated Micro-Grid

Optimized Fuzzy-Cuckoo Controller for Active Power Control of Battery Energy Storage System, Photovoltaic, Fuel Cell and Wind Turbine in an Isolated Micro-Grid

Adaptive Neural Network-Based Control of a Hybrid AC/DC Microgrid

Recent advances in industrial control

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