System identification of PEM fuel cells using an improved Elman neural network and a new hybrid optimization algorithm
Dongmin Yu,Dongmin Yu,Yong Wang,Yong Wang,Huanan Liu,Huanan Liu,Kittisak Jermsittiparsert,Navid Razmjooy +7 more
TLDR
An optimized improved Elman neural network based on a new hybrid optimization algorithm is proposed for increasing their efficiency in the next designs of the proton exchange membrane fuel cell.About:
This article is published in Energy Reports.The article was published on 2019-11-01 and is currently open access. It has received 132 citations till now. The article focuses on the topics: Hybrid algorithm & System identification.read more
Citations
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Optimal parameter identification of PEMFC stacks using Adaptive Sparrow Search Algorithm
Yanlong Zhu,Nasser Yousefi +1 more
TL;DR: The proposed ASSA is utilized for minimizing the sum of squared error (SSE) between the empirical stack voltage and the calculated stack voltage by optimal selection of the mentioned parameters in the PEMFC stack.
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A new technique for optimal estimation of the circuit-based PEMFCs using developed Sunflower Optimization Algorithm
TL;DR: A newly developed model of the Sunflower Optimization Algorithm (DSFO) is proposed for minimizing the sum of squared error (SSE) value between the estimated and the actual output voltage of the PEMFC stack.
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Multi-objective optimization for the proper selection of the best heat pump technology in a fuel cell-heat pump micro-CHP system
TL;DR: In this article, a multi-objective technique has been proposed for optimal analysis of three different candidate heat pump solutions including the vapor compression cycle (VCC), trans-critical R744 cycle, and Peltier device to determine which one gives the best configuration and better performance on a hybrid heat pump and fuel cell-based micro-CHP system.
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Optimal structure design of a PV/FC HRES using amended Water Strider Algorithm
TL;DR: In this article, an off-grid combined renewable energy system (HRES) by photovoltaic (PV) and fuel cell (FC) systems is proposed to provide electricity for a remote area in Jiaju Tibetan Village, Danba, Sichuan Province China The main idea is formulated according to the Total Annual Cost (TAC).
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Matching Model of Energy Supply and Demand of the Integrated Energy System in Coastal Areas
TL;DR: In this article, a matching model of energy supply and demand of the integrated energy system in coastal areas in the United States was constructed by using the matching relationship between energy supply-demand, so as to complete the matching of the matching.
References
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Diagnosis of polymer electrolyte fuel cells failure modes (flooding & drying out) by neural networks modeling
TL;DR: This paper presents a diagnosis procedure of water management issues in fuel cell, namely flooding and drying out, based on a limited number of parameters that are, besides, easy-to-monitor.
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A Hybrid Neural Network - World Cup Optimization Algorithm for Melanoma Detection.
TL;DR: A new efficient method to detect malignancy in melanoma via images using multi-layer perceptron network and WCO algorithm, which attempts to minimize the root mean square error.
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A New Formulation to Reduce the Number of Variables and Constraints to Expedite SCUC in Bulky Power Systems
TL;DR: The SCUC results drawn using the proposed algorithms are compared with those obtained by a conventional MIP-based algorithm to show the effectiveness of the proposed algorithm.
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Optimal offering and bidding strategies of renewable energy based large consumer using a novel hybrid robust-stochastic approach
Oveis Abedinia,Mohsen Zareinejad,Mohammad Hossein Doranehgard,Gholamreza Fathi,Noradin Ghadimi +4 more
TL;DR: A linear model with integer variables is developed to derive offering and bidding curves, which are robust against the uncertainty associated with the load demand of the large consumer, and results show that the higher amount of uncertain parameter is considered, the higher procurement price has resulted for theLarge consumer.
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A novel chaotic image encryption algorithm based on improved baker map and logistic map
TL;DR: A novel image encryption algorithm based on double chaotic systems, using the two-dimensional Baker chaotic map to control the system parameters and the state variable of the logistic chaotic map, which has been proven to be random and unpredictable by complexity analysis.