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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Energy efficiency improvements by investigating the water flooding management on proton exchange membrane fuel cell (PEMFC)
Oluwatosin Ijaodola,Zaki El Hassan,Emmanuel Ogungbemi,F.N. Khatib,Tabbi Wilberforce,James Thompson,Abdul Ghani Olabi,Abdul Ghani Olabi +7 more
TL;DR: In this article, a broad study of research work associated with the effect of water flooding and management in Proton Exchange Membrane Fuel Cells (PEMFC) is presented, which operates at relatively low temperatures at conditions that could allow the accumulation of water that degrade cell performance.
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Two stage forecast engine with feature selection technique and improved meta-heuristic algorithm for electricity load forecasting
TL;DR: A hybrid forecast strategy including novel feature selection technique, and a complex forecast engine based on a new intelligent algorithm to improve its accuracy and capability is proposed for short-term load forecasting of electricity load.
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A New Meta-Heuristic Optimization Algorithm Inspired by FIFA World Cup Competitions: Theory and Its Application in PID Designing for AVR System
TL;DR: The main objective of the proposed system is to minimize the steady-state error and also to improve the transient response of the AVR system by optimal PID controller by WCO algorithm.
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Parameter optimization for a PEMFC model with a hybrid genetic algorithm
TL;DR: In this article, an electrochemical-based fuel cell model suitable for engineering optimization is presented and optimized by means of a niche hybrid genetic algorithm (HGA) by using stack outputvoltage, stack demand current, anode pressure and cathode pressure as input-output data.
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RETRACTED: Risk-assessment of photovoltaic-wind-battery-grid based large industrial consumer using information gap decision theory
TL;DR: In this article, the energy procurement problem for a large electricity consumer is solved under various resources and the results of information gap decision theory are presented in three different strategies for the large consumer.