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Open AccessJournal ArticleDOI

System identification of PEM fuel cells using an improved Elman neural network and a new hybrid optimization algorithm

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.
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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.

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Journal ArticleDOI

Optimal parameter identification of PEMFC stacks using Adaptive Sparrow Search Algorithm

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.
Journal ArticleDOI

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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Journal ArticleDOI

Electricity load forecasting by an improved forecast engine for building level consumers

TL;DR: A new prediction model for small scale load prediction i.e., buildings or sites is outlined, based on improved version of empirical mode decomposition (EMD) which is called sliding window EMD (SWEMD), a new feature selection algorithm and hybrid forecast engine.
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Robust optimization based optimal chiller loading under cooling demand uncertainty

TL;DR: This work proposes a robust optimization approach for uncertainty modeling of cooling demand in order to obtain robust chiller loading in the uncertain environment which cooling demand is supplied by multi-chiller system.
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Multi-objective energy management in a micro-grid

TL;DR: The MOPSO method has been used for management and optimal distribution of energy resources in proposed micro-grid and the problem was analyzed with the NSGA-II algorithm to demonstrate the efficiency of the proposed method.
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A new prediction model of battery and wind-solar output in hybrid power system

TL;DR: Short term power forecast of wind and solar power is proposed to evaluate the available output power of each production component and includes a feature selection filter and hybrid forecast engine based on neural network and an intelligent evolutionary algorithm.
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Fuzzy-based heat and power hub models for cost-emission operation of an industrial consumer using compromise programming

TL;DR: A conflict bi-objective model for cost-emission based operation of industrial consumer in the presence of peak load management is proposed and fuzzy decision making approach is provided to select the trade-off solution from the Pareto solutions.
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