A hybrid power plant (Solar-Wind-Hydrogen) model based in artificial intelligence for a remote-housing application in Mexico

被引：26

作者：

Chavez-Ramirez, A. U. ^{[1
]}

Vallejo-Becerra, V. ^{[2
]}

Cruz, J. C. ^{[3
]}

Ornelas, R. ^{[4
]}

Orozco, G. ^{[1
]}

Munoz-Guerrero, R. ^{[5
]}

Arriaga, L. G. ^{[1
]}

机构：

[1] Ctr Invest & Desarrollo Tecnol Electroquim SC, Pedro Escobedo 76703, Queretaro, Mexico

[2] Univ Autonoma Queretaro, Fac Ingn, Div Invest & Posgrad, Ctr Univ Cerro de las Campanas, Queretaro 76010, Qro, Mexico

[3] Inst Tecnol Chetumal, Div Estudios Posgrad & Invest, Chetmal 77013, Quintana Roo, Mexico

[4] Tozzi Renewable Energy SpA, I-48010 Mezzano, RA, Italy

[5] IPN, CINVESTAV, Dept Ingn Elect, Mexico City 07360, DF, Mexico

来源：

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY | 2013年 / 38卷 / 06期

关键词：

Artificial intelligence; Electrolyzer; Fuel cell; Hybrid power generation plant; Photovoltaic; Wind turbine; PEM FUEL-CELL; NEURAL-NETWORKS; ENERGY; ECONOMY; SYSTEM; FLOW;

D O I：

10.1016/j.ijhydene.2012.11.140

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

World fossil fuel reserve is expected to be exhausted in coming few decades. Therefore, the decentralization of energy production requires the design and integration of different energy sources and conversion technologies to meet the power demand for single remote housing applications in a sustainable way under various weather conditions. This work focuses on the integration of photovoltaic (PV) system, micro-wind turbine (WT), Polymeric Exchange Membrane Fuel Cell (PEM-FC) stack and PEM water electrolyzer (PEM-WE), for a sustained power generation system (2.5 kW). The main contribution of this work is the hybridization of alternate energy sources with the hydrogen conversion systems using mid-term and short-term storage models based in artificial intelligence techniques built from experimental data (measurements obtained from the site of interest), this models allow to obtain better accuracy in performance prediction (PVMSE = 8.4%, PEM-FCMSE = 2.4%, PEM-WEMSE = 1.96%, GSR(MSE) = 7.9%, WTMSE = 14%) with a practical design and dynamic under intelligent control strategies to build an autonomous system. Copyright (C) 2012, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

引用

页码：2641 / 2655

页数：15

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