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利用人工神经网络优化封闭垃圾填埋场沼气燃料的能源生产:以约旦的阿尔加巴维垃圾填埋场为例

Optimization of energy production from biogas fuel in a closed landfill using artificial neural networks: A case study of Al Ghabawi Landfill, Jordan.

作者信息

Alrbai Mohammad, Abubaker Ahmad M, Darwish Ahmad Adnan, Al-Dahidi Sameer, Ayadi Osama, Hjouj Dirar, Al-Ghussain Loiy

机构信息

Department of Mechanical Engineering, School of Engineering, University of Jordan, Amman 11942, Jordan.

Mechanical Engineering Department, Villanova University, PA 19085, USA.

出版信息

Waste Manag. 2022 Aug 1;150:218-226. doi: 10.1016/j.wasman.2022.07.011. Epub 2022 Jul 18.

DOI:10.1016/j.wasman.2022.07.011
PMID:35863170
Abstract

Landfills have high potency as renewable energy sources by producing biogas from organic waste degradation. Landfills biogas (LFG) can be used for power plant purposes instead of allowing it to flare to the atmosphere which contributes to the global warming. The aim of this work was to introduce and examine an optimization model for maximizing the power generation of Al Ghabawi landfill in Amman city, Jordan. The optimization process focused on studying the effect of several operating parameters within the landfill power plant. To achieve this goal, a combustion model had been built and validated against a set of historical real data obtained from the landfill operator. In addition to that, an Artificial Neural Network (ANN) model had been built to perform a multi-objective optimization to obtain the optimal power generation conditions for Al Ghabawi landfill. The combustion model along with the ANN model aim to estimate the best engine operating conditions based on the actual daily data of the landfill. The engine operating parameters includes the intake pressure and temperature, the ignition time and the equivalence ratio. The results of the study indicate that the current operating parameters can be optimized to maximize the gensets power generation. Based on the daily data of the produced LFG, the optimal operating conditions for the landfill are 2.32 bar for the intake pressure, 303 K for the intake temperature, 0.9-1.0 for the equiveillance ratio and for the ignition time it is 13 degrees before the top dead center (BTDC). These optimized operating parameters can maximize the landfill power generation by at least 1 MW for each genset.

摘要

通过有机废物降解产生沼气,垃圾填埋场作为可再生能源具有很高的潜力。垃圾填埋场沼气(LFG)可用于发电厂,而不是任其燃烧排放到大气中,因为这会加剧全球变暖。这项工作的目的是引入并研究一个优化模型,以实现约旦安曼市Al Ghabawi垃圾填埋场发电量的最大化。优化过程聚焦于研究垃圾填埋场发电厂内多个运行参数的影响。为实现这一目标,建立了一个燃烧模型,并根据从垃圾填埋场运营商获得的一组历史实际数据进行了验证。此外,还建立了一个人工神经网络(ANN)模型来进行多目标优化,以获得Al Ghabawi垃圾填埋场的最佳发电条件。燃烧模型与ANN模型旨在根据垃圾填埋场的实际日数据估算最佳发动机运行条件。发动机运行参数包括进气压力和温度、点火时间和当量比。研究结果表明,当前的运行参数可以进行优化,以实现发电机组发电量的最大化。根据所产生的LFG的日数据,该垃圾填埋场的最佳运行条件为:进气压力2.32巴,进气温度303开尔文,当量比0.9 - 1.0,点火时间为上止点前13度(BTDC)。这些优化后的运行参数可使每个发电机组的垃圾填埋场发电量至少最大化1兆瓦。

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