确定新南威尔士州生物能源潜在生物质利用的新工具

J. Perraud, R. Bridgart, Catherine Carney, F. Ximenes
{"title":"确定新南威尔士州生物能源潜在生物质利用的新工具","authors":"J. Perraud, R. Bridgart, Catherine Carney, F. Ximenes","doi":"10.36334/modsim.2023.perraud379","DOIUrl":null,"url":null,"abstract":": Australia is in the bottom quartile of OECD countries in using bioenergy as a proportion of total energy supply. A lack of reliable information about underutilised biomass feedstocks was identified as a significant roadblock to the development of bioenergy projects across Australia. Existing biomass resources derived from various sources were mapped in New South Wales, Australia as part of the Australian Biomass for Bioenergy Assessment Project. A parallel project is trialling the establishment of Australian native species as short-rotation biomass crops. Focussing for now on the available data for New South Wales (https://www.dpi.nsw.gov.au/forestry/science/forest-carbon/biomass-for-bioenergy) we have implemented a software product and web browser tool to facilitate the exploitation of this data. This is a tool for a spectrum of users who want to rapidly obtain aggregate information and explore scenarios for the use of biomass, notably but not limited to energy supply. Two categories of sources of biomass are conceptualised: agricultural, forestry and other residues, and the plantation of energy crops in marginal or degraded land areas. Users can define geographic or point areas as sources of feedstocks, transport and pelletisation hubs, power plants such as a biomass power stations or hybrid solar-biomass plants, and linkages between these nodes (Figure 1). From the defined geographic extents of interest, the tool queries the spatial layers from an ArcGIS server to obtain the potential available biomass for each crop type and biomass productivity from woody biomass crops. Users can optionally adjust values and attributes such as moisture content and energy density. Additional custom feedstock types can be defined. Scenarios can be saved as files to the desktop. The types of outputs reported for a scenario include the carbon footprint and cost of transport, or which size of power plant is feasible given the available biomass of a scenario and the characteristics of the solar irradiation for a hybrid solar-biomass plant. It is also easy to produce the amount of avoided equivalent carbon footprint from a fossil fuel such as coal. The tool is built mostly with Python. Two packages contain respectively the domain logic and user interface components. The domain package features a data model that consistently handles biomass feedstocks throughout the system, to avoid possible confusions such as wet and dry masses in calculations. The web front-end is built using Jupyter notebooks and the packages ipywidgets and jupyter-flex to work via a web browser. The web application is currently available as a testing site with an access restricted to testers and key stakeholders. The broader vision for this activity is an evolvable software infrastructure for holistic, large-scale assessment of projects using biomass including their engineering, economic and environmental aspects. We are considering opportunities to use this software as an integration platform for other emerging activities exploring ways to transition to a system with a net zero carbon footprint.","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new tool for determining potential biomass use for bioenergy in New South Wales\",\"authors\":\"J. Perraud, R. Bridgart, Catherine Carney, F. Ximenes\",\"doi\":\"10.36334/modsim.2023.perraud379\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": Australia is in the bottom quartile of OECD countries in using bioenergy as a proportion of total energy supply. A lack of reliable information about underutilised biomass feedstocks was identified as a significant roadblock to the development of bioenergy projects across Australia. Existing biomass resources derived from various sources were mapped in New South Wales, Australia as part of the Australian Biomass for Bioenergy Assessment Project. A parallel project is trialling the establishment of Australian native species as short-rotation biomass crops. Focussing for now on the available data for New South Wales (https://www.dpi.nsw.gov.au/forestry/science/forest-carbon/biomass-for-bioenergy) we have implemented a software product and web browser tool to facilitate the exploitation of this data. This is a tool for a spectrum of users who want to rapidly obtain aggregate information and explore scenarios for the use of biomass, notably but not limited to energy supply. Two categories of sources of biomass are conceptualised: agricultural, forestry and other residues, and the plantation of energy crops in marginal or degraded land areas. Users can define geographic or point areas as sources of feedstocks, transport and pelletisation hubs, power plants such as a biomass power stations or hybrid solar-biomass plants, and linkages between these nodes (Figure 1). From the defined geographic extents of interest, the tool queries the spatial layers from an ArcGIS server to obtain the potential available biomass for each crop type and biomass productivity from woody biomass crops. Users can optionally adjust values and attributes such as moisture content and energy density. Additional custom feedstock types can be defined. Scenarios can be saved as files to the desktop. The types of outputs reported for a scenario include the carbon footprint and cost of transport, or which size of power plant is feasible given the available biomass of a scenario and the characteristics of the solar irradiation for a hybrid solar-biomass plant. It is also easy to produce the amount of avoided equivalent carbon footprint from a fossil fuel such as coal. The tool is built mostly with Python. Two packages contain respectively the domain logic and user interface components. The domain package features a data model that consistently handles biomass feedstocks throughout the system, to avoid possible confusions such as wet and dry masses in calculations. The web front-end is built using Jupyter notebooks and the packages ipywidgets and jupyter-flex to work via a web browser. The web application is currently available as a testing site with an access restricted to testers and key stakeholders. The broader vision for this activity is an evolvable software infrastructure for holistic, large-scale assessment of projects using biomass including their engineering, economic and environmental aspects. We are considering opportunities to use this software as an integration platform for other emerging activities exploring ways to transition to a system with a net zero carbon footprint.\",\"PeriodicalId\":390064,\"journal\":{\"name\":\"MODSIM2023, 25th International Congress on Modelling and Simulation.\",\"volume\":\"98 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MODSIM2023, 25th International Congress on Modelling and Simulation.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36334/modsim.2023.perraud379\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MODSIM2023, 25th International Congress on Modelling and Simulation.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36334/modsim.2023.perraud379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在使用生物能源占总能源供应的比例方面,澳大利亚在经合组织国家中处于最低的四分之一。缺乏关于未充分利用的生物质原料的可靠信息被认为是澳大利亚生物能源项目发展的一个重大障碍。作为澳大利亚生物质能评估项目的一部分,在澳大利亚新南威尔士州绘制了来自各种来源的现有生物质资源的地图。一个平行的项目正在试验建立澳大利亚本地物种作为短期轮作生物量作物。目前,我们主要关注新南威尔士州的可用数据(https://www.dpi.nsw.gov.au/forestry/science/forest-carbon/biomass-for-bioenergy),我们已经实施了一个软件产品和网络浏览器工具,以促进对这些数据的利用。这是一种工具,适用于希望快速获取汇总信息和探索生物质使用场景的用户,特别是但不限于能源供应。概念化了两类生物量来源:农业、林业和其他残留物,以及在边缘或退化土地地区种植能源作物。用户可以将地理或点区域定义为原料来源、运输和颗粒化中心、发电厂(如生物质发电站或混合太阳能-生物质发电厂)以及这些节点之间的联系(图1)。根据已定义的地理范围,该工具从ArcGIS服务器查询空间层,以获得每种作物类型的潜在可用生物量和木质生物质作物的生物量生产力。用户可以选择调整数值和属性,如水分含量和能量密度。可以定义其他自定义原料类型。场景可以以文件的形式保存到桌面。为某一设想所报告的产出类型包括碳足迹和运输费用,或考虑到某一设想的可利用生物量和混合太阳能-生物质能工厂的太阳辐照特性,何种规模的发电厂是可行的。从煤炭等化石燃料中也很容易产生避免等量的碳足迹。该工具主要使用Python构建。两个包分别包含域逻辑和用户界面组件。领域包的特点是一个数据模型,在整个系统中始终如一地处理生物质原料,以避免可能的混淆,如计算中的湿质量和干质量。web前端是使用Jupyter笔记本和ipywidgets和Jupyter -flex包构建的,可以通过web浏览器工作。web应用程序目前是一个测试站点,只有测试人员和关键涉众才能访问。这项活动的更广泛的愿景是一个可进化的软件基础设施,用于全面、大规模地评估使用生物质的项目,包括其工程、经济和环境方面。我们正在考虑使用该软件作为其他新兴活动的集成平台,探索过渡到净零碳足迹系统的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A new tool for determining potential biomass use for bioenergy in New South Wales
: Australia is in the bottom quartile of OECD countries in using bioenergy as a proportion of total energy supply. A lack of reliable information about underutilised biomass feedstocks was identified as a significant roadblock to the development of bioenergy projects across Australia. Existing biomass resources derived from various sources were mapped in New South Wales, Australia as part of the Australian Biomass for Bioenergy Assessment Project. A parallel project is trialling the establishment of Australian native species as short-rotation biomass crops. Focussing for now on the available data for New South Wales (https://www.dpi.nsw.gov.au/forestry/science/forest-carbon/biomass-for-bioenergy) we have implemented a software product and web browser tool to facilitate the exploitation of this data. This is a tool for a spectrum of users who want to rapidly obtain aggregate information and explore scenarios for the use of biomass, notably but not limited to energy supply. Two categories of sources of biomass are conceptualised: agricultural, forestry and other residues, and the plantation of energy crops in marginal or degraded land areas. Users can define geographic or point areas as sources of feedstocks, transport and pelletisation hubs, power plants such as a biomass power stations or hybrid solar-biomass plants, and linkages between these nodes (Figure 1). From the defined geographic extents of interest, the tool queries the spatial layers from an ArcGIS server to obtain the potential available biomass for each crop type and biomass productivity from woody biomass crops. Users can optionally adjust values and attributes such as moisture content and energy density. Additional custom feedstock types can be defined. Scenarios can be saved as files to the desktop. The types of outputs reported for a scenario include the carbon footprint and cost of transport, or which size of power plant is feasible given the available biomass of a scenario and the characteristics of the solar irradiation for a hybrid solar-biomass plant. It is also easy to produce the amount of avoided equivalent carbon footprint from a fossil fuel such as coal. The tool is built mostly with Python. Two packages contain respectively the domain logic and user interface components. The domain package features a data model that consistently handles biomass feedstocks throughout the system, to avoid possible confusions such as wet and dry masses in calculations. The web front-end is built using Jupyter notebooks and the packages ipywidgets and jupyter-flex to work via a web browser. The web application is currently available as a testing site with an access restricted to testers and key stakeholders. The broader vision for this activity is an evolvable software infrastructure for holistic, large-scale assessment of projects using biomass including their engineering, economic and environmental aspects. We are considering opportunities to use this software as an integration platform for other emerging activities exploring ways to transition to a system with a net zero carbon footprint.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Modelling of the activated sludge process with a stratified settling unit Recent changes in the water and ecological condition at the arid Tarim River Basin A study on internal observation of vertical protective nets of temporary structures using image processing techniques Developing synthetic datasets for reef modelling Modelling hydrological impact of remotely sensed vegetation change
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1