A GIS based assessment of bioenergy potential in England within existing energy systems

Thomas, Amy; Bond, Alan; Hiscock, Kevin M.

doi:10.1016/j.biombioe.2013.01.010

Cited by 60 publications

(34 citation statements)

References 49 publications

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“…GIS can support multicriteria analysis and assessment for siting wind and solar farms (Janke, 2010) and biomass plants (Perpina, et al, 2013;Hohn et al, 2014;Zhang et al, 2011;Ahamed et al, 2011). It can also support the evaluation of potential renewable energy from installed developments in relation to solar and wind potential (Erdinc and Uzunoglu, 2012) and biomass potential from energy crops on a regional scale (Fiorese and Guariso, 2010;Thomas et al, 2013;Hammer et al, 2003;Larsson and Nilsson, 2005;Nygaard et al, 2010).…”

Section: Remote Sensing and Gis-based Methodsmentioning

confidence: 99%

Multicriteria analysis for sources of renewable energy using data from remote sensing

Matějı́ček

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Renewable energy sources are major components of the strategy to reduce harmful emissions and to replace depleting fossil energy resources. Data from remote sensing can provide information for multicriteria analysis for sources of renewable energy. Advanced land cover quantification makes it possible to search for suitable sites. Multicriteria analysis, together with other data, is used to determine the energy potential and socially acceptability of suggested locations. The described case study is focused on an area of surface coal mines in the northwestern region of the Czech Republic, where the impacts of surface mining and reclamation constitute a dominant force in land cover changes. High resolution satellite images represent the main input datasets for identification of suitable sites. Solar mapping, wind predictions, the location of weirs in watersheds, road maps and demographic information complement the data from remote sensing for multicriteria analysis, which is implemented in a geographic information system (GIS). The input spatial datasets for multicriteria analysis in GIS are reclassified to a common scale and processed with raster algebra tools to identify suitable sites for sources of renewable energy. The selection of suitable sites is limited by the CORINE land cover database to mining and agricultural areas. The case study is focused on long term land cover changes in the 1985-2015 period. Multicriteria analysis based on CORINE data shows moderate changes in mapping of suitable sites for utilization of selected sources of renewable energy in 1990, 2000, 2006 and 2012. The results represent map layers showing the energy potential on a scale of a few preference classes (1-7), where the first class is linked to minimum preference and the last class to maximum preference. The attached histograms show the moderate variability of preference classes due to land cover changes caused by mining activities. The results also show a slight increase in the more preferred classes for utilization of sources of renewable energy due to an increase area of reclaimed sites. Using data from remote sensing, such as the multispectral images and the CORINE land cover datasets, can reduce the financial resources currently required for finding and assessing suitable areas.* Corresponding author. This is useful to know for communication with the appropriate person in cases with more than one author.

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Section: Remote Sensing and Gis-based Methodsmentioning

confidence: 99%

Multicriteria analysis for sources of renewable energy using data from remote sensing

Matějı́ček

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…With the application of GIS software (e.g., Esri ArcGIS® buffer tool), many assessments use a circular based configuration for the catchment area of a bioenergy plant, with the radius of the circle used to estimate the transport distance to the plant [70][71][72]. The calculation of this radial transport distance can be based on simple demand-supply properties (i.e., x tonnes of biomass required and it takes y number of hectares with a yield z), or more advanced calculations using the approach of [73].…”

Section: What Is Relca?mentioning

confidence: 99%

RELCA: a REgional Life Cycle inventory for Assessing bioenergy systems within a region

O’Keeffe¹,

Wochele-Marx²,

Thrän

2016

Energ Sustain Soc

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Background: The last decade has seen major development and adoption of bioenergy, particularly in Germany. This has resulted in a scattering of decentralised bioenergy plants across the landscape, due to their dependency on spatially diffuse biomass resources. Regional conditions (e.g., soils, climate, management) influence the environmental burdens resulting from biomass production and thus, also effect the environmental performance of bioenergy production. Therefore, more regionally focused life cycle approaches are required for assessing these bioenergy systems. The aim of this paper is to outline such an approach. "RELCA", is a regional life cycle inventory for assessing the regional and spatial variation in the environmental performance of bioenergy production within a region. Methods: Five modelling steps are combined to form the RELCA approach in order to determine: (1) regional crop allocation, (2) regional biomass management, (3) representative bioenergy plant models, (4) bioenergy plant catchments, and (5) indirect upstream emissions (non-regional) associated with regional bioenergy production. The challenges and options for each of these five modelling steps are outlined. Additionally, a simple example is provided using greenhouse gases emissions (GHG) to show how RELCA can be used to identify the potential regional distribution of environmental burdens associated with the production of a bioenergy product (e.g. biodiesel) within a region. Results: An approach for combining regionally distributed inventory for biomass production with regionally distributed inventory for bioenergy technologies, through the use of catchment delineation was developed. This enabled the introduction of greater regional details within the life cycle approach. As a first "proof of concept," GHG emissions were estimated for a simple example, illustrating how RELCA can identify the potential regional distribution of environmental burdens (direct and indirect) associated with producing a bioenergy product. Conclusions: RELCA (v1.0) is a powerful scoping approach, which is the first to investigate the regional and spatial variation in the environmental performance of bioenergy production within a region through the use of catchment delineation. RELCA (v1.0) is not without its limitations. Despite these, it still provides a good starting point for further discussion, improvements, and modelling developments for assessing the regional and spatial environmental implications of bioenergy production (e.g., such as impacts to soil, water, and biodiversity) for a within regional context .

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“…Therefore, careful evaluation of the agronomic environment is required; mainly in regards of the quantity of straw to be left in each area, once it supports decisionmaking on the amount of nutrients and additives required for a new sugarcane cycle (TRIVELIN et al, 2013). Besides this, the logistic planning of the mill-field-mill route, seeking to optimize the recovery process, enables to select which straw recovery route will be used for each sugarcane area.…”

Section: Production Chain Of Sugarcane Straw To Electricitymentioning

confidence: 99%

Identification, assessment and ordering of concepts for agro-energy planning and possibilities of spatial analysis

et al. 2015

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ABSTRACT:The present study aims to present the main concepts of the sugarcane straw to energy planning. Throughout the study, the subject is contextualized highlighting broader aspects of sustainability, which is considered the main driver towards agro-energy modernization. Concerning sugarcane straw, we first evaluated its availability regarding technical and economic aspects, and then it summarized the straw production chain for energy supply purposes. As a proposal to support agro-energy planning, it is presented some spatial tools that have been barely used in the Brazilian energy planning context so far. Therefore, working on straw to electricity associated with supply chain basis, we developed a conceptual model to spatially assess this bioenergy system. Using the model proposed, it is described the whole supply chain at state level, which accounted the potential of a single mill to explore straw, as well as main costs associated with straw acquisition, investments on the straw recovery routes and electricity transmission. Bearing these concepts in mind, it is fully believed that spatial analysis can bring important information for agro-energy action plans.KEYWORDS: sugarcane, straw, agro-energy planning, geographic information system. IDENTIFICAÇÃO, AVALIAÇÃO E ORDENAMENTO DE CONCEITOS PARA O PLANEJAMENTO AGROENERGÉTICO E AS POSSIBILIDADES DA ANÁLISE ESPACIALRESUMO: O presente artigo busca apresentar os principais conceitos envolvendo um planejamento energético específico da palha da cana-de-açúcar. Ao longo do trabalho, procurou-se contextualizar o tema por meio de questões de sustentabilidade, considerada um dos principais indutores em direção à modernização da agroenergia. Considerando a palha da cana de açúcar, avaliou-se primeiramente sua disponibilidade envolvendo aspetos técnicos e econômicos, e posteriormente caracterizou-se a cadeia de produção da palha para energia. Como proposta para auxílio ao planejamento agroenergetico, apresentou-se algumas ferramentas espaciais que até então pouco têm sido utilizadas para planejamento energético no Brasil. Deste modo, trabalhando o potencial de palha para eletricidade associado à sua cadeia de produção, desenvolveu-se um modelo conceitual para se avaliar espacialmente esse sistema bioenergético. Utilizando o modelo proposto, foi possível descrever toda a cadeia de produção da palha para energia em um nível estadual, envolvendo o potencial que cada usina pode explorar, bem como os principais custos associados à sua aquisição, investimentos relacionados à rota de recuperação e em linhas de transmissão. Por meio dos conceitos abordados, acredita-se que análise espacial pode trazer importantes informações para planos de ação no âmbito agroenergético. PALAVRAS-CHAVE:cana-de-açúcar, palha, planejamento energético, sistema de informação geográfica.Identification, assessment and ordering of concepts for agro-energy planning and possibilities of sp atial analysisEng.

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A GIS based assessment of bioenergy potential in England within existing energy systems

Cited by 60 publications

References 49 publications

Multicriteria analysis for sources of renewable energy using data from remote sensing

Multicriteria analysis for sources of renewable energy using data from remote sensing

RELCA: a REgional Life Cycle inventory for Assessing bioenergy systems within a region

Identification, assessment and ordering of concepts for agro-energy planning and possibilities of spatial analysis

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