EconPapers    
Economics at your fingertips  
 

Facility location allocation modelling for bio-energy system in Anambra State of Nigeria: Integration of GIS and location model

E.c Chukwuma

Renewable Energy, 2019, vol. 141, issue C, 460-467

Abstract: The adoption of appropriate waste management strategy has been considered as a lasting solution to part of the environmental problems facing Anambra State of Nigeria. Implementation of spatial information technologies such as Remote Sensing (RS) and Geographic Information System (GIS) in addressing the issue of waste management has been identified as an appropriate technology. The limitations of the use of GIS alone or only location mathematical models in effective suitability analysis has been observed by many researchers, therefore this study adopted the integration of geospatial technology with Set Cover Location Model (SCLM) and facility location allocation modelling as a holistic approach to the problem. The result of the study shows that a minimum of three biogas processing plants is needed to maximally process all the wastes in the study area. The output of the allocation and location model shows that a processing plant with about 5.6 Tons, 1.7 Tons and 57 Tons capacity is best located at Ajali, Ihiala and Abagana towns respectively in the study area. It is recommended that strategic waste management approach as used in this study will be a veritable tool for energy solution in the study area.

Keywords: GIS; Set cover location modelling; Centralized biogas plant; Location/allocation model; Agricultural wastes (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148119305051
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:141:y:2019:i:c:p:460-467

DOI: 10.1016/j.renene.2019.04.022

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:renene:v:141:y:2019:i:c:p:460-467