Abstract

Rapid growth of population, industrialization, and rise in living standards of communities has resulted in increasing environmental pollution and loss of natural resources, but also in the inaccessibility to quality energy services, especially the most and highly desired electricity particularly for majority of the population living in remote areas. So, in a bid to respond and tackle both at the same time, the challenges of lack of access to quality energy services and improper management and disposal of Municipal Solid Waste (MSW); a renewed awareness of renewable energies and best practice of Municipal Solid Waste (MSW) has to be created. In fact, the utilization of LFG for energy production, especially based on stand-Alone mini-grids or off-grids configurations is part of the growing complexity which contributes and plays a major role in promoting renewable energy for poverty alleviation, allowing economic growth in an environmentally friendly and responsible way. Following and going alongside the first paper previously developed which dealt with the technical, economic, and environmental assessment of deploying a Landfill Gas to Energy (LFGTE) generation system; the work in this paper develops and presents a comparative study of two different stand-alone schemes based on landfill gas to energy projects which are basically a Simple Stand-Alone system and Combined Heat and Power Stand-Alone system. However, the comparative study referred to in this research work is done by means of an economic assessment using the Hybrid Optimization Model for Electric Renewables (HOMER) software in order to develop the cost optimization analysis. In fact, the cost optimization analysis performed in this paper is based at first on the Net Present Cost (NPC) since this cost represents the total cost of the project including all cost components such as operational and maintenance (O&M), replacement, total capital cost, etc. and finally on the Cost of Energy (COE). The cost for the two configuration systems earlier mentioned are optimized, compared, and analyzed.

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