Composition, placement, and economics of rural microgrids for ensuring sustainable development

Nearly 20% of the world's population does not have adequate access to reliable- or any- electricity, and population growth is exceeding electrification rates. The desire for power in rural and developing communities is growing continuously, and access to electricity can now be considered a necessity, not an extravagance. Lack of electrification contributes to cyclic poverty, child mortality, and hampers education, leading to an even greater divide between the developed and developing worlds. Centralized generation and distribution systems are not suited to rural areas where transmission distances are great, nor developing areas where the capital cost of large centralized generation plants is untenable. This work examines the practicality of energy production and storage, covering a large portion of the globe utilizing HOMER as an optimization tool. Multiple load profiles based on actual developing rural usage were used to create a variety of community scenarios, and the demand was optimized with a variety of generation and storage options. Every model utilizes location- based radiance, wind, and fuel prices. The goal of developing electrification is twofold: First, to provide affordable and reliable electricity, and the second is to explore every avenue of generating that electricity in an environmentally sustainable way. The sites represented in the paper- one from each country- signify communities in various states of development based on an earnings metric. Ultimately, the relative power of irradiance, wind speeds, and diesel prices can be compiled into a single index to determine whether a community should tie into the grid, or have a standalone microgrid. This break- even point from an economic standpoint is short, and favors independent microgrids in many rural areas. Additionally, whether a community should consider completely renewable energy, or mixed renewable and diesel generation sources is highly predictable based on only a few metrics, and in many circumstances, makes little impact to the levelized cost of energy. (C) 2017 Elsevier Ltd. All rights reserved.