Analysis of electrification strategies for rural renewable electrification in developing countries using agent-based models

CSS Publication Number: 
CSS21-06
Abstract: 

This paper presents an Agent-Based Model that determines the minimum cost strategy for rural electrification delivery systems and associated decentralized generation focusing entirely on renewable resources. The model creates generalized scenarios examining stakeholders' preferences for renewable resources to deploy and preferences between centralized and decentralized generation.

Literature suggests that low demand, topographical challenges and distance from the grid are the main drivers for decentralized generation. This work shows that available energy potential is an important driver as well by introducing the concepts of stress (the percentage of renewable energy potential taken up by demand) and centrality (the ratio between size of resources and average distance to demand) and demonstrating that these parameters influence the minimum cost strategy despite distance and demand.

At very low stress levels the lowest cost networks result from emphasizing decentralized generation. At stress levels above 2%, least cost delivery systems result from emphasizing grid extension of clusters created around resources with high centrality and the decentralized mix is high due to the geographical limitations of renewables. Results show that in every case, while deploying renewable energy for rural electrification, a mixture of grid extension and decentralized generation coexist for universal electrification in the least cost strategies.

Research Areas: 
Keyword: 
Rural electrification
Micro-grid modeling
Decentralized generation
Developing countries
Agent-based models
Publication Type: 
Journal Article
Energy for Sustainable Development
Date Published: 
February 9, 2021
Persistent URL: 
https://doi.org/10.1016/j.esd.2021.01.004
Full Citation: 
Alfaro, Jose F., and Shelie A. Miller. (2021) “Analysis of electrification strategies for rural renewable electrification in developing countries using agent-based models.” Energy for Sustainable Development 61: 89-103.
Admin Content
Publication Status: 
Published