Browsing by Subject "Energy access"

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Open Access
Leveraging large-scale data for supply chain network design: a location-allocation model for Rwanda
(2024-08) Gürkan, Zeynep Göze
Clean cooking strategies are significant contributors to the enhancement of development and sustainability. Regarding the lower emission levels compared to biomass usage, we consider Liquefied Petroleum Gas (LPG) a clean cooking strategy to promote, especially in developing countries. Hence, we design large-scale supply chain operations for the LPG distribution in Rwanda. This involves addressing the location-allocation problem of facilities by utilizing a large dataset on the location and LPG demand of each rooftop by formulating a Mixed-Integer Linear Programming (MILP) model. In order to decrease the size of the problem, we propose three methods. First of all, we design the system independent of time index. Next, we use the agglomerative hierarchical clustering-based heuristic approach to cluster the rooftops and locate retailers on the distance-constrained geomedian point of each cluster. Finally, we propose to decompose the formulated MILP model to get adequate solutions in less time. For computational analysis, we compare the system configurations with different retailer locations obtained by the village centroid approach and agglomerative hierarchical clustering based-heuristic approach. In addition, we investigate whether the existing system configuration can be extended when the projected increase in yearly LPG demand is introduced. Moreover, we conduct a sensitivity analysis to show the trade-off between the infrastructure and transportation costs due to the volatility in diesel fuel prices. Finally, we compare the results and performances of the main model and the decomposed model.
Embargo
Mathematical programming models for multistage rural electrification planning: Off-grid, grid and mini-grid options
(Pergamon-Elsevier Science Ltd., 2025-02-01) Yazıcı, Gözde; Karaşan, Oya Ekin; Kocaman, Ayşe Selin; Stoner, Rob
Approximately 9% of the global population lacks access to electricity. The majority of this population resides in rural areas, highlighting the critical importance of rural electrification efforts. In this study, we introduce novel mathematical programming models aimed at addressing the technology choice and network design challenges in rural electrification. These models determine the optimal electrification technology among off- grid, grid and mini-grid options for each demand point while designing the cost effective grid and mini-grid networks. Furthermore, we present multistage versions of these mathematical models, demonstrating the cost advantage of multistage modeling. These formulations can serve as a comprehensive framework that incorporates investment requirements for system roll-out. Through numerical experiments utilizing both real- life and synthetic instances, we offer new insights into electrification in diverse environments. Our research is expected to contribute to the socio-economic development of developing countries and aid in achieving the targets outlined in Sustainable Development Goal 7.