In April, Ayse Selin Kocaman, a Ph.D. student in the Modi Research Group, was awarded with first place in the 2011 Production and Operations Management Society (POMS) College of Sustainable  Operations Ph.D. Proposal Award Competition with her dissertation titled “Connecting People to Electricity- Single Level and Multi-Level Grid Network Design for Rural Electrification.”

In a technological landscape that is altered by emergence of off-grid and distributed approaches, there is a need amongst infrastructure planners to evaluate the costs of networked approaches vis a vis off-grid approaches and to make rapid assessment of the progress in rural electrification. However, it is not easy to estimate the cost of networked infrastructure taking into account both the spatial distribution of demand and the optimal placement of infrastructure to meet that demand. Through its algorithms, Selin’s proposal can enable the tools that allow planners to make assessments about networked infrastructure rapidly and accurately.

The first heuristic algorithm, Selin proposes, provides a quick solution for the partial electrification problem where the grid network can only connect pre-specified number of households with low voltage lines. It also, helps understanding the effect of household settlement patterns on the electrification cost. Moreover, she describes the first multi-level heuristic algorithm that can simultaneously select the locations and service areas of transformers without requiring candidate locations and builds network in both medium voltage and low voltage levels in a power distribution system. The algorithm minimizes overall infrastructure costs while considering the cost of the transformer, the costs of building out low voltage line downstream towards the spatially distributed demand and medium voltage line upstream towards the source.

The algorithms have been applied to real world rural settings in Africa, where household locations digitized from satellite imagery are prescribed. Results shows that the algorithms provide stable network designs with realistic values and they can be used as powerful tools by planners to rapidly estimate the cost of installing a distribution system.