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To grid or not to grid Vijay Modi modi@columbia.edu Professor, Earth Institute and Columbia Engineering
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80
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Ayse Selin Kocaman / ask2170@columbia.eduask2170@columbia.edu Modi Research Group
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Ayse Selin Kocaman / ask2170@columbia.eduask2170@columbia.edu Modi Research Group Sounds simple, but where exactly people live was not obvious from census data
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Ayse Selin Kocaman / ask2170@columbia.eduask2170@columbia.edu Modi Research Group Mean Cost Calculations (MID) Results for Different Dispersion of Structures
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Ruhiira, Uganda: 200 km 2, Southern Uganda (near Mbarara)
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Data Acquired for: – Households – Institutions – Commercial – Productive use Unit Type Number Education 27 Health 6 Markets 27 Grinding Mills 32 Household Clusters 399
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> 13,0000 Households (from satellite imagery) can be clustered into ~400 demand points Min # HHs = 1 Max # HHs = 253 Average = 33
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Demand Estimates: Electricity Consumption data and estimates are made for electricity demand at all points (kWh/year)
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Input data: Facilities and Household Clusters Unit Type Number Education 27 Health 6 Markets 27 Grinding Mills 32 Household Clusters 399
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Grid Connection
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Off-Grid Connection Points in darker shades are those with off-grid connection
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Percentage of Grid vs Off-Grid Coverage
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82 190 317 375 393 418 448 412 456 502 613 554
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Decision-making thru data (WB Report) Local Priorities and Constraints Roll-out plans and timelines with costing Rural and national linked
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Senegal, national planning
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Photograph Credits: Jose Barnuevo Potou cluster, SENEGAL, first Electricity for social institutions Stand-alone technologies mini-grids Local Level Planning and Priorities Grid extension
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Roll-out: By Branch (MV) Connect most cost-effective branches first Phase 1 < 20 Phase 2 20 – 25 Phase 3 > 25 Investment per capita
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Africa-Wide Transmission Scenario
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