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Modelling Smart Electrification Focusing on sub-Saharan Africa

Modelling Smart Electrification Focusing on sub-Saharan Africa. Manuel Welsch, 23 March 2011. Modelling Smart Grid Electrification. Rationale. Lack of access: in 2009, 70% of the population in sub-Saharan Africa (SSA) did not have access to electricity (IEA, 2010).

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Modelling Smart Electrification Focusing on sub-Saharan Africa

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  1. Modelling Smart Electrification Focusing on sub-Saharan Africa Manuel Welsch, 23 March 2011

  2. Modelling Smart Grid Electrification Rationale • Lack of access: in 2009, 70% of the population in sub-Saharan Africa (SSA) did not have access to electricity (IEA, 2010). • Importance of electrification is well understood at national and global level • Significant opportunities: limited legacy of infrastrucure and regulation may allow for radical departure from traditional approaches. Need to avoid technology lock. • Current Smart Grids discourse: largely focused on industrialised countries, but many potential benefits equally valid for SSA.

  3. Modelling Smart Grid Electrification Rationale • Smart Grids for SSA: concepts and associated policies require targeted refinement to optimise the cost-benefit balance • Refined Concept provided in “Smart and Just Grids: Opportunities for sub‐Saharan Africa” (Morgan Bazilian, Manuel Welsch, Deepak Divan, David Elzinga, Goran Strbac, Mark Howells, Lawrence Jones, Andrew Keane, Dolf Gielen, V. S. K. Murthy Balijepallii, Abeeku Brew‐Hammond, and Kandeh Yumkella, 2011) • Need to underpin this refined concept: currently discussion at a conceptual level. Modelling with OSeMOSYS may help prioritise Smart Grid options and develop business case.

  4. Modelling Smart Grid Electrification Modelling Challenge • How to improve access to, and quality of, electricity in rural electrification schemes with reduced overall costs through an optimised allocation of resources. • Focus on daily operation (i.e., matching supply with daily load curve) incorporated with long term planning. • Demand side management: • Load control switches for large consumer loads • Smart Appliances • Prioritisation of consumer loads • Distributed storage: • E.g., local battery charging stations • Market approaches: • Time-of-use pricing • Low-cost electricity with reduced quality

  5. Modelling Smart Grid Electrification OSeMOSYS • Integrating the modelling objectives in OSeMOSYS: • Focus on stereotypical mini-grid electrification scheme with subsequent linkages to a national grid • Define level of flexibility in meeting specific demands • Include load prioritisation • Include storage options • Derive electricity price curve per ‚representative‘ hour and modell consumer response to price signals Contact: manuel.welsch@energy.kth.se

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