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Planning for Large-Scale Wind and Solar Power in South Africa: Identifying Cost-Effective Deployment Strategies Using Spatiotemporal Modeling-Working Paper 340

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  • Kevin Ummel

Abstract

South Africa and many other countries hope to aggressively expand wind and solar power (WSP) in coming decades. The challenge is to turn laudable aspirations into concrete plans that minimize costs, maximize benefits, and ensure reliability. Success hinges largely on the question of how and where to deploy intermittent WSP technologies. This study develops a 10-year database of expected hourly power generation for onshore wind, solar photovoltaic, and concentrating solar power technologies across South Africa. A simple power system model simulates the economic and environmental performance of different WSP spatial deployment strategies in 2040, while ensuring a minimum level of system reliability. The results suggest that explicit optimization of the location and relative quantities of WSP technologies has the potential to significantly reduce the cost of greenhouse gas abatement compared to more conventional planning approaches. It is estimated that advanced modeling techniques could save South Africa on the order of $100 million per year (present value) by 2040. The data and techniques introduced here utilize opensource satellite data and software to minimize the cost of analysis. The approach could be translated to other contexts, providing low-cost, early-stage information to guide long-term infrastructure planning as countries prepare to exploit WSP at scale. Additional work is needed to incorporate transmission constraints and costs and embed the model in a probabilistic framework capable of identifying deployment strategies that are spatially robust to uncertainty in future technology and fuel costs.

Suggested Citation

  • Kevin Ummel, 2013. "Planning for Large-Scale Wind and Solar Power in South Africa: Identifying Cost-Effective Deployment Strategies Using Spatiotemporal Modeling-Working Paper 340," Working Papers 340, Center for Global Development.
  • Handle: RePEc:cgd:wpaper:340
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    Cited by:

    1. Madeleine McPherson & Theofilos Sotiropoulos-Michalakakos & LD Danny Harvey & Bryan Karney, 2017. "An Open-Access Web-Based Tool to Access Global, Hourly Wind and Solar PV Generation Time-Series Derived from the MERRA Reanalysis Dataset," Energies, MDPI, vol. 10(7), pages 1-14, July.
    2. Kevin Ummel & Charles Fant, 2014. "Planning for Large-Scale Wind and Solar Power in South Africa: Identifying Cost-Effective Deployment Strategies Through Spatiotemporal Modelling," WIDER Working Paper Series wp-2014-121, World Institute for Development Economic Research (UNU-WIDER).
    3. Ummel, Kevin & Fant, Charles, 2014. "Identifying cost-effective deployment strategies through spatiotemporal modelling," WIDER Working Paper Series 121, World Institute for Development Economic Research (UNU-WIDER).

    More about this item

    Keywords

    poverty; inequality; economic development;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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