How effective are heuristic solutions for electricity planning in developing countries

Yakubu Abdul-Salam, Euan Phimister

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Heuristic algorithms have been widely used to provide computationally feasible means of exploring the cost effective balance between grid versus off grid sources for universal electrification in developing countries. By definition in such algorithms however, global optimality is not guaranteed. We present a computationally intensive but globally optimal mixed integer non-linear programming (MINLP) model for electricity planning and use it in a Monte Carlo simulation procedure to test the relative performance of a widely used heuristic algorithm due to [28]. We show that the overall difference in cost is typically small suggesting that the heuristic algorithm is generally cost effective in many situations. However we find that the relative performance of the heuristic algorithm deteriorates with increasing degree of spatial dispersion of unelectrified settlements, as well as increasing spatial remoteness of the settlements from the grid network, suggesting that the effectiveness of the heuristic algorithm is context specific. Further, we find that allocation of off grid sources in the heuristic algorithm solution is often significantly greater than in the MINLP model suggesting that heuristic methods can overstate the role of off-grid solutions in certain situations.
Original languageEnglish
Pages (from-to)14-24
Number of pages11
JournalSocio-Economic Planning Sciences
Volume55
Early online date28 Apr 2016
DOIs
Publication statusPublished - Sep 2016

Keywords

  • Algorithms
  • Electricity
  • Grid/off-grid
  • Mixed integer programming
  • Monte Carlo simulation
  • Parshall et al. algorithm

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