How effective are heuristic solutions for electricity planning in developing countries |
| |
| Institution: | 1. The James Hutton Institute, Craigiebuckler, Aberdeen, AB15 8QH, UK;2. Aberdeen Centre for Research in Energy Economics and Finance, University of Aberdeen, Aberdee, UK;1. Rwanda Polytechnic, Rwanda;2. Department of Economics, University of Rwanda, Rwanda;3. Institute of Policy Analysis and Research (IPAR) Rwanda, Kigali, Rwanda;4. Department of Agricultural Economics, University of Rwanda, Rwanda;1. African Centre of Excellence in Energy for Sustainable Development, University of Rwanda, Kigali, Rwanda;2. School of Engineering, Howard College Campus, University of KwaZulu-Natal, Durban, South Africa;3. School of Engineering, University of Rwanda, College of Science & Technology, Rwanda;4. Department of Applied Economics, Lilongwe University of Agriculture and Natural Resources (LUANAR), Bunda College Campus, Lilongwe, Malawi;1. University of Houston, Texas, USA;2. Aalto University, Finland;3. Columbia University, USA;4. Johns Hopkins SAIS, USA |
| |
| 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. |
| |
| Keywords: | Electricity Algorithms Mixed integer programming Grid/off-grid Monte Carlo simulation Parshall et al algorithm |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
