Abstract
Language | English |
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Number of pages | 6 |
DOIs | |
Publication status | Published - 27 Jul 2017 |
Event | 2017 IEEE PES PowerAfrica Conference: Harnessing Energy, Information and Communications Technology (ICT) for Affordable Electrification of Africa - GIMPA Conference Centre, Accra, Ghana Duration: 27 Jun 2017 → 30 Jun 2017 http://sites.ieee.org/powerafrica/ |
Conference
Conference | 2017 IEEE PES PowerAfrica Conference |
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Country | Ghana |
City | Accra |
Period | 27/06/17 → 30/06/17 |
Internet address |
Fingerprint
Keywords
- mini grids
- renewable energy
- sustainability
- rural electrification
- Africa
- India
Cite this
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Optimized network planning of mini-grids for the rural electrification of developing countries. / Nolan, Steven; Strachan, Scott; Rakhra, Puran; Frame, Damien.
2017. Paper presented at 2017 IEEE PES PowerAfrica Conference, Accra, Ghana.Research output: Contribution to conference › Paper
TY - CONF
T1 - Optimized network planning of mini-grids for the rural electrification of developing countries
AU - Nolan, Steven
AU - Strachan, Scott
AU - Rakhra, Puran
AU - Frame, Damien
N1 - (c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
PY - 2017/7/27
Y1 - 2017/7/27
N2 - 1.2 billion people, predominantly living in remote rural regions in countries of the Global South, currently live without access to any modern source of energy. Options for electrification of these communities include extending existing national grid infrastructure, deploying mini-grids, and installing standalone home systems (SHS). Deriving the most cost effective means of delivering energy to these consumers is a complex, multidimensional problem that normally requires determination on a case-by-case basis. However, optimization of the network planning may help to maximize the socio-economic return of the installed energy system. This paper presents an optimization process that minimizes the installation cost of a mix of generation sources for a rural mini-grid using a multi-objective particle swarm optimization (MOPSO) technique. Minimizing the cost of distribution layout is first formulated as a capacitated minimum spanning tree (CMST) problem and solved using the Esau-Williams method. Multiple cable sizes and source locations are then added to create a multi-level capacitated minimum spanning tree (MLCMST) problem, solved via a Genetic Algorithm (GA) employing Prim-Pred encoding. The method is applied to a case study village in India.
AB - 1.2 billion people, predominantly living in remote rural regions in countries of the Global South, currently live without access to any modern source of energy. Options for electrification of these communities include extending existing national grid infrastructure, deploying mini-grids, and installing standalone home systems (SHS). Deriving the most cost effective means of delivering energy to these consumers is a complex, multidimensional problem that normally requires determination on a case-by-case basis. However, optimization of the network planning may help to maximize the socio-economic return of the installed energy system. This paper presents an optimization process that minimizes the installation cost of a mix of generation sources for a rural mini-grid using a multi-objective particle swarm optimization (MOPSO) technique. Minimizing the cost of distribution layout is first formulated as a capacitated minimum spanning tree (CMST) problem and solved using the Esau-Williams method. Multiple cable sizes and source locations are then added to create a multi-level capacitated minimum spanning tree (MLCMST) problem, solved via a Genetic Algorithm (GA) employing Prim-Pred encoding. The method is applied to a case study village in India.
KW - mini grids
KW - renewable energy
KW - sustainability
KW - rural electrification
KW - Africa
KW - India
U2 - 10.1109/PowerAfrica.2017.7991274
DO - 10.1109/PowerAfrica.2017.7991274
M3 - Paper
ER -