Towards the Sustainable Development Goals: A Bi-objective framework for electricity access

Abstract Traditionally, the main focus of evaluation in universal electricity access problems has been cost. However, additional criteria such as increasing renewable penetration due to environmental concerns or grid penetration due to reliability concerns, have become increasingly important. We acknowledge the importance of additional criteria and propose a bi-objective framework so as to help decision makers investigate the trade-offs between potentially conflicting criteria in rural electrification. We consider two objective space based exact approaches using the Prize Collecting Steiner Tree (PCST) formulation and two metaheuristic algorithms to find Pareto solutions, and investigate their performances on real life problem instances. This study is expected to be an important decision support tool for the electrification of underdeveloped communities, having the potential of contributing to their socio-economic development.

[1]  D. J. Elzinga,et al.  An algorithm for the bi-criterion integer programming problem , 1986 .

[2]  Mohd Amran Mohd Radzi,et al.  Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A review , 2012 .

[3]  Shashank Mohan,et al.  National electricity planning in settings with low pre-existing grid coverage: Development of a spatial model and case study of Kenya , 2009 .

[4]  Marco Laumanns,et al.  SPEA2: Improving the strength pareto evolutionary algorithm , 2001 .

[5]  Horst W. Hamacher,et al.  Finding representative systems for discrete bicriterion optimization problems , 2007, Oper. Res. Lett..

[6]  Rumi Rajbongshi,et al.  Optimization of PV-biomass-diesel and grid base hybrid energy systems for rural electrification by using HOMER , 2017 .

[7]  Sara Lumbreras,et al.  Electricity for all: The contribution of large-scale planning tools to the energy-access problem , 2020 .

[8]  Ayse Selin Kocaman,et al.  Bi‐objective optimization of a grid‐connected decentralized energy system , 2018 .

[9]  Mohamed Haouari,et al.  Tight compact models and comparative analysis for the prize collecting Steiner tree problem , 2013, Discret. Appl. Math..

[10]  Ernst Worrell,et al.  Analyzing grid extension and stand-alone photovoltaic systems for the cost-effective electrification of Kenya , 2015 .

[11]  Woonghee Tim Huh,et al.  Initial layout of power distribution systems for rural electrification: A heuristic algorithm for multilevel network design , 2012 .

[12]  David E.H.J. Gernaat,et al.  The role of decentralized systems in providing universal electricity access in Sub-Saharan Africa – A model-based approach , 2017 .

[13]  Todd Levin,et al.  Least-cost network evaluation of centralized and decentralized contributions to global electrification , 2012 .

[14]  Euan Phimister,et al.  The politico-economics of electricity planning in developing countries: A case study of Ghana , 2016 .

[15]  Juan José Salazar González,et al.  The biobjective travelling purchaser problem , 2005, Eur. J. Oper. Res..

[16]  Markus Leitner,et al.  A Computational Study of Exact Approaches for the Bi-Objective Prize-Collecting Steiner Tree Problem , 2015, INFORMS J. Comput..

[17]  Ayse Selin Kocaman,et al.  A prize collecting Steiner tree approach to least cost evaluation of grid and off-grid electrification systems , 2018, Energy.

[18]  O. Nadjemi,et al.  Potential, optimization and sensitivity analysis of photovoltaic-diesel-battery hybrid energy system for rural electrification in Algeria , 2019, Energy.

[19]  R. Prim Shortest connection networks and some generalizations , 1957 .

[20]  Attia A. El-Fergany,et al.  Optimizing performance attributes of electric power systems using chaotic salp swarm optimizer , 2020, International Journal of Management Science and Engineering Management.

[21]  Ignacio J. Pérez-Arriaga,et al.  Optimal Electrification Planning Incorporating On- and Off-Grid Technologies: The Reference Electrification Model (REM) , 2019, Proceedings of the IEEE.

[22]  Valerie M. Thomas,et al.  Can developing countries leapfrog the centralized electrification paradigm , 2016 .

[23]  Vijay Modi,et al.  Local and national electricity planning in Senegal: Scenarios and policies , 2012 .

[24]  U. Deichmann,et al.  The Economics of Renewable Energy Expansion in Rural Sub-Saharan Africa , 2010 .

[25]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[26]  Lothar Thiele,et al.  Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.

[27]  David P. Williamson,et al.  A note on the prize collecting traveling salesman problem , 1993, Math. Program..

[28]  Manuel Welsch,et al.  A cost comparison of technology approaches for improving access to electricity services , 2016 .

[29]  David S. Johnson,et al.  The prize collecting Steiner tree problem: theory and practice , 2000, SODA '00.

[30]  Debao Zhang,et al.  Research on the configuration and operation effect of the hybrid solar-wind-battery power generation system based on NSGA-II , 2019 .

[31]  Martin W. P. Savelsbergh,et al.  A Criterion Space Search Algorithm for Biobjective Integer Programming: The Balanced Box Method , 2015, INFORMS J. Comput..

[32]  Adriaan Zomers,et al.  Remote Access: Context, Challenges, and Obstacles in Rural Electrification , 2014, IEEE Power and Energy Magazine.

[33]  Simon Bawakyillenuo Deconstructing the dichotomies of solar photovoltaic (PV) dissemination trajectories in Ghana, Kenya and Zimbabwe from the 1960s to 2007 , 2012 .