The fulfillment of the sustainable development goals of the United Nations (UN) in remote communities undoubtedly goes through the consequent development of the energy supply system (ESS). Structuring a procedure for modeling the ESS, according to development requirements, is vital for decision making. This publication reviews the main methods for designing local development programs that apply a sustainable livelihoods approach and a group of modeling tools for ESS. The necessary criteria are verified to structure a model that integrates the expectations of sustainable development, through the indicators of sustainable livelihoods (SLs), with the requirements of the ESS and the use of available renewable energy resources. In the review carried out, it is found that the methods of analysis and planning of sustainable local development are disconnected from the models for energy planning. On the other hand, the relationship of the indicators for calculating SLs with the characteristics and behavior of energy demand with respect to time is verified. The main criteria, parameters, and optimization methods necessary for the design and expansion of ESS in hard-to-reach areas are also discussed. Lastly, the necessary elements are proposed to be validated through a future study case for the dimensioning and expansion of ESS in hard-to-reach communities, integrating the analysis of development programs based on SLs.

The Sustainable Development Goals (SDGs) of the United Nations Organization pursue the provision of affordable and quality energy for all human beings, which is why the correct planning of Energy Supply Systems (ESS) in communities that present levels of energy poverty, that is, the impossibility to satisfy their minimum needs for energy services. This work proposes a methodology to evaluate the contribution to development by the adequate provision of the demand of ESS in remote communities through the approach of Sustainable Livelihoods (SLs). The methodology starts from the initial evaluation of the sustainable livelihoods or capitals of the communities and the analysis of their interaction. Then, a capital improvement process is proposed by selecting the indicator values that optimize the model in each period, through an evolutionary algorithm that guarantees that the indicators evolve to a rich scenario as a result of planning to evolve the key variables based on a quantitative model with the indicators that empower evaluating the contribution of the ESS to them.