Alexander Vallejo Díaz

Urban wind energy has emerged as an attractive source of distributed generation in cities to achieve sustainable development goals. The advancement in technologies for the use of urban wind energy has offered an alternative for the decarbonization of cities and the energy transition. The objectives of this work are (1) to identify the potential of wind energy through numerical weather prediction (NWP) data tools and (2) to identify the roles and responsibilities of the stakeholders involved in the decision-making process. A methodology was developed in two phases and applied to a case study in the Dominican Republic. The first phase consisted of estimating the wind energy potential for the 32 provinces at a height of 10 m using open access NWP tools provided by NASA. In the second phase, 28 stakeholders were identified through snowball sampling. The Responsible, Accountable, Consulted, and Informed (RACI) matrix tool was applied to identify the roles of the 28 institutions addressed at the country level as relevant in the decision-making process for the energy sector. The annual average wind speed and energy potential for each province were determined. It was found that 24 provinces have poor potentials, below <4.5 m/s. In the northwest and east is where there is the greatest potential, between 4.83 and 6.63 m/s. The population density was established, and it was observed that the provinces with greater potential are less densely populated. Through 59 interviews, 28 institutions were identified and evaluated due to their relevance in decision making for the implementation of energy projects. According to the RACI matrix, the Ministry of Energy and Mines has been categorized as “A”, electricity distribution companies as “R”, energy associations and universities as “C”, and educational and justice institutions as “I”.

Urban wind energy has emerged as an attractive source of distributed generation in cities to achieve sustainable development goals. The advance in technologies for the use of urban wind energy has turned this source into an attractive alternative for the decarbonization of cities and the energy transition. The objectives of this work are (1) to identify the potential of wind energy through numerical weather prediction (NWP) data tools and (2) to identify the roles and responsibilities of the stakeholders involved in the decision-making process. A methodology was developed in two phases and applied to a case study in the Dominican Republic. The first phase consisted of estimating the wind energy potential for the 32 provinces at a height of 10 m using open-access geographic reference systems tools provided by NASA. In the second phase, 28 stakeholders were identified through snowball sampling. The Responsible, Accountable, Consult, and Informed (RACI) matrix tool was applied to identify the roles of the 28 institutions addressed at the country level as relevant in the decision-making process for the energy sector. The annual average wind speed and energy potential for each province were determined. It was found 24 provinces have poor potential, below <4.5 m/s. In the northwest and east is where there is the greatest potential, between 4.83 - 6.63 m/s. The population density was established and was observed that the provinces with greater potential are less densely populated. Through 59 interviews 28 institutions were identified and evaluated due to their relevance in decision-making for the implementation of energy projects. The MEM has strongly categorized as “A”, electricity distribution companies as “R”, energy associations and universities as “C”, and educational and justice institutions as “I”.

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.

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.