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Off-grid renewable systems can play a pivotal role in the process of rural electrification, thus promoting local development. Moreover, scientific literature is increasingly addressing this issue through the concept of sustainability and appropriate technologies. With regards to this topic, we present a sizing methodology which better relates the results and the sizing process itself to the local context. Specifically, we address the research area of sizing methodologies for off-grid PV systems. Typically, the Loss of Load Probability (LLP) is a key parameter in these methodologies, but is difficult to set as regards the specific context. The proposed methodology employs the concept of Levelized Cost of Supplied and Lost Energy, it is based on the estimate of an economic Value of Lost Load, and eventually, the LLP results to be an output of the process. Therefore, the methodology uses only data characterizing the local situation and results better fit with population conditions. We also propose a simple approach to compute the Value of Lost Load and we apply the methodology for a rural area of Uganda. The results show that the methodology identifies a reliable system which supplies electricity with a fair cost while minimizing the energy bill of the consumers. [ABSTRACT FROM AUTHOR]

Access to electric power supply has always had a significant role in promoting improvements in all the society sectors, nevertheless nowadays 1.3 billion of people still do not have electricity access. Moreover, most of them live in rural areas of developing countries which are often isolated, scattered populated and characterized by poor infrastructure and services. In this situation, the growing consideration towards the target of universal access to energy has emphasized the role of rural electrification, and off-grid small-scale generation represents one of the most appropriate options. As a consequence, the scientific literature has devoted attention to this topic with a large number of papers. In this frame, the present analysis focuses on off-grid systems for rural electrification and provides a general framework to this topic and an analytical review of the literature. The work is based on the review of more than 350 papers mainly published from 2000 to 2014 within selected journals, and it is organized in two sections. In the first one we describe the role of small-scale generation systems throughout the process of electrification, the main features of rural areas and their typical energy uses, and we propose a new comprehensive taxonomy for off-grid systems for rural electrification. In the second one we develop an extensive review of the selected literature according to the proposed classification and to five main research areas: Technology: layout and components; Models and methods for simulation and sizing; Techno-economic feasibility analyses and sustainability analyses; Case studies analyses; Policy analyses. The work results in a comprehensive review which organizes and capitalizes the main fundamentals of the addressed topic and provides elements to get acquainted with the literature. [ABSTRACT FROM AUTHOR]

As it emerges from the literature, electricity access in rural contexts is deeply intertwined with socioeconomic dynamics. However, the advent of a reliable and sufficient source of electricity is not the sole driver that might contribute to local development. Indeed, complementary activities might have a crucial role in sustaining the development of rural communities as well as the electricity access. The current research addresses the lack of counterfactual scenarios in which the impact of complementary activities on electrification projects can be investigated. The authors introduce the case study of Matembwe village, a rural community in the Njombe region of Tanzania. The data collection includes the electricity consumption, number of electricity connections, and number of income-generating activities in a timespan ranging from 1989 to 2015. The analysis is based on system dynamics. The study considers different scenarios representing the dynamics related to the following complementary actions: access to market measures, access to credit measures, and access to usable skills. On the one hand, the study reveals that the effectiveness of the considered complementary actions is limited except from the access to microcredit which fosters an increase in electricity connections by 17%. On the other hand, both access to microcredit and the starting up of a local cooperative by CEFA Onlus that reinvests its profits in the local market impact the socio-economic dimension by 69% and 22%, respectively. [ABSTRACT FROM AUTHOR]

Thanks to their modularity and their capacity to adapt to different contexts, hybrid microgrids are a promising solution to decrease greenhouse gas emissions worldwide. To properly assess their impact in different settings at country or cross-country level, microgrids must be designed for each particular situation, which leads to computationally intractable problems. To tackle this issue, a methodology is proposed to create surrogate models using machine learning techniques and a database of microgrids. The selected regression model is based on Gaussian Processes and allows to drastically decrease the computation time relative to the optimal deployment of the technology. The results indicate that the proposed methodology can accurately predict key optimization variables for the design of the microgrid system. The regression models are especially well suited to estimate the net present cost and the levelized cost of electricity (R 2 = 0.99 and 0.98). Their accuracy is lower when predicting internal system variables such as installed capacities of PV and batteries (R 2 = 0.92 and 0.86). A least-cost path towards 100% electrification coverage for the Bolivian lowlands mid-size communities is finally computed, demonstrating the usability and computational efficiency of the proposed framework. • A novel methodology to create surrogate models for energy planning is presented. • Gaussian regression is compared to multi-variable regression. • The surrogate models for Economic indicators have a high prediction accuracy. • PV and Batteries installed capacity have lower prediction accuracy. • Surrogate models are created and coupled to a rural energy planning tool. [ABSTRACT FROM AUTHOR]

Efforts towards ensuring clean and affordable electricity for all have been progressing slowly in rural, off grid areas of developing countries. In this context, hybrid microgrids may offer reliable and potentially clean electricity for isolated locations. Nevertheless, the process of planning and operation of these systems faces several challenges, often due to the uncertainties related to the renewable resources and to the stochastic nature of electricity consumption in rural contexts. This paper tackles this problem and contributes to the literature in bridging the gap between field practices and two-stage stochastic modeling approaches by identifying an open-source modeling framework which is then applied to real local data. As reference case-study, we consider a microgrid built in 2015 in Bolivia. Overall, the optimal system results from a compromise between the Net Present Cost, the peak capacity installed and the flexibility (to balance variable generation). Different approaches to size isolated microgrids are tested, with the conclusion that methods accounting for the uncertainty in both demand and renewable generation may lead to a more robust configuration with little impacts on the final cost for the community. • The historical monitoring data from a remote PV-diesel microgrid in Bolivia for rural electrification is presented. • A novel two-stage optimization framework is developed for the robust design of such systems under uncertainty. • Components models and performance curves are derived from the monitoring data. • Among different model formulations, stochastic MILP models generate the most robust system configuration. • Recommendations are formulated regarding the optimal configuration with respect to the existing system. [ABSTRACT FROM AUTHOR]