The electrification rate of Myanmar is about 40 percent and its improvement is an urgent matter. The Sustainable Development Goal 7 recognizes the importance of energy access and calls for a solution to the Government of Myanmar’s plans to reach 100 percent electrification by 2030. To achieve this ambitious plan, both centralized (main-grid extension) and decentralized approaches should be considered. In this study, we focused on distributed mini-grids among electrification options. In Myanmar, as in other developing countries in the region, diesel generators are widely used as power sources of mini-grids. Considering the global trend of reduction of carbon dioxide emission, power sources should be selected carefully. When discussing possible power sources, cost-competitiveness is an important aspect. Therefore, we researched the question: How costcompetitive are mini-grids powered by solar photovoltaics (PVs) compared to conventional diesel power source? We used the primary data collected through interviews and field surveys, and calculated the levelized cost of electricity (LCOE) of mini-grids. Our results show that solar PVs and batteries are cost-competitive compared with diesel in off-grid areas where diesel fuel prices are much higher than in urban areas. However, to improve efficiency, daytime use of electricity (e.g. productive use) needs to be promoted.

In this work, a new method of predicting the surface tension of heavy oils and its temperature dependence was developed. The surface tensions of five fractions and residue fractionated by the vacuum distillation of atmospheric residue (AR), and AR itself were predicted, based on a detailed composition and molecular structure analysis, i.e., “petroleomics”. In this method, the chemical compositions and molecular structures of compounds included in the fractions and residue were identified by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), and then the critical pressure, critical temperature and boiling point of each compound were calculated by the group contribution method. Next, using the calculated properties, the surface tension of each compound was predicted by the principle of corresponding states. Finally, a mixing rule, in which the surface tension of mixtures was expressed as a linear function of mole fraction of each compound, was used to predict the surface tensions of the five fractions and residue of AR and AR itself. By comparing the predicted and experimental values of the surface tensions and their temperature dependence, it was found that the present method is useful for predicting the surface tension of heavy oils.