Solar energy is one of the most mature technologies to produce electricity from renewable energy. This papers analyses the solar radiation potential in the city of Barranquilla (Colombia), located at 10°59'16" north and 74°47'20" west, for using Concentrated Solar Power technology (CSP) to generate electricity. Due to the lack of meteorological data in coastal areas of Colombia, Daily Integration Approach (DI) was used as the hourly radiation model. The DI model, along with radiation data from NASA-SSE (Surface meteorology and solar energy) were used to map the direct and beam radiation. The maps were plotted using the Matplotlib Basemap Toolkit in Python 2.7. The solar maps showed the high potential of solar radiation for CSP at the north coast of Colombia. Then, System Advisor Model (SAM) was used to perform a yearly simulation, in the city of Barranquilla, of a parabolic trough solar power plant of 50 MWe. The model included thermal energy storage (TES) with natural gas as backup and a sensitivity analysis was performed to find the optimum size which minimizes the Levelized Cost of Energy (LCOE). The results showed that for typical solar field cost, the minimum LCOE is around 25 cents/kWh which is still pretty high as compared with traditional systems but it has a positive impact on carbon footprint, using natural gas this value is reduced to 9.76 cents/kWh.

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The use of renewable energy sources, especially wind energy, has been widely developed, mostly during the last decade. The main objective of the present study is to conduct a literature review focused on the evaluation under uncertainty of wind energy investment using the real options approach to find out whether public opposition (NIMBY projects) has been contemplated, and if so, what have been the flexible strategies applied for its intervention. Overall, 97 publications were analyzed, identifying 20 different models or approaches, which were grouped into eight categories: 1. Real options, 2. Optimization, 3. Stochastics, 4. Financial evaluation, 5. Probabilistic, 6. Estimation, 7. Numerical prediction, and 8. Others. The real options approach, present in 32% of the studies, was the most popular. Twenty-eight types of uncertainties were identified, which were grouped, for better analysis, into nine categories. In total, 62.5% of the studies included the price of electricity as a source of uncertainty; 18.8%, the velocity of wind; and 15.6%, the feed-in rates-subsidy. Both random and non-random techniques were applied to assess the real options and to model the uncertainties. When evaluating real options, the Monte Carlo simulation technique was the most preferred, with 16 (51.6%) applications, followed by non-randomized techniques, decision tree, and dynamic programming, with eight (25.8%) applications each. There is a marked tendency to use stochastic processes to model uncertainty, particularly geometric Brownian motion, which was used in 61.3% (19) of the studies in the sample. When searching for “real options AND (nimby OR public opposition)”, no study was found, which shows the possibility of developing research on this aspect to determine its impact on investments in wind energy projects.

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