Optimization of renewable energy projects with Excel when professional software is not available
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Abstract
Sometimes, for the realization of profitability analysis and projects with renewable energy sources, professional software is not available, or the input and output parameters do not correspond to those available or desired by the user, since the designer chooses the parameters with which his algorithm has to operate. Many projects such as the one presented in this document can be designed by professionals and students with modest computer knowledge and solved with the Excel application present in all Microsoft Office packages. The example shown is aimed at determining the main parameters of the preliminary project, performing the profitability calculations and the sensitivity analysis of a hybrid wind-electric system that must guarantee the base demand of an isolated grid. The results are compared with those obtained with the professional software HOMER Beta V.2.68.
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References
Beiter, P., Elchinger, M., & Tian, T. (2016). U.S Department of Energy: 2016 Renewable Energy Data Book. https://www.nrel.gov/docs/fy18osti/70231.pdf
Blank, L., & Tarquin, A. (2006). INGENIERÍA ECONÓMICA. Sexta Edición (S. A. D. C. V. McGRAW-HILL/INTERAMERICANA EDITORES (ed.)).
Burton, T., Sharpe, D., Jenkins, N., & Bossanyi, E. (2002). WIND ENERGY HANDBOOK.
Enríquez, L., García, L., Oro, C., & Muñoz, J. (2016). Parametric Estimate Cost of Wind Farms in Latin America and the Caribbean. IOSR Journal of Mechanical and Civil Engineering, 13(04), 66–70. https://doi.org/10.9790/1684-13040646670
Fernández, C. (2012). Entre la TIR y el VPN para la evaluación de un proyecto. Instituto Pacifico, VII, 1–2.
Khan, J. K., Uddin, Z., Tanweer, I. S., Ahmed, F., Aijaz, A., & Jilani, S. U. (2015). An Analysis of Wind Speed Distribution and comparison of five numerical methods for Estimating Weibull Parameters at Ormara , Pakistan. EUROPEAN ACADEMIC RESEARCH, II(11), 14007–14015.
Manwell, J. F., & McGowan, J. G. (2009). WIND ENERGY EXPLAINED. Theory, Design and Application. Second Edition.
Oyarzo, H. (2008). Modelización matemática para evaluar energías para sistemas eólicos e híbridos eólico-diesel. ESCUELA TÉCNICA SUPERIOR DE INGENIEROS AGRÓNOMOS DEPARTAMENTO DE INGENIERÍA RURAL.
Randall, W., & Whitesides, P. E. (2012). Process Equipment Estimating by Ratio and Proportion. Course Notes, PDH Course G, 127, 1–8. www.PDHcenter.com
Roqueñí, I., Roqueñi, N., Álvarez, J., & Mesa, J. (2008). Introducción. Revista Clínica Española, 208, 1–9. https://doi.org/10.1016/s0014-2565(08)71781-8
Streeter, V. L., Wylie, E. B., & Bedford, K. W. (2000). Mecánica de los Fluidos - Streeter - 9 Edición.pdf (p. 749).
Unnasch, S., Browning, L., & Kassoy, E. (2001). Refinement of Selected Fuel-Cycle Emissions Analyses. Final Report, ARB Contract 98-338.
Villarrubia, M. (2007). Manual de Energía Eólica.Edición CEAC.
Watson, K. (1995). Sensitivity Analysis in Outcome Evaluations: A Research and Practice Note. Canadian Journal of Program Evaluation/La Revue Canadienne d’evaluation de Programme, 10(2), 113–122.