The wind power of Mexico

Hernández-Escobedo, Quetzalcoatl; Manzano‐Agugliaro, Francisco; Zapata-Sierra, Antonio

doi:10.1016/j.rser.2010.07.019

Cited by 83 publications

(33 citation statements)

References 18 publications

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“…As a renewable and alternative energy, wind is the most common and fastest-growing source of energy in the world [3][4][5]. The characteristics of wind energy are important in different aspects regarding wind energy exploitation [6,7]. Wind is highly variable, both in space and in time [8].…”

Section: Introductionmentioning

confidence: 99%

Statistical Diagnosis of the Best Weibull Methods for Wind Power Assessment for Agricultural Applications

2014

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Abstract:The best Weibull distribution methods for the assessment of wind energy potential at different altitudes in desired locations are statistically diagnosed in this study. Seven different methods, namely graphical method (GM), method of moments (MOM), standard deviation method (STDM), maximum likelihood method (MLM), power density method (PDM), modified maximum likelihood method (MMLM) and equivalent energy method (EEM) were used to estimate the Weibull parameters and six statistical tools, namely relative percentage of error, root mean square error (RMSE), mean percentage of error, mean absolute percentage of error, chi-square error and analysis of variance were used to precisely rank the methods. The statistical fittings of the measured and calculated wind speed data are assessed for justifying the performance of the methods. The capacity factor and total energy generated by a small model wind turbine is calculated by numerical integration using Trapezoidal sums and Simpson's rules. The results show that MOM and MLM are the most efficient methods for determining the value of k and c to fit Weibull distribution curves.

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Section: Introductionmentioning

confidence: 99%

Statistical Diagnosis of the Best Weibull Methods for Wind Power Assessment for Agricultural Applications

2014

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“…This promotes the reliability of the electricity grid's availability and stability and reduces the need for grid expansions since electricity can be consumed where it is generated due to a decentralized integration of wind energy into the existing system. However, regions with a site quality factor lower than 80% could be excluded because of too high subsidy requirements and the availability of several better sites across Mexico [10,11,12].…”

Section: Discussion and Limitationsmentioning

confidence: 99%

“…They focus on the wind speed distributions in certain regions. Hernández-Escobedo et al [12] performed a similar analysis but investigated wind speeds for all Mexican regions. However, none of the studies provides financial insights.…”

Section: Related Workmentioning

confidence: 99%

Financial Decision Support System for Wind Energy _ Analysis of Mexican Projects and a Support Scheme Concept

Koukal¹,

Piel²

2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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Energy consumption is constantly on the increase all over the world. Especially fast-growing economies in emerging countries contribute to this increase. Governments need to promote the expansion of renewable energies in these countries by providing adequate general conditions and suitable support schemes. We provide decision support for the assessment of wind energy projects and their financial conditions. Following design science research (DSR) principles, a discounted cash flow (DCF) model in combination with a Monte Carlo simulation (MCS) to consider project risks was created. On this basis, a decision support system (DSS) was implemented in MATLAB. The applicability of the DSS is evaluated in the course of an analysis of onshore wind projects in Mexico. Based on the analysis' results, a concept of a support scheme is designed to promote an expansion of onshore wind energy across Mexico.

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“…Wind power with capacity factors higher than 20% has a potential of 71 GW [11]. A range of between 1 GW and 70 GW is applied in the high RES scenarios.…”

Section: Wind Powermentioning

confidence: 99%

“…Different studies report an additional feasible geothermal power potential from current geothermal capacity of up to 4.6 GW e plus around up to 7.2 GW e as probable and possible reserves [6,7,10]. Studies conducted for wind power estimate a potential of about 71 GW considering capacity factors (CF) higher that 20% [6,8,11]. For CF above 30% the potential is assessed at 11 GW [12] and for CF higher than 35% 5.2 GW [13,14].…”

Section: Introductionmentioning

confidence: 99%

Analysis of large-scale integration of renewable energy sources in the Mexican electricity system

Vidal-Amaro

Østergaard

Sheinbaum-Pardo

2015

WIT Transactions on Ecology and the Environment

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The Mexican electricity consumption is highly based on fossil fuels. In 2012 only 15% of the electricity generation was produced using renewable energy sources (RES) and most of the new installed capacity during the last decade has been based on combined cycle power plants. On the other hand, Mexico is a land of ample opportunities for renewable energy exploitation that could lower its dependency on fossil fuels. Recently, the Mexican Congress approved a regulation limiting fossil fuel-based electricity generation to 65% by the year 2024, to 60% by 2035 and to 50% by 2050. In this work we investigate the potential for renewable energy integration into the Mexican electricity system. We construct three scenarios (low, mid and high biomass) for achieving the 2024 target and analyse the electricity system response to varying contributions of wind and solar power production to the scenarios. The minimum complementary capacity based on fossil fuels needed to cover the demand without electricity imports is also assessed. Results indicate that within each scenario several combinations of bio, wind and solar power make a minimum of 35% RES electricity production possible. However, in every scenario there is only one combination resulting in the minimum overall capacity. Biomass has the highest effectiveness in terms of high RES production with the lowest needed overall power generating capacity.

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The wind power of Mexico

Cited by 83 publications

References 18 publications

Statistical Diagnosis of the Best Weibull Methods for Wind Power Assessment for Agricultural Applications

Statistical Diagnosis of the Best Weibull Methods for Wind Power Assessment for Agricultural Applications

Financial Decision Support System for Wind Energy _ Analysis of Mexican Projects and a Support Scheme Concept

Analysis of large-scale integration of renewable energy sources in the Mexican electricity system

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