Two on step ahead wind speed forecasting models were compared. A univariate model was developed using a linear autoregressive integrated moving average (ARIMA). This method's performance is well studied for a large number of prediction problems. The other is a multivariate model developed using a nonlinear autoregressive exogenous artificial neural network (NARX). This uses the variables: barometric pressure, air temperature, wind direction and solar radiation or relative humidity, as well as delayed wind speed. Both models were developed from two databases from two sites: an hourly average measurements database from La Mata, Oaxaca, Mexico, and a ten minute average measurements database from Metepec, Hidalgo, Mexico. The main objective was to compare the impact of the various meteorological variables on the performance of the multivariate model of wind speed prediction with respect to the high performance univariate linear model. The NARX model gave better results with improvements on the ARIMA model of between 5.5% and 10.6% for the hourly database and of between 2.3% and 12.8% for the ten minute database for mean absolute error and mean squared error, respectively.

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The use of small wind turbines (SWTs) is an alternative energy strategy with increasing potential for satisfying in situ electrical demands and should be studied to promote social penetration. The Valley of Mexico Metropolitan Area (VMMA) has air pollution issues that need to be addressed. This has resulted in programs for monitoring atmospheric variables, such as wind speed. By selecting and using 3 years’ worth of available data, we developed a methodology to study the technical and economic feasibility of using SWTs in the VMMA. To this end, 28 SWT models were assessed at 18 locations to estimate annual energy production. In light of certain data characteristics, an adjustment to the power production was proposed for the specific case of using SWTs. Cash flow analysis and annualized net present value (ANPV) were used to determine economic feasibility for each location; furthermore, electric home feeds in the VMMA were considered to model local economic conditions. Similar wind conditions were observed within the VMMA; however, only two wind turbine and location models provided positive ANPV values. The extra annual benefit for each project was calculated by associating the cost per mitigation of CO2 emissions, which may provide an economic strategy for promoting the penetration of this technology.

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