Comparison of forecasting methods for vertical axis wind turbine applications in an urban/suburban area

Abstract

Wind forecasting plays an important role in the economic benefit and system reliability of wind turbine power generation. The goal of the present study is to investigate different forecasting methods that can be used to improve the amount of energy captured by a small-scale vertical axis wind turbine (VAWT) operating in a gusty wind environment typical of an urban/suburban area. Four forecasting methods are studied in the present research: Persistence Method, Modified Persistence Method, Autoregressive Moving Average (ARMA) model, and Weather Research and Forecasting (WRF) model. The forecasting models are used to predict the wind conditions and optimal rotational speed of VAWTs located in Oklahoma City for data collected in 2009. In all cases, a constant rotational speed controller was used with a forecasting horizon of 1 day. The results indicate that a 5% increase in accuracy of the wind forecast could increase the total amount of energy captured by the VAWT by as much as 13%. The results also indicate that the use of a tuned speed adjustment factor (AF) in the modified persistence method improves the overall performance of the VAWT by as much as 6% compared to the persistence method. The value of AF was found to be site-independent and linearly proportional to the annual average wind speed. For the ARMA model, there exists an optimal amount of training data and forecasting horizon that results in minimal error when the forecasting data are compared to the actual data. For each of the sites investigated, the modified persistence method appears to slightly outperform the persistence, ARMA, and WRF models. In all cases, the forecasting models allow the VAWT to capture approximately 78%–85% of the optimal amount of energy that could be generated assuming the actual wind data were known in advance. The economic viability of the VAWT is also examined by comparing the Levelized Cost of Energy (LCOE) for the VAWT with the national electricity unit price. The LCOE of the system is competitive with the national electricity unit price at the sites where the annual average wind speed is 4.3 m/s or greater.