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Wind is one of the most promising sources of alternative energy. The construction of wind farms is destined to grow in the U.S., possibly twenty-fold by the year 2030. To maximize the wind energy capture, this paper presents a model for wind turbine placement based on the wind distribution. The model considers wake loss, which can be calculated based on(More)
As a complex mental process, creativity requires the coordination of multiple brain regions. Previous pathological research on figural creativity has indicated that there is a mechanism by which the left side of the brain inhibits the activities of the right side of the brain during figural creative thinking, but this mechanism has not been directly(More)
—In this paper, a data-mining approach is applied to optimize combustion efficiency of a coal-fired boiler. The combustion process is complex, nonlinear, and nonstationary. A virtual testing procedure is developed to validate the results produced by the optimization methods. The developed procedure quantifies improvements in the combustion efficiency(More)
—This paper examines time series models for predicting the power of a wind farm at different time scales, i.e., 10-min and hour-long intervals. The time series models are built with data mining algorithms. Five different data mining algorithms have been tested on various wind farm datasets. Two of the five algorithms performed particularly well. The support(More)
In this paper, models for short-and long-term prediction of wind farm power are discussed. The models are built using weather forecasting data generated at different time scales and horizons. The maximum forecast length of the short-term prediction model is 12 h, and the maximum forecast length of the long-term prediction model is 84 h. The wind farm power(More)
Different models for monitoring wind farm power output are considered. Data mining and evolutionary computation are integrated for building the models for prediction and monitoring. Different models using wind speed as input to predict the total power output of a wind farm are compared and analyzed. The k-nearest neighbor model, combined with the principal(More)
—The concept of anticipatory control applied to wind turbines is presented. Anticipatory control is based on the model predictive control (MPC) approach. Unlike the MPC method, non-controllable variables (such as wind speed) are directly considered in the dynamic equations presented in the paper to predict response variables, e.g., rotor speed and turbine(More)
Keywords: Wind turbine Wind energy Data mining Model predictive control Evolutionary computation algorithm Control strategy optimization a b s t r a c t The paper presents an intelligent wind turbine control system based on models integrating the following three approaches: data mining, model predictive control, and evolutionary computation. To enhance the(More)
A data-driven approach to the performance analysis of wind turbines is presented. Turbine performance is captured with a power curve. The power curves are constructed using historical wind turbine data. Three power curve models are developed, one by the least squares method and the other by the maximum likelihood estimation method. The models are solved by(More)
—In this paper, a data-mining approach is used to develop a model for optimizing the efficiency of an electric-utility boiler subject to operating constraints. Selection of process variables to optimize combustion efficiency is discussed. The selected variables are critical for control of combustion efficiency of a coal-fired boiler in the presence of(More)