A clustering approach is presented for short-term prediction of power produced by a wind turbine at low wind speeds. Increased prediction accuracy of wind power to be produced at future time periods is often bounded by the prediction model complexity and computational time involved. In this...

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...

This paper examines a new time series method for very short-term wind speed forecasting. The time series forecasting model is based on Bayesian theory and structural break modeling, which could incorporate domain knowledge about wind speed as a prior. Besides this Bayesian structural break model...

We present a model for scheduling power generation at a wind farm, and introduce a particle swarm optimization algorithm with a small world network structure to solve the model. The solution generated by the algorithm defines the operational status of wind turbines for a scheduling horizon...

Bearings are an essential part of turbine generators and gearboxes. Dynamic and unpredictable stress causes the bearings to wear prematurely, leading to increased turbine maintenance costs, and could lead to sudden, expensive turbine breakdowns. Over temperature impacts the performance of...

The rapid expansion of wind farms has drawn attention to operations and maintenance issues. Condition monitoring solutions have been developed to detect and diagnose abnormalities of various wind turbine subsystems with the goal of reducing operations and maintenance costs. This paper explores...

A data-mining approach for the optimization of a HVAC (heating, ventilation, and air conditioning) system is presented. A predictive model of the HVAC system is derived by data-mining algorithms, using a dataset collected from an experiment conducted at a research facility. To minimize the...

Agent-based modeling has proven effective in increasing the understanding of complex systems, including social-economical systems. Agoal of modeling complex systems is to distill the system into simple agents with phenotypes guided by simple rules. The model then displays the emergent behavior...