A data-driven approach for optimizing the reheat process in a variable-air-volume box is presented. Data-mining algorithms derive temporal predictive models from the reheat process data. The bi-objective model formed is solved with a modified particle swarm optimization algorithm. To increase...

An anticipatory control scheme for optimizing power and vibration of wind turbines is introduced. Two models optimizing the power generation and mitigating vibration of a wind turbine are developed using data collected from a large wind farm. To model the wind turbine vibration, two parameters,...

This paper discusses energy savings in wastewater processing plant pump operations and proposes a pump system scheduling model to generate operational schedules to reduce energy consumption. A neural network algorithm is utilized to model pump energy consumption and fluid flow rate after...

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...