Engineering Commons^™

Deep Learning Based Power System Stability Assessment For Reduced Wecc System, Yinfeng Zhao

Doctoral Dissertations

Power system stability is the ability of power system, for a giving initial operating condition, to reach a new operation condition with most of the system variables bounded in normal range after subjecting to a short or long disturbance. Traditional power system stability mainly uses time-domain simulation which is very time consuming and only appropriate for offline assessment.

Nowadays, with increasing penetration of inverter based renewable, large-scale distributed energy storage integration and operation uncertainty brought by weather and electricity market, system dynamic and operating condition is more dramatic, and traditional power system stability assessment based on scheduling may not be …

Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, Guillermo Terrén-Serrano

Electrical and Computer Engineering ETDs

Due to the increasing use of photovoltaic systems, power grids are vulnerable to the projection of shadows from moving clouds. An intra-hour solar forecast provides power grids with the capability of automatically controlling the dispatch of energy, reducing the additional cost for a guaranteed, reliable supply of energy (i.e., energy storage). This dissertation introduces a novel sky imager consisting of a long-wave radiometric infrared camera and a visible light camera with a fisheye lens. The imager is mounted on a solar tracker to maintain the Sun in the center of the images throughout the day, reducing the scattering effect produced …

Smart Distributed Generation System Event Classification Using Recurrent Neural Network-Based Long Short-Term Memory, Shuva Das

Electronic Theses and Dissertations

High penetration of distributed generation (DG) sources into a decentralized power system causes several disturbances, making the monitoring and operation control of the system complicated. Moreover, because of being passive, modern DG systems are unable to detect and inform about these disturbances related to power quality in an intelligent approach. This paper proposed an intelligent and novel technique, capable of making real-time decisions on the occurrence of different DG events such as islanding, capacitor switching, unsymmetrical faults, load switching, and loss of parallel feeder and distinguishing these events from the normal mode of operation. This event classification technique was designed …

Dc-Dc Converter Control System For The Energy Harvesting From Exercise Machines System, Alexander Sireci

Master's Theses

Current exercise machines create resistance to motion and dissipate energy as heat. Some companies create ways to harness this energy, but not cost-effectively. The Energy Harvesting from Exercise Machines (EHFEM) project reduces the cost of harnessing the renewable energy. The system architecture includes the elliptical exercise machines outputting power to DC-DC converters, which then connects to the microinverters. All microinverter outputs tie together and then connect to the grid. The control system, placed around the DC-DC converters, quickly detects changes in current, and limits the current to prevent the DC-DC converters and microinverters from entering failure states.

An artificial neural …