Engineering Commons^™

Short Term Energy Forecasting For A Microgird Load Using Lstm Rnn, Akhil Soman

Masters Theses

Decentralization of the electric grid can increase resiliency (during natural disasters) and can reduce T&D energy losses and emissions. Microgrids and DERs can enable this to happen. It is important to optimally control microgrids and DERs to extract the greatest economic, environmental and resiliency benefits. This is enabled by robust forecasting to optimally control loads and energy sources. An integral part of microgrid control is power side and load side demand forecasting.

In this thesis, we look at the ability of a powerful neural network algorithm to forecast the load side demand for a microgrid using the UMass campus as …

Uav Parameter Estimation Through Machine Learning, Andres Enriquez Fernandez

Open Access Theses & Dissertations

Parameter identification of Unmanned Aerial Vehicles (UAV) is very helpful for understanding cause-effect relationships of physical phenomenon, investigating system performance and characteristics, fault diagnostics, control development/tuning, and more. Traditional ways of performing parameter identification involve establishing a mathematical model that describes the system's behavior. The equations in the model contain parameters that are estimated indirectly from measured flight data. This parameter identification process requires knowledge of the physics involved. Also, it necessitates a careful consideration of the aircraft instrumentation for accurate measurements. It also requires careful design of the flight maneuvers to ensure thorough excitation of the flight dynamics involved. …

A Neural Network Approach To Estimate Buoy Mooring Line Sensor Deflection, Tom Price

Dissertations, Master's Theses and Master's Reports

Instrumented moorings are often used to measure characteristics, such as temperature and current, over the water column. However, the moorings deflect from the effects of currents and waves, which could lead to innacurate measurements. In this work, a computationally efficient method to compensate for mooring sensor position errors is developed. The two-step process first uses a hydrodynamic model of the buoy and mooring line system to create estimated mooring line deflections in a steady current. A neural network model is trained to approximate the hydrodynamic model’s mooring line displacement given the spatial location of the buoy and current profile measurements. …

Toward Closing The Urban Surface Energy Balance Using Satellite Remote Sensing, Joshua Hrisko

Dissertations and Theses

The energy exchanges at the Earth’s surface are responsible for many of the processes that govern weather, climate, human health, and energy use. This exchange, commonly known as the surface energy balance (SEB), determines the near-surface thermodynamic state by partitioning the available energy into surface fluxes. The net all-wave radiation is often the primary energy source, while the heat storage and sensible and latent heat fluxes account for the majority of energy distributed elsewhere. While the SEB of various natural environments(trees, crops, soils) has been well-observed and modeled, the urban surface energy balance remains elusive. This is due to the …

Time- And Space-Dependent Uncertainty Analysis And Its Application In Lunar Plasma Environment Modeling, Xinpeng Wei

Doctoral Dissertations

”During an engineering system design, engineers usually encounter uncertainties that ubiquitously exist, such as material properties, dimensions of components, and random loads. Some of these parameters do not change with time or space and hence are time- and space-independent. However, in many engineering applications, the more general time- and space-dependent uncertainty is frequently encountered. Consequently, the system exhibits random time- and space-dependent behaviors, which may result in a higher probability of failure, lower average lifetime, and/or worse robustness. Therefore, it is critical to quantify uncertainty and predict how the system behaves under time- and space- dependent uncertainty. The objective of …