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Full-Text Articles in Engineering
Cost Analysis Of Optimized Islanded Energy Systems In A Dispersed Air Base Conflict, Jay F. Pearson, Torrey J. Wagner, Justin D. Delorit
Cost Analysis Of Optimized Islanded Energy Systems In A Dispersed Air Base Conflict, Jay F. Pearson, Torrey J. Wagner, Justin D. Delorit
Faculty Publications
The United States Air Force has implemented a dispersed air base strategy to enhance mission effectiveness for near-peer conflicts. Asset dispersal places many smaller bases across a wide geographic area, which increases resupply requirements and logistical complexity. Hybrid energy systems reduce resupply requirements through sustainable, off-grid energy production. This paper presents a novel hybrid energy renewable delivery system (HERDS) model capable of (1) selecting the optimal hybrid energy system design that meets demand at the lowest net present cost and (2) optimizing the delivery of the selected system using existing Air Force cargo aircraft. The novelty of the model’s capabilities …
A Multi-Criteria Logistics Analysis Of Photovoltaic Modules For Remote Applications, Nathan Thomsen [*], Dimitri Papazoglou, Torrey J. Wagner, Andrew J. Hoisington, Steven J. Schuldt
A Multi-Criteria Logistics Analysis Of Photovoltaic Modules For Remote Applications, Nathan Thomsen [*], Dimitri Papazoglou, Torrey J. Wagner, Andrew J. Hoisington, Steven J. Schuldt
Faculty Publications
Reliable electrical power grids are frequently unavailable or inaccessible in remote locations, including developing nation communities, humanitarian relief camps, isolated construction sites, and military contingency bases. This often requires sites to rely on costly generators and continuous fuel supply. Renewable energy systems (RES) in the form of photovoltaic (PV) arrays and energy storage present a rapidly improving alternative to power these remote locations. Previous RES literature and PV optimization models focused on economics, reliability, and environmental concerns, neglecting the importance of logistics factors in remote installations. This paper proposes additional optimization variables applicable to remote PV systems and compares PV …
Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey J. Wagner, Clay Koschnick, Steven J. Schuldt, Jada B. Williams, Kevin Hallinan
Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey J. Wagner, Clay Koschnick, Steven J. Schuldt, Jada B. Williams, Kevin Hallinan
Faculty Publications
Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal solar panels using 14 months of data collected from 12 northern-hemisphere locations. We performed our data collection and analysis in the absence of irradiation data—an approach not commonly found in prior literature. Using latitude, month, hour, ambient temperature, pressure, humidity, wind speed, and cloud ceiling as independent variables, a distributed random forest regression algorithm modeled the combined …