Lehigh University Doctoral Student Kevin Wyckoff Researches Energy Solutions for Remote Communities

Some communities, such as those in remote rural or islanded locations, need to import their fuel, such as diesel, for energy. Transporting the fuel over mountains, bodies of water, and over long distances adds to the cost. Because of this, researchers and communities are searching for efficiencies to lower these costs. Microgrids (small, localized energy networks that can operate independently of the main power grid) are one option, and a vein of research focuses on a renewable energy-powered microgrid that allows remote communities to produce sufficient power for their needs at a lower cost than fuel importation.

Lehigh University Mechanical Engineering and Mechanics (MEM) graduate student Kevin Wyckoff researches marine energy systems, including wind, wave, and solar. He recently published his first journal article on an algorithm he developed that calculates the lowest LCOE (or the average cost of energy generation for the lifetime of the equipment, a common metric for energy costs) for renewable energy-supported microgrids. His co-authors are his dissertation advisors (Dr. Farrah Moazeni, Assistant Professor of Civil and Environmental Engineering; Dr. Javad Khazaei, Assistant Professor of Electrical and Computer Engineering; and Dr. Arindam Banerjee, Paul B. Reinhold Professor and Department Chair, MEM). Co-edited by Dr. Banerjee, the special issue of the journal Renewable Energy featured selected papers from the University Marine Energy Consortium 2023 Conference.

The energy produced by wind, waves, and sun is variable. “You can change how much a diesel generator is outputting,” Wyckoff says. “But wind speed is not something you can dictate.” The blustery energy of a windy day can’t be saved–all that potential power is literally gone with the wind.

A battery solves this problem, storing energy to smooth uneven energy supply or cope with a sudden spike in demand. Wyckoff says, “You’re trying to match these different moments of the power that’s needed and the power you have. Sometimes you have more power than you need, sometimes you have less power than you need,” due to the natural fluctuation in wind speed, wave energy, and sun amounts.

In the article, Wyckoff discusses the configuration of multiple renewable energy sources that will determine the optimal battery size needed to provide enough power to meet demand at the lowest LCOE for rural/islanded communities reliant on microgrids, or small-scale energy production and distribution systems, for electrical power. Wyckoff says, “the first thing that drove us forward with this research was the idea of integrating economic dispatch, looking at a time frame and electricity demands to essentially find the cheapest power, and there’s no other research doing this with wave energy or offshore wind energy.”

A battery can store energy and stabilize supply, but it can also become depleted. The research was powered in part by this consideration. Wyckoff says that the thinking behind this research article was, “let’s look at a system [test case] and let’s see how much storage we need with different kinds of configurations of resources…that’s the novel algorithm [in the article], that we are looking at the system and we pick the storage size we need to successfully meet all of the electricity demands throughout the time period we’re looking at.”

Wyckoff gathered data from three renewable energy sources. For wave and wind energy, he used data gathered by NOAA (National Oceanic and Atmospheric Administration) buoys east of Puerto Rico; east of Cape Canaveral, Florida; and south of New York City. These buoys record wave height, period, and other qualities, as well as wind speeds measured about 4 meters above sea level. For solar resource data, he used data from the National Solar Radiation Database (NSRD), which includes irradiance from both direct and diffuse light using satellites.

This real-world data was modeled by several open source tools. The wind data, for example, was processed by an AOC 15/50 turbine in the National Renewable Energy Laboratory (NREL)-developed wind energy simulator OpenFAST, while the wave energy was modeled via WEC-sim, an open-source wave energy converter simulator developed by both NREL and Sandia national labs using the programming language MATLAB/SIMULINK. Solar data was calculated from NSRD’s data for each of the three locations.

Cost functions, or estimated costs for producing the energy, were assigned to each energy source to figure out the LCOE for each. “To formulate the optimal economic dispatch, each resource on the microgrid requires a cost function,” Wyckoff says. Two of the challenges here included estimating wave energy cost, because there are few wave-based commercial energy entities to base estimated costs on, and estimating battery costs, because not only are there few commercial-scale storage facilities, but also various types and sizes of batteries will have different costs.

For a grid system to reach the lowest LCOE, the basic costs of producing the energy, from equipment to storage and distribution, has to be lower than the actual value of the energy. Adjusting the number and positions of the turbines and wave energy converters has an effect on cost. The costs found in the study are those associated with supplying the microgrid with energy from renewable sources, as well as the costs of lithium-ion batteries, chosen because they are commonly used and widely studied.

Using the output from these sources, Wyckoff calculated the total energy from marine energy systems, then calculated the battery storage needs. Because the battery would be storing this energy and directly fueling the microgrid, Wyckoff also had to determine the size of the battery and the cost of storage.

In the end, Wyckoff was able to determine the LCOE for energy storage from energy sourced from solar, wind, and wave, and to demonstrate the potential for microgrid use based on renewable energy for islanded or rural communities, as well as to pinpoint seasonal variations in energy systems, making long-term energy storage solutions a critical step in developing a low-cost economic dispatch.

Wyckoff, from High Bridge, New Jersey, is in his fourth year of doctoral study, and his advising team’s expertise areas mirror the elements in his article. The advisors include Dr. Arindam Banerjee, who heads the Turbulent Flow Design Group (aka TurbLab) at Lehigh, which studies multiscale fluid dynamics with an emphasis on energy-and biological systems, and is a PI on the Atlantic Marine Energy Center (AMEC), which is researching the blue economy; Dr. Farrah Moazeni, who researches water distribution in relation to grid and electrical distribution systems; Dr. Javad Khazaei, who works on microgrid optimization; and Dr. Shalinee Kishore, Director of the Institute for Cyber Physical Infrastructure and Energy and Iacocca Chair Professor in the Department of Electrical and Computer Engineering, who studies smart grid systems. All are involved in AMEC, a consortium that draws on similar strengths at Lehigh and three other universities (University of New Hampshire, Stony Brook University, and the Coastal Studies Institute at East Carolina University).

Wyckoff has a relatively long relationship with Dr. Banerjee. In his senior year of undergrad, he took Dr. Banerjee’s Renewable Energy course (MEM) and now says it was “maybe my favorite course” at Lehigh. As Wyckoff entered his fifth year at Lehigh, working on his master’s degree, he kept in touch with Banerjee, who, late in that academic year, asked Wyckoff if he’d be interested in an open position for a graduate student in his lab. This coincided with Wyckoff’s growing realization that he’d like to pursue a doctorate. He applied and became part of Dr. Banerjee’s TurbLab in Packard, where a multidisciplinary approach is the norm.

Working with Dr. Banerjee on AMEC-related projects seems to suit Wyckoff’s intellectual style, which mixes several approaches into one study. He says that even when he was a high school student applying to Lehigh for undergraduate, he was “interested in multiple sciences and having a wide foundation.” Now, as he’s progressed through undergraduate and graduate studies, he says, he’s still keeping that broad focus: “In engineering you have to learn a lot of different things as kind of a base, especially in mechanical engineering.”

Having defended his dissertation proposal last fall, Wyckoff expects to earn his PhD in 2026.  His dissertation focuses on the integration of offshore renewable energy into grids and intervening into issues that arise with this goal and focuses mostly on wind and waves. After he receives his degree, he says, he is contemplating a postdoc, as it seems like a “natural” next step as he figures out where he wants to land, industry or academia.