Area(s) of Expertise
Stochastic modeling of coupled natural-human systems; water and energy systems analysis; financial risk management
Ph.D. (Environmental Sciences and Engineering) University of North Carolina-Chapel Hill (2014)
M.Sc. (Environmental Sciences and Engineering) University of North Carolina-Chapel Hill (2010)
B.Sc. (Environmental Science) University of North Carolina-Chapel Hill (2007)
Area(s) of Expertise
Stochastic modeling of coupled natural-human systems in order to: 1) improve understanding of emergent risks to people and the environment across sectors and scales; and 2) develop novel approaches for mitigating these vulnerabilities.
This proposed work will weave together new and existing knowledge about natural hazards, power systems, and financial/economic markets in order to explore interdependencies and feedbacks between the U.S. power sectorÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢s efforts to manage extreme weather and reduce greenhouse gas emissions. Research efforts will focus on developing a deep understanding of system dynamics in different testbeds distributed across the U.S. These testbeds will facilitate investigation of how regional differences in natural resources, climate, infrastructure, and human institutions shape interactions between extreme weather and decarbonization efforts. The unifying thread throughout, and the major research objective of this proposal, is the development and application of a systems analysis framework for resilient and robust management of weather risk in grids transitioning to renewable energy.
The Science and Technologies for Phosphorus Sustainability (STEPS) Center is a convergence research hub for addressing the fundamental challenges associated with phosphorus sustainability. The vision of STEPS is to develop new scientific and technological solutions to regulating, recovering and reusing phosphorus that can readily be adopted by society through fundamental research conducted by a broad, highly interdisciplinary team. Key outcomes include new atomic-level knowledge of phosphorus interactions with engineered and natural materials, new understanding of phosphorus mobility at industrial, farm, and landscape scales, and prioritization of best management practices and strategies drawn from diverse stakeholder perspectives. Ultimately, STEPS will provide new scientific understanding, enabling new technologies, and transformative improvements in phosphorus sustainability.
The overarching goal of the proposed research tasks for the NCSU team in Phase 2 of IM3 is to help develop new, open source operational models of the U.S. bulk electric power system, one for each of the three regional interconnections: the Western Electricity Coordinating Council (WECC); the Electric Reliability Council of Texas (ERCOT); and the Eastern Interconnection (EIC). These models will then be used by NCSU and other members of the IM3 team to address the impacts of weather and water dynamics in the simulation of grid operations in Experiment Groups B and D as described in the IM3 Phase 2 proposal
Enabling the next generation of sustainable farms requires a paradigm shift in resource management of the two most critical agricultural inputs for food production: water and nitrogen (N) - based fertilizer. Inefficient management of these resources increases food production costs, decreases productivity, and impacts the environment. An integrated approach is needed to improve the sustainability and efficiency throughout the production chain. Emerging (bio)electrochemical (BEC) technologies offer alternatives to conventional, fossil-fuel intensive N fertilizer production. Recently our team has demonstrated two game-changing BEC technologies: 1) microbial conversion of nitrogen gas into ammonium, and 2) plasma generation of N species (e.g., nitrate, nitrite) and other reactive species in water for fertilization and anti-pathogen benefits. We will integrate these technologies to produce BEC, N-based fertilizer, and with advanced sensor and delivery systems, we will precisely supply fertilizers for sustainable precision agriculture. Our proposed approach focuses on the development of a novel ÃƒÂ¢Ã¢â€šÂ¬Ã…â€œBEC fertigation on demand systemÃƒÂ¢Ã¢â€šÂ¬Ã‚Â by using sensor-driven data and molecular analyses to investigate BEC fertigation impact on the plantsÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢ growth, adaptation, and microbiome; its impact on food safety and quality, and its economic feasibility for on-farm deployment.
Concerns over depleting oil reserves and national security have spurred renewed vigor in developing bio-based fuels. A variety of feedstocks, conversion technologies, and biobased refinery concepts have been proposed and are being investigated. The viability of these systems is typically quantified through sustainability assessments. Current work has focused on the assessment of technologies either based on economic viability or environmental impact but typically not concurrently. Further, there has been minimal work in the area of biorefinery optimization. The proposed work will develop a unique toolset that is capable of identifying promising production pathways as well as performance targets for biobased energy and co-product systems. The foundation of the work is a modular engineering process model that captures the performance of various feedstock production systems, conversion technologies, and end use. This foundation is coupled with techno-economic, life cycle and resource demand modeling to understand the sustainability of the various production pathways. The work includes the novel coupling of economics and environmental impact through integration of a social cost of carbon such that a more holistic assessment can be performed.
Most hydropower utilities rely on external forecast products provided by NOAA River Forecast Centers and/or an additional source from private industry to support the scheduling of hydropower operations. The producers of these forecasts ÃƒÂ¢Ã¢â€šÂ¬Ã¢â‚¬Å“ NOAA, industry, and even in-house forecasters ÃƒÂ¢Ã¢â€šÂ¬Ã¢â‚¬Å“ do not have access to the dynamic energy prices (production cost models) or the electricity tradersÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢ strategies to maximize revenue from utilization of the hydropower assets. Therefore, the group operating the reservoir is unable to assess the market value of their inflow forecasts, eliminating any ability to target forecast improvements to increase contributions of hydropower to electrical system needs. Both NOAA and industry have reached out to DOE WPTO to understand which inflow forecast products and accuracy levels would be needed to enhance the value of forecasts, from water management and marketed hydropower and grid resilience perspectives. We propose to use inflow forecast, reservoir and power system model simulations, and case studies to practically demonstrate where forecast improvements would create the most value for hydropower services. This research will benefit utilities and other hydropower operators who utilize flow forecasting to support water management and electricity production; it will also support DOE in targeting future investments related to forecasting that will benefit these groups.
We will develop a framework for characterizing the uncertainty on the performance of electric power systemÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢s assets and for using that uncertainty characterization in the operations of electricity markets (including scheduling, dispatch, pricing,and settlement). We will focus on the uncertainty of bulk renewables (wind farms, solar PV farms, and hydropower) w/o energy storage systems, but will also consider smaller scale renewables in the system that are either directly participating in wholesale markets, or behind-the meter, impacting load.
This project will develop an improved understanding of the coupled dynamics among the natural processes that underpin drought and poor air quality, the human systems that manage water resources and electricity supply, and localized human exposure to fine particulate matter and ozone pollution, all under the influence of two anthropogenic drivers: technology adoption and climate change.
Primary objective is to co-advise a graduate student at UNC Chapel Hill in the development of Life Cycle Analysis and Techno-economic Analysis models of algal biofuel facilities, particularly considering uncertainty in environmental and market-based processes. The system design and plant operations of modeled facilities will be simulated using an existing Matlab model that represents alternative system configurations, project finance, plant operations (cultivation, harvesting and downstream conversion), discounted cashflow analysis and life cycle measures of environmental and financial sustainability. Key project goals include investigation of the impacts of high pH and high alkalinity growth on system energy requirements, culture stability, and overall economic competitiveness
The electrical grid in California is changing quickly, driven primarily by aggressive state supported targets that aim to produce 50% of the stateÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢s electricity from renewable sources by 2030, with this percentage likely to increase even more by 2050. This will entail substantial changes to the stateÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢s current generating portfolio, which relies predominately on a combination of natural gas and hydropower. Today, when drought impacts California, the state experiences a significant decrease in hydropower production. Utilities are forced to replace this lost hydropower with more expensive generation from natural gas plants, which increases the wholesale price of electricity. In this project, Dr. Kern will model the operations of CaliforniaÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢s power system, including its interactions with important import markets in the Pacific Northwest and Southwest, under a wide range of future scenarios, while tracking system behavior and wholesale and retail price dynamics. The operations of CaliforniaÃƒÂ¢Ã¢â€šÂ¬Ã¢â€žÂ¢s grid will be simulated using a multi-area ÃƒÂ¢Ã¢â€šÂ¬Ã…â€œUnit Commitment/Economic DispatchÃƒÂ¢Ã¢â€šÂ¬Ã‚Â (UC/ED) model that captures power flows among the major California utilities and neighboring systems. This class of model is used by electric power utilities and researchers alike, to schedule generation in networks of power plants and study the behavior of power systems under different market, policy and environmental conditions.