Research Ongoing Funded Projects/ Recently Completed Projects

Ongoing Funded Projects

Mid-Atlantic Regional Integrated Sciences and Assessments (MARISA) (http://www.midatlanticrisa.org/)

If there’s anything that’s certain about the effects of climate change it’s how much is still uncertain. No one knows exactly how much sea levels will rise or local weather patterns (like storms) will change, making future planning extremely difficult for vulnerable coastal and floodplain areas. The Hobbs group and their colleagues are helping planners to better reckon with these uncertainties when making decisions about how we use and protect our coastlines and watersheds. MARISA is a project between JHU, the RAND Corporation, Penn State, and Cornell University. The center, currently funded for five years, was established by the National Oceanic and Atmospheric Administration to help stakeholders adapt to climate variability and change in the Chesapeake Bay Watershed. MARISA’s goal is to help water planners, transportation engineers, land-use developers, policy-makers, and other managers effectively deal with the questions that climate change is bringing about. A focus is on deciding how much adaptability to incorporate into a system while factoring in costs.

Coastal SEES Collaborative Research: Morphologic, Socioeconomic, and Engineering Sustainability of Massively Anthropic Coastal Deltas: the Compelling Case of the Huanghe Delta

Owing to their extraordinary natural resources and ecosystem services, river-delta coastlines host hundreds of millions of people worldwide. However, the sustainability of society on delta landscapes is uncertain, due to significant human influences including: 1) reduction of sediment - the life sustaining resource for any delta system - as a result of damming and leveeing of river channels, 2) disrupting natural sediment dispersal and deposition patterns within and along river-delta coastlines, 3) accelerated sinking of low-lying deltaic landscapes due to sub-surface water and fossil fuel extraction, and 4) sea-level rise, which threatens to drown deltaic landscapes. The overarching goal of this project is to evaluate river-delta sustainability by merging science that examines physical aspects of delta growth with socio-economic decisions. This research will provide guidance for the sustainable use of vulnerable delta resources, while promoting best engineering practices that protect society and infrastructure from disasters including river flooding, ocean storms, and sea-level rise. Additional broader impacts include training future scholars for the interdisciplinary field of coastal sustainability, creating an internet-based interface to promote global-citizen awareness in coastal sustainability, and developing teaching modules with complementary workshops intended for high-school courses on coastal science and sustainability for underrepresented groups in Houston and Los Angeles. This project is supported as part of the National Science Foundation's Coastal Science, Engineering, and Education for Sustainability program - Coastal SEES.

The crucial resource in building sustainable deltaic coastlines is sediment, and the key control on sediment delivery is river channel avulsions, relatively rapid displacements of river channels and the formation of new river channels. A multi-investigator, cross disciplinary team of researchers will address the following questions of fundamental importance to river-delta coastal sustainability: What are the socioeconomic consequences of altering river channel pathways on a highly utilized delta? Are current delta land loss mitigation strategies sustainable over long-range (decades to centuries) timescales? Can the location of significant future flooding events be predicted? These questions will be addressed using the Huanghe (Yellow River) delta, China as a case study. The Huanghe delta is a compelling region because it is one of the most dynamic and heavily urbanized coastal landscapes in the world. Lessons learned from the Huanghe delta will be exportable to evaluate the sustainability of delta coastlines worldwide. This project will build predictive models for coastal sustainability by bringing together the mechanics of avulsion on deltas, associated channel-shoreline interaction, socio-economic response to natural and engineered avulsions, and the resulting coupled human-natural system dynamics. U.S. researchers in cooperation with Chinese colleagues will create a template for multi-disciplinary coastal sustainability research to help guide future governance and decision making that integrates human-delta dynamics, societal objectives and uncertainty, hazard and land use engineering, coastal morphodynamics, and educational outreach. This project will evaluate whether massively anthropic coastal landscapes can be managed using engineered avulsions to minimize coastal erosion in the face of reduced sediment supply and rising sea level.

"PIRE: USA/Europe Partnership for Integrated Research and Education in Wind Energy Intermittency: From Wind Farm Turbulence to Economic Management"( Project Director: C. Meneveau, Johns Hopkins University)

This project is a US-European partnership for an integrated research and educational program for graduate and undergraduate students, post-docs and faculty. The international collaboration will address pressing research questions that arise when adding inherently intermittent wind sources to power systems. With billions of dollars to be invested in renewable power, improved understanding and better tools for effective use of sustainable but intermittent power sources are crucial. Research will be tightly integrated with a training program that includes carefully designed international experiences.

The project will develop improved knowledge about physical sources of variability and intermittency, such as atmospheric turbulence, and use it to develop next-generation tools for statistical characterizations of variability across multiple temporal and spatial scales. This information will be used for improving wind farm design, grid integration strategies and economic management of grid-integrated wind farms. Specifically, the study will focus on fluctuations at the seconds to hour time scale, for which turbulence within wind farms and micro-scale atmospheric flow variability are crucial. Next-generation computational fluid dynamics tools that (unlike traditional tools) describe fluctuation dynamics, will be developed and validated with laboratory and field observations. Results will be used to establish the statistical characterizations needed for next-generation modeling, forecasting, and control tools to manage fluctuations across various scales in the electric power system, from wind turbine dynamics and wind farm design to integration with power systems and energy markets. New optimal power flow tools that incorporate improved statistical characterizations of wind-farm output variability will be used to optimize resource siting and operations. Market mechanisms will be evaluated for incenting generation owners to respond rapidly to fluctuations and build flexible back-up plants, and for motivating consumers to adapt in real-time to changes in supply availability through demand response programs.

"SEP Collaborative: Integrating Heterogeneous Energy Resources For Sustainable Power Networks - A Systems Approach"( Project Director: Dennice F. Gayme, Johns Hopkins University)

Finding new and innovative means of integrating large amounts of renewable energy into the electric power grid while maintaining stability, reliability, security and efficiency will be critical for creating sustainable energy pathways that do not compromise the availability of resources for future generations.
Vision: This project will examine how control and design of large-scale and distributed energy resources can contribute to both stabilizing and improving the performance of power systems with high penetrations of renewable energy sources that provide variable and uncertain output. The research will involve a system theoretic end-to-end analysis from detailed source characterization (where wind is used as a surrogate for a portfolio of highly intermittent renewable sources) to propagation of these inputs through the transmission and distribution networks and include analyses of the impacts on system and market operations.

The project provides a framework and procedures for integrating approaches across several research communities. The problems addressed by traditional power system research such as stability and performance will be tied to new-generation fluid mechanics simulation tools that can provide high-fidelity characterizations of resource unsteadiness along with its spatio-temporal statistics. This information will be fed into to a continuum model of the power network (a partial differential equation that naturally encapsulates both spatial and temporal information). Connections between operational and market issues such as power flow regulation, grid management and risk mitigation strategies using storage and demand response will be made by leveraging a common set of tools based on optimization, convex relaxations and optimal control theory, which are common in both the economics and controls communities. Outputs from the continuum model will be inputs to these models. Practical solutions require stability and performance questions to be analyzed alongside the regulatory reforms necessary to enable resource purveyors to participate in power markets. Thus, regulatory and economic issues are integral to the proposed effort and sustainable energy pathways proposed via stability and operational analyses will be added to quantitative models that include policy and market constraints. Technical feasibility and efficiency will therefore inform proposed policy and market design changes.

"Performance and Effectiveness of Urban Green Infrastructure: Maximizing Benefits at the Subwatershed Scale through Measurement, Modeling, and Community-Based Implementation", EPA (Project Director: Arthur E. Mcgarity, Swarthmore College)

Philadelphia's Green City Clean Waters program provides a context for research on how best to manage innovative urban stormwater practices that reduce runoff volume at the source. Implementing this green infrastructure (GI) approach presents municipal officials in charge of urban sewer systems with new and complex challenges compared to the "gray" alternatives that are specified and designed by a handful of technical experts and approved by a committee of decision makers. This project intends to resolve the complexities of GI implementation by engaging in transdisciplinary research on methodologies, the results of which will guide municipal managers and regulators in the development of strategies to establish conditions in the various urban districts that lead to decisions being made, by the thousands of individual decision makers, that cumulatively contribute positively to the desired program goals.

Leading by Dr. Arthur McGarity with a team of experts from multiple disciplines to bring advanced techniques of measurement, modeling, and community based implementation, the project team bears on this problem with the primary goal of maximizing benefit within a context of realistic constraints on overall cost, equitable distribution of benefits, and political feasibility. A fundamental aspect of our research approach is the idea that these methodologies should be developed and applied from the “bottom-up” by engaging our municipal and community partners in all stages of the research and project design.

Press Coverage:
EPA Announces $5 Million in Grants for Green Infrastructure Research (1/21/2014)

"Transmission Investment Assessment Under Uncertainty Using a Multi-Stage Stochastic Model Approach with Recourse", US Department of Energy, Consortium for Electricity Reliability Technology Solutions

The introduction of electricity markets, together with increasing interregional trade and the integration of renewables, has made transmission expansion planning more complicated. Uncertainty about fuel prices, the location, amount, and type of new generation and about electricity demand means that transmission investments today may later be regretted as being the of the wrong type, amount or in the wrong location. Traditional deterministic planning methods cannot value the optionality and flexibility associated with particular investments as compared to alternatives whose consequences may be irreversible. Policy models, such NEMS or IPM, that can simulate interregional additions of transfer capability and generation investment and operation response to them implicitly assume that market players have perfect foresight and consistent beliefs over the entire time horizon and that they must commit irreversibly to a particular expansion path today. The resulting projections of transmission investment may be quite different from what investors will do in the face of pervasive economic, technological, and policy uncertainty, particularly if some of the alternative expansion paths allow investors to revise their choices in the future when the value of present uncertainties become better known. Unfortunately, most of the existing literature on transmission planning under uncertainty focuses on either simple one-period decision problems, one-period game-theoretic models with interactions between transmission and generation investment, or multi-period decision problems without these interactions that consider a highly simplified set of scenarios.

This project involves the development and application of a stochastic two- and three-stage modelling approach to capture the multistage nature of the planning problem together with the interaction of demand, generators, and transmission investors in the market in response to future uncertainties and possibilities for obtaining information. Both transmission investment and generation investment in response to transmission availability would be modelled. Multiple scenarios representing broadly different futures concerning fuel prices, load growth, carbon policy evolution, and the location, amount, and types of renewable investment will be defined. Within-year variability in load and wind output, accounting for interregional diversity, would be represented using an OPF framework. The OPF model would initially be a linear programming DC load flow representation, while a decomposition scheme will be developed that would enable use of the SuperOPF or similar models. This model would allow the following questions to be addressed. Are investments made considering uncertainties significantly and systematically different from investments resulting from a deterministic (single scenario) market or planning model? Do uncertainties in the 20202040 timeframe have implications for transmission investments being made now? What are the costs and benefits of increasing flexibility in transmission plans? Are there no-regrets transmission investments in the near-term that are beneficial under most or all scenarios? What are the economic costs that would result from disregarding uncertainties in transmission planning, and what is the value of better information concerning future uncertainties? Preliminary results for the UK available here.

 

Grants


- Mid-Atlantic Regional Integrated Sciences and Assessments (MARISA) program (NOAA, 5 years starting 9/2016; D. Knopman (RAND) Director; B. Hobbs JHU Co-Director).


- Yale-JHU SEARCH (Solutions for Energy, Air, Climate, and Health) Center (M. Bell (Yale) Director; B. Hobbs JHU Co-Director), 1/16-1/21


Recently Completed Porjects

"System Dynamics Analysis of Obesity", NIH (PI: Youfa Wang, JHSPH)

Lead by researchers from the Johns Hopkins Global Center for Child Obesity, we are developing and applying systems dynamics and agent-based models that represent the economic, behavioral, and physiological subsystems whose interactions determines the prevalence of obesity.

National Center for Earthsurface Dynamics, NSF Science & Technology Center, University of Minnesota

"EFRI-RESIN: Development of Complex Systems Theories and Methods for Resilient and Sustainable Electric Power and Communications Infrastructures", National Science Foundation

Microgrids are small-scale grids (~0.1-10 MW in size) that can be operated independently of the main grid. They can be supplied by a mix of renewable and fossil-generating units for improved sustainability and resiliency during both equipment failures and natural disasters. Microgrids, operated by businesses interacting in retail markets, will provide customers with appropriate incentives to participate in energy savings and grid survivability during emergency conditions. We consider the economic, environmental, and reliability benefits of such grids, considering how their interaction with regional power markets results in changes in operations and investments elsewhere. That work uses regional market models (based on the ECN COMPETES model, which was developed in cooperation with JHU) plus economic, emissions, and thermodynamic models of microgrid operation. More recently, we have focussed on the potential reliability and black-start benefits of microgrids to regional power systems. We are also using cooperative game theory to identify regulatory strategies to ensure that microgrids that have positive net social benefits are profitable in retail markets, while those with negative net benefits would not be.

The stated purpose of NCED is to transform management of ecosystems, resources, and land use, in part by enhancing the usefulness of channel and landscape modeling. By explicitly linking modeling to decision making, scientific information can be used effectively to inform managers and stakeholders about the consequences and performance of management alternatives, and simultaneously, decision analyses can provide feedback on what information would be most valuable for improving management. My NCED work focuses on the use of decision analysis to improve ecosystem restoration decisions. The major questions that are now being addressed by my groups NCED-funded research are: (1) How can we improve elicitation of expert judgment concerning probabilities? (2) What are the optimal mixes and designs of land building projects in the Mississippi Delta? (3) How can stakeholder value judgments be integrated with sediment budgets and engineering analysis to identify preferred strategies for reducing sediment loss in the Minnesota River basin, considering scientific and economic uncertainties? (4) What are the most effective ways to integrate expert judgments, stakeholder preferences, and scientific information in stream restoration?

"Model-based Methods for Debiasing Individual Probability Assessments: Theory and Experiments", National Science Foundation (With Robert Clemen, Duke U.)

Subjective probability elicitation is often conducted by risk and decision analysts to obtain probability distributions of uncertain variables that cannot be quantified by other means. Elicitations can be conducted either through interviews or surveys. There is a lot of guidance available on best practices for interview-style elicitations, however, this guidance is lacking for survey-style elicitations. Survey style elicitations are prone to cognitive biases, some of which can be minimized through survey design and some which are present even in the most carefully designed survey. Even expert judgments are subject to variety of biases such as partition dependence, carryover, and overconfidence. The objectives of this research study are: (1) to identify cognitive biases present in elicitation surveys (including partition-dependence, over-confidence, and carry-over bias), (2) to develop model-based approaches to quantify the magnitude and correct for the biases, and (3) to offer guidance on structuring elicitation surveys to minimize biases. Our testing of the models is based upon a survey of Duke University students and a more extensive web-based survey designed to test hypotheses concerning the effect of survey design on the biases.