Recent News
Benjamin Hobbs gave a plenary talk at ESIG
--June 2019
Spyrou, E., Hobbs, B. F., Bazilian, M. D., & Chattopadhyay, D. (2019). Planning power systems in fragile and conflict-affected states. Nature Energy, 4(April) was published on Nature Energy and was selected as the cover of the April issue.
--March.18, 2019
Johns Hopkins Stochastic Multi-stage Integrated Network Expansion (JHSMINE) Formulation Version1
--Aug.3, 2017
Part of group members reunion at ESIG in Denver, 2019
Welcome to the Hobbs Energy & Environment Decisions Research Group at the Johns Hopkins University.
We use optimization, economics, and decision analysis to plan, operate, and analyze power systems and their environmental effects, and for ecosystem restoration. In this website, you can learn about the research questions we are interested in and the methods we use, be introduced to our students and graduates, and learn about Hopkins' graduate programs in environmental and energy systems & policy.
Our students study a range of systems analysis, economics, and statistical methods from courses within the EHE Systems & Policy Group, as well as other departments and schools in JHU (including Applied Mathematics & Statistics, SAIS, Civil & Mechanical Engineering, and Economics). These methods are widely used for private sector decisions (especially operation and design of engineered systems, power supply); public infrastructure (transport, water supply); and public policy (simulating how private market efficiency and pollution emissions will respond to public policy changes, and the incidence of benefits and costs). Our policy analysis work has a strong 'bottom-up' or engineering-economic flavor to it, including rich technological and environmental detail. Such detail permits more realistic understanding of how policy can affect, for instance, costs, air emissions, land use decisions, and fuel use in the electric power sector.
Example 1: Models to Optimize Transmission Grids for Renewable Energy
As one example of this type of modeling, we develop models for optimizing transmission grids for renewable energy that recognize the large uncertainties we face concerning where, what types, and the amounts of renewable sources that will be developed. In particular, we use two-stage stochastic programming to ask: what transmission investments should be made now, and which ones should be delayed, given the uncertain response of the power market to policy, technology, and economic changes? We applied this method first in the UK and now in the Western US (see the publications sector of this website). We found that disregarding uncertainty results in significantly inferior solutions, wasting money and decreasing the economic & environmental benefits of renewable power.
Example 2: Optimal Sediment Diversions to Restore the Mississippi River Delta
As another example, we have asked: what are the optimal sediment diversion sizes and configurations for restoring the Mississippi River Delta? We apply integer programming together with detailed models of water and sediment diversion and land building to identify cost-effective portfolios of so-called engineered avulsions. Design parameters include the width, depth, and vertical placement of each structure in the river's levee. The analysis shows that large avulsions reaching deep in the water column are essential for building large amounts of land.
What are our graduates doing now?
Graduates from this group are readily employed as consultants, engineers, public policy analysts, energy traders and planners, and faculty. There is a great need for graduates who are familiar with environmental & energy problems and processes, and who can use the methods of systems analysis & economics to provide quantitative answers to important planning & policy questions. See the Teaching section of this website for summaries of the educational opportunities that EHE together with other JHU divisions offer in this area.