INFORMS Open Forum

INFORMS-ENRE Online Scientific Event - 27 January 2022 - C. Lindsay Anderson & Vivienne Li (Cornell University)

  • 1.  INFORMS-ENRE Online Scientific Event - 27 January 2022 - C. Lindsay Anderson & Vivienne Li (Cornell University)

    Posted 01-22-2022 18:35
    Dear colleagues,

    Our first ENRE online event of the New Year takes place this coming Thursday January 27, 2022, starting at 15:00 GMT (UK time); see below for more details.

    Please feel free to forward this invitation to anyone who might be interested. For more information and recordings of past seminars, see

    We hope to see many of you on Thursday,
    Miguel Anjos and Lars Schewe


    27 January 2022 15:00-16:30 UK time (on Zoom) | C. Lindsay Anderson & Vivienne Li (Cornell University)
    Meeting ID: 844 6627 9844
    Passcode: ENRE2022

    Considering Electric Grid Robustness via a General Effective Resistance Measure (C. Lindsay Anderson)

    Increasing interconnection of renewable energy resources in electric power systems introduces potential network vulnerabilities. In this work we consider a vulnerability measure that quantifies the impact on the system global frequencies, due to small local perturbations to a node's natural frequency.
    Complex networks are frequently used to model coupled dynamical systems ranging from interacting molecules in chemical reactions to high voltage electric grids We apply this framework to high voltage electric grids where each node corresponds to a voltage phase angle associated with a bus and two nodes are connected to another by an edge where there exists a transmission line that connects the busses in the physical system. Given a fixed complex network topology with specific governing dynamics, our framework finds an optimal allocation of edge weights that minimizes the vulnerability measure(s) at the node(s) for which we expect perturbations to occur.

    C. Lindsay Anderson (Ph.D. Applied Mathematics, University of Western Ontario, Canada; M.Sc. and B.Sc Eng. University of Guelph, Canada) is currently an associate professor and the Interim Director of the Cornell Energy Systems Institute and at Cornell University. Previously, Lindsay was the Kathy Dwyer Marble and Curt Marble Faculty Director for Energy with the Cornell Atkinson Center for Sustainability. Her research interests are the application of optimization under uncertainty to large-scale problems in sustainable energy systems, and has been funded by the National Science Foundation, US Department of Energy, PSERC, and the National Science and Engineering Research Council of Canada.

    A Multi-Objective Adaptive Policy Search Approach for Microgrid Energy Management (Vivienne Liu)

    Microgrids are emerging as an effective and adaptive infrastructure option to promote distributed energy resource (DER) integration, and to engage end-use customers in efficient and responsive energy use. A major challenge of managing microgrids is to identify energy dispatch strategies that accommodate multiple conflicting objectives from diverse stakeholders and are robust to the significant uncertainties confronting their operations. Our study adopts the Evolutionary Multi-Objective Direct Policy Search (EMODPS) method and modifies it to be a multi-agent multi-objective evolutionary algorithm reinforcement learning framework to handle the daily energy management problem. We quantify the performance tradeoffs between economic profit, environmental impact, reliability of the system operation, and the effectiveness of battery use that emerge for different parametrized microgrid control policies on a case study. We demonstrate that the non-dominated alternative policies are adaptive to exogenous information and are collaborative between multiple agents. We further open the black box to interpret the high dimensional parameterized control policies regarding how, why, and when the exogenous information are being used by the optimized policies. The proposed framework provides a posteriori analysis with appropriate representation of stakeholder and climate priorities in the design and operation of microgrids, fostering positive outcomes for climate and society in general.

    Vivienne Liu is a PhD candidate in the field of Systems Engineering at Cornell University. Her research focuses on the application of modeling and algorithmic methods to improve the stochastic decision-making process for the operations of power systems. Vivienne holds a B.S. in Electrical Engineering from Tianjin University, China, and a M.S. in Electrical Engineering from Stanford University.

    Miguel F. Anjos, Ph.D., P.Eng., FHEA, SMIEEE, FEUROPT, FCAE
    President, INFORMS Section on Energy, Natural Resources, and the Environment (ENRE)
    Vice-President, INFORMS International Activities
    Chair of Operational Research, School of Mathematics, University of Edinburgh, U.K.
    Schöller Senior Fellow, University of Erlangen-Nürnberg, Germany