Start Date: | 4/25/2019 | Start Time: | 4:00 PM |
End Date: | 4/25/2019 | End Time: | 5:00 PM |
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Event Description Abstract: The increased incidence of extreme events and the associated socio-economic losses due to power outages during the last decades are evidence that enhancing the ability to rapidly re- store the functionality of the power system is a fundamental concern for operators and planners. The inherent uncertainty of these extreme events makes the solution to the economic restoration of the electricity network’s with network constraints challenging. In particular, the allocation of resources to quickly restore the system requires to make decisions in terms of what demands to serve and how to reconfigure the system dynamically.
The dynamic formation of microgrids is a potential solution for both pre-disturbance planning and post- disaster electric grid recovery efforts. There is a recent literature proposing a distribution level microgrid formation model that applies to radial distribution systems characterized by directed power flows. However, with high renewable penetration levels in future power systems, the flows are expected to be undirected even in distribution networks. We propose and develop a model to deal with the restoration process of future power systems, embedding some of the characteristics these systems are likely to have. More specifically, our formulation can deal with radial and meshed topologies, and it requires little pre-processing of the input data. Additionally, we extend the model to allow for possible mobile and fixed distributed generation technologies and distributed energy resources, and explicitly include demand responsive loads with a minimum satisfiability constraint. Thus, this extended formulation can be used as an operation and a short-term planning tool for the DG scenario-based location problem.
We also propose a heuristic approach to deal with the scalability issue for stochastic instances of the problem. We present results with systems up to 3012 nodes.
Bio-sketch: Alberto J. Lamadrid L. (Ph.D. Applied Economics and Management, Cornell University, 2012; M.A. Economics NYU, 2004; B.Sc. Electrical Engineering, Universidad de los Andes, Colombia, 2001) is an associate professor in the Economics Department at the College of Business and Economics, and in the Industrial and Systems Engineering Department at the P.C. Rossin College of Engineering and Applied Science at Lehigh University. He is a member of the Institute for Cyber Physical Infrastructure and Energy at Lehigh University, and he is also adjunct associate professor in the Johnson College of Business at Cornell University. He has participated in funded grants by NSF and the Department of Energy, as well as other awards funded by the state of Pennsylvania and EPRI. His research interests are in electricity markets, power systems, and energy economics. He has worked on topics involving multi- period stochastic optimization in electrical networks, modeling and strategic management of resilient interdependent systems, adoption of renewable energy sources and the valuation of power infrastructure assets. |
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