Balasubramanian Sambasivam and Suman Saurabh, Post-doctoral Fellows, Energy Institute, The University of Texas at Austin.
Speaker Biography: Balasubramanian Sambasivam
Balasubramanian (Bala) Sambasivam is a Postdoctoral research fellow in the Operations Research and Industrial Engineering program and Energy Institute’s micro-to-macro research initiative at the University of Texas at Austin. He has a Ph.D. in energy transitions and sustainability from the Indian Institute of Science Bangalore, India, and a Master’s in renewable energy from the Technical University of Berlin, Germany. His research interests include energy system modeling, energy transitions, and OR problems related to energy applications.
Abstract: Optimal Resource Placement for Electric Grid Resilience via Network Topology
Extreme weather events such as hurricanes, snow and ice storms, and heavy thunderstorms pose significant threats to electric transmission and distribution networks and have caused major outages in the recent past. Designing electricity systems to be resilient against extreme weather threats is thus a critical objective of electricity system planners. In this study, we investigate the resilience of alternative electric grid configurations by adopting a stylized approach based on graph theory, probabilistic analysis, and simulation. We consider two alternative classes of electricity network topology: binary trees and rectangular lattices. For each topology, we derive the probabilities that customers located at various nodes in the network will continue to have power following a disaster, depending on the locations of resources (e.g., generators, storage units) in the network. Then, these probabilities are incorporated into the problem of optimally placing resources throughout the network. This is a cost-benefit problem that weighs the benefits of placing resources closer to customers -- that is, pursuing a distributed resilience strategy -- against the higher total cost of deploying a greater number of smaller resource units. Our analytical and numerical results thus shed light on the general circumstances in which centralized or distributed resilience strategies are preferable.
Speaker Biography: Suman Saurabh
Suman Saurabh is a Postdoctoral research fellow at the Energy Institute’s micro-to-macro research initiative. He has a Ph.D. in Engineering Sciences from Southern Illinois University. His research interests include energy and economy interaction, geomechanics, and energy transitions.
Abstract: An agent-based approach to studying energy and economic coupling in a limited-resourced society.
Organisms consume energy for maintaining life processes, growing and reproduction.Economies also behave in a similar way, consuming energy to produce economic outputs like goods and services, while building infrastructures (growing). In the field of biology, Kleiber’s law describes an allometric relationship indicating that a mammal’s metabolism grows sub-linearly with body mass, meaning a ten times larger animal does not consume ten times more energy from food. Research also shows similar sublinear scaling between Primary Energy Consumption (PEC) and Gross Domestic Product (GDP) of countries, provoking questions as to exactly how similar growth dynamics apply to both economies and biological systems. In this talk, I will address how Agent-Based Modeling (ABM) approach can be used to define (create) a simplistic energy-dependent economy to study scaling between energy consumption and the size of the economy. This agent based model is based on Ordinary Differential Equation (ODE) model, “HANDY (Human and Nature Dynamics)”. The motivation behind creating an ABM for an ODE was to explore “micro/individual” rules for agents in a system, where the “macro” results of HANDY ODE model can be reproduced using the “micro” ABM model. Additionally, the agent-based model also extends the HANDY model and tries to account for effect of model features like wealth ownership (individual vs communal) and distribution (e.g., inequality).
Some interesting results that have been seen in the model simulations are, first, the agent-based (“micro”) model was able to produce the same results as of the HANDY ODE (“macro”) model with some differences attributed to discrete behavior of the ABMs. Second, a simple random transaction algorithm of wealth between a pair of agents leads to an unequal wealth distribution among the agents. Third, individual wealth ownership leads to lesser population growth and consumption. Finally, the ABM produces a sublinear relation between resource consumption (analogue to PEC) and population (GDP) as in the real-world economic data.