Energy Systems Research
Energy systems research in the IEOR Department focuses on modeling, analysis, and optimization of energy systems and, in particular, power systems. Our department is affiliated with PSERC (power systems engineering research center) of which Dr. Oren is a co-founder and site director, with CERTS (center for electric reliability technology solutions). Research activities have focused on a variety of topics including power systems economics, electricity market design, energy and environmental regulation, demand response, renewables integration, energy risk management, and the development of computational tools for planning, operation, and analysis of electric power systems. The research has been funded by PSERC, DOE, ARPA-E, NSF, FERC, CERTS, EPRI, LLNL, and the SIEMENS Co. The program boasts a long list of distinguished alums that currently hold academic faculty positions in power systems, economics, and operations research and executive positions in energy-related industries including electric utilities, energy trading, and consulting companies.
Faculty
Selected Publications
Estimating and Incentivizing Imperfect-Knowledge Agents with Hidden Rewards
Dogan, Ilgin & Shen, Max & Aswani, Anil. (2023). Estimating and Incentivizing Imperfect-Knowledge Agents with Hidden Rewards. 10.48550/arXiv.2308.06717.
Big data-driven decoupling framework enabling quantitative assessments of electric vehicle performance degradation
Zhao, Yang & Wang, Zhenpo & Shen, Max & Zhang, Lei & Dorrell, David & Sun, Fengchun. (2022). Big data-driven decoupling framework enabling quantitative assessments of electric vehicle performance degradation. Applied Energy. 327. 120083. 10.1016/j.apenergy.2022.120083.
Nonlinear Least Absolute Value Estimator for Topology Error Detection and Robust State Estimation
Park, Sangwoo & Mohammadi-Ghazi, Reza & Lavaei, Javad. (2021). Nonlinear Least Absolute Value Estimator for Topology Error Detection and Robust State Estimation. IEEE Access. PP. 1-1. 10.1109/ACCESS.2021.3118036.
Hybrid of fixed and mobile charging systems for electric vehicles: System design and analysis
Chengzhang, Wang & He, Fang & Shen, Max & Li, Meng. (2021). Hybrid of fixed and mobile charging systems for electric vehicles: System design and analysis. Transportation Research Part C: Emerging Technologies. 126. 103068. 10.1016/j.trc.2021.103068.
Assessment of battery utilization and energy consumption in the large-scale development of urban electric vehicles
Zhao, Yang & Wang, Zhenpo & Shen, Max & Sun, Fengchun. (2021). Assessment of battery utilization and energy consumption in the large-scale development of urban electric vehicles. Proceedings of the National Academy of Sciences. 118. e2017318118. 10.1073/pnas.2017318118.
Enhanced Modeling of Contingency Response in Security-constrained Optimal Power Flow
T. Altun, R. Madani, A. Atamtürk, R.Baldick, A. Davoudi. Enhanced Modeling of Contingency Response in Security-constrained Optimal Power Flow. BCOL Research Report 21.01, IEOR, University of California-Berkeley.
Mean–field moral hazard for optimal energy demand response management
Elie, Romuald & Hubert, Emma & Mastrolia, Thibaut & Possamaï, Dylan. (2019). Mean-field moral hazard for optimal energy demand response management.
Uniqueness of Power Flow Solutions Using Graph-theoretic Notions
Zhang, Haixiang & Park, Sangwoo & Lavaei, Javad & Baldick, R.. (2020). Uniqueness of Power Flow Solutions Using Graph-theoretic Notions.
Data-driven framework for large-scale prediction of charging energy in electric vehicles
Zhao, Yang & Wang, Zhenpo & Shen, Max & Sun, Fengchun. (2021). Data-driven framework for large-scale prediction of charging energy in electric vehicles. Applied Energy. 282. 116175. 10.1016/j.apenergy.2020.116175.
Smoothing Property of Load Variation Promotes Finding Global Solutions of Time-Varying Optimal Power Flow
Julie Mulvaney-Kemp, Salar Fattahi, and Javad Lavaei, Smoothing Property of Load Variation Promotes Finding Global Solutions of Time-Varying Optimal Power Flow, conditionally accepted for IEEE Transactions on Control of Network Systems, 2020.