Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

MA45

2 - Optimizing the Use of CO2 Bulk Energy Storage for Transmission Deferral

factorization, and eigenvalue decomposition. We revamp the traditional PDIP method by embedding a sparse clique-factorization MC during each PDIP iteration. The MC method avoids substantial consensus equality constraints associated with the existing approaches and is more flexible to be performed in a parallel fashion. Numerical experiments demonstrate the effectiveness of our approaches. 4 - Robust Decentralized Secondary Frequency Control in Power Systems: Merits and Trade-Offs Changhong Zhao, National Renewable Energy Laboratory, Lakewood, CO, 80401, United States, Erik Weitenberg, Yan Jiang, Enrique Mallada, Claudio De Persis, Florian D÷rfler Frequency restoration in power systems is conventionally performed by broadcasting a centralized signal to local controllers. As a result of the energy transition, technological advances, and the scientific interest in distributed control and optimization methods, a plethora of distributed frequency control strategies have been proposed recently that rely on communication amongst local controllers. In this paper we propose a fully decentralized leaky integral controller for frequency restoration that is derived from a classic lag element. We study steady-state, asymptotic optimality, nominal stability, input-to-state stability, noise rejection, transient performance, and robustness properties of this controller in closed loop with a nonlinear and multivariable power system model. We demonstrate that the leaky integral controller can strike an acceptable trade-off between performance and robustness as well as between asymptotic disturbance rejection and transient convergence rate by tuning its DC gain and time constant. We compare our findings to conventional decentralized integral control and distributed averaging-based integral control in theory and simulations. n MA45 North Bldg 228A Joint Session ENRE/Practice Curated: Power Systems Analytics Sponsored: Energy, Natural Res & the Environment/Electricity Sponsored Session Chair: Shmuel S. Oren, University of California-Berkeley, Berkeley, CA, 94720-1777, United States Co-Chair: Georgios Patsakis, University of California Berkeley, University of California Berkeley, Berkeley, CA, 94702, United States 1 - An Oligopoly Power Market Model in Presence of Strategic Prosumers Sepehr Ramyar, University of California-Santa Cruz, Santa Cruz, CA, United States, Yihsu Chen We investigate the formation of wholesale power prices in presence of strategic prosumers and analyze how the unconventional behavior of agents capable of consumption and generation at the same time can impact wholesale power markets. In this study, the price is determined endogenously by strategic prosumers along with other market participants. We study the behavior of prosumers under price-taking assumption and then contrast it with results from Cournot oligopoly with strategic prosumers. We discuss and report the results of price and social surplus implications. 2 - Sequential Pricing and Intermittent Supply in Electricity Markets with Heterogeneous Traders Motivated by the ongoing integration of renewable energy sources, we analyze sequential market pricing in short-term electricity markets with producers operating under heterogeneous constraints. We propose a multi-stage competitive equilibrium model to analyze retailers and heterogeneous producers’ optimal sequential trading. The simulated value of flexibility, indicating a first-mover advantage, is validated empirically for different countries. 3 - Comparison of Tools to Address Profound Uncertainty in Power Systems Evangelia Spyrou, Johns Hopkins University, 3400 N. Charles Street, Geography and Environmental Engineer, Baltimore, MD, 21218, United States, Benjamin Field Hobbs Many tools have been developed to aid decision making under uncertainty. However, most power system analyses tend to use a single particular tool such as stochastic programming or robust optimization. Here, we critically review available tools including Robust Decision Making, which is widely used by the climate change adaptation community, and discuss their strengths and weaknesses. We investigate both theoretical properties of the tools and their practical performance through examples drawn from World Bank studies of climate and conflict risks. Derck Koolen, Rotterdam School of Management, Chris Bennekerslaan 29Q, Rotterdam, 3061EB, Netherlands, Wolfgang Ketter, Liangfei Qiu, Alok Gupta

Ramteen Sioshansi, Associate Professor, The Ohio State University, 240 Baker Systems Engineering Building, 1971 Neil Avenue, Columbus, OH, 43210-1271, United States, Jonathan D. Ogland- Hand, Jeffrey M. Bielicki, Ebony S. Nelson, Benjamin M. Adams, Thomas A. Bushcheck, Martin O. Saar CO2-bulk energy storage (CO2-BES) can store electricity by compressing and injecting CO2 into the subsurface. Electricity is discharged by producing geothermally-heated CO2 and converting that heat into electricity. We investigate the value that CO2-BES may have for transmission line deferral when electricity that is generated from a Class 5 wind resource in Wyoming is sold to a high- demand location in California. Results suggest that CO2-BES can increase revenue with less transmission capacity and can have value for transmission deferral, especially if revenue is earned for storing CO2. 3 - Sociotechnical Network Analysis for Power Grid Resilience in South Korea Daniel Eisenberg, Arizona State University, 1828 Menerini Place, Martinez, CA, 94553, United States, Thomas Seager, Jeryang Park Critical infrastructure resilience depends on the functionality of technical components and the actions taken by people to adapt to surprise. Here, we study how social and technical networks influence each other by linking a network model of blackout management in South Korea to a corresponding electric power grid network. Results show that Korean power companies receiving equivalent treatment in emergency management protocols are affected by blackouts in markedly different ways. Also, the comparison between static and time-variant analyses indicate that the roles of organizations shift depending on methods used. n MA44 North Bldg 227C Computational Problems Related to Optimal Power Flow Sponsored: Energy, Natural Res & the Environment/Electricity Sponsored Session Chair: Andy Sun, Georgia Institute of Technology, Atlanta, GA, 30312, United States 1 - A Stability-constrained Optimization Framework for Nonlinear Systems with Applications in Power Grids Qifeng (Evan) Li, MIT, Cambridge, MA, United States This talk will present a steady-state optimization framework for nonlinear control systems with their dynamic stability taken into account. Generally, the dynamics of a control system is captured by a set of differential-algebraic equations (DAEs). Adding the DAEs to the steady-state optimization framework as constraints results in a DAE-constrained problem. An existing mature approach for solving the DAE-constrained optimization problems is the “discretize-then-optimize method. However, it is not suit for solving the DAE-constrained problems in large-scale systems. Differently, the proposed approach estimates the stability region based on a convex Lyapunov function and projects it onto the steady-state domain as algebraic constraints on the control variables of the steady-state optimization problem. The proposed stability-constrained optimization framework can be applied to many types of nonlinear systems, such as Lur’e, polynomial, and non-polynomial systems. In this talk, I will illustrate the idea of the proposed approach based on an application scenario in power grids, which can be formulated as Lur’e systems. The construction of convex Lyapunov functions for Lur’e, polynomial, and non-polynomial systems will also be discussed respectively. 2 - Joint State Estimation and Sparse Topology Error Detection for Nonlinear Power Systems SangWoo Park, UC Berkeley, Berkeley, CA, United States, Reza Mohammadi-Ghazi, Javad Lavaei This paper proposes a new technique for robust state estimation (SE) in the presence of a small number of topological errors for power systems modeled by AC power flow equations. The developed method leverages the availability of a large volume of SCADA measurements and minimizes the L1 norm of nonconvex residuals augmented by a nonlinear, but convex, regularizer. We show that under mild conditions, the solution obtained by the designed estimator identifies a small subgraph of the network that can be used to find topological errors in the model. Furthermore, we develop a theoretical upper bound on the SE error. The efficacy of the method is demonstrated through numerical simulations on IEEE test systems. 3 - Matrix Completion Embedded PDIP Method for SDP Relaxation of Large-scale OPF Problems Na Li, Harvard University, 33 Oxford Street, MD 147, Cambridge, MA, 02138, United States, Rui Li, Shengwei Mei Semidefinite programming (SDP) relaxation has been used to solve nonconvex OPF problems. Bottlenecks in solving large-scale SDP with primal-dual interior- point (PDIP) method primarily exist in matrix multiplication, Cholesky

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