Steven H. Low

California Institute of Technology, Pasadena, California, United States

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Publications (272)158.96 Total impact

  • Lingwen Gan · Steven H. Low

    No preview · Article · Jan 2016 · IEEE Journal on Selected Areas in Communications
  • Qiuyu Peng · Steven Low
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    ABSTRACT: The optimal power flow (OPF) problem is funda- mental in power distribution networks control and operation that underlies many important applications such as volt/var control and demand response, etc.. Large-scale highly volatile renewable penetration in the distribution networks calls for real-time feed- back control, and hence the need for distributed solutions for the OPF problem. Distribution networks are inherently unbalanced and most of the existing distributed solutions for balanced networks do not apply. In this paper we propose a solution for unbalanced distribution networks. Our distributed algorithm is based on alternating direction method of multiplier (ADMM). Unlike existing approaches that require to solve semidefinite programming problems in each ADMM macro-iteration, we exploit the problem structures and decompose the OPF problem in such a way that the subproblems in each ADMM macro- iteration reduce to either a closed form solution or eigen-decomposition of a 6x6 hermitian matrix, which significantly reduce the convergence time. We present simulations on IEEE 13, 34, 37 and 123 bus unbalanced distribution networks to illustrate the scalability and optimality of the proposed algorithm.
    No preview · Article · Dec 2015
  • Yunjian Xu · Steven H. Low
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    ABSTRACT: Being widely used in many deregulated wholesale electricity markets, the locational marginal pricing (LMP) mechanism is known to achieve social optimality in a competitive market. When profit-maximizing generators act strategically to manipulate prices; however, LMP may lead to high loss of economic efficiency. In this paper, we apply the Vickrey-Clarke-Groves (VCG) mechanism to wholesale electricity markets. We show that the VCG mechanism minimizes the total cost at a truth-telling dominant strategy equilibrium. We establish an important comparative result that the VCG mechanism always results in higher per-unit electricity prices than the LMP mechanism under any given set of reported supply curves. Numerical results show that the difference between the per-unit prices resulting from the two mechanisms is negligibly small (about 4%) in the IEEE 14-bus and 30-bus test systems. Finally, we apply the VCG mechanism to a day-ahead setting with start-up cost (of conventional generators) and intermittent renewable generation. We show that the VCG mechanism induces the truth-telling behavior of conventional generators in dominant strategies and yields each conventional generator a non-negative expected profit.
    No preview · Article · Oct 2015 · IEEE Transactions on Smart Grid
  • Qiuyu Peng · Yujie Tang · Steven H. Low
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    ABSTRACT: The feeder reconfiguration problem chooses the on/off status of the switches in a distribution network in order to minimize a certain cost such as power loss. It is a mixed-integer nonlinear program and, hence, hard to solve. In this paper, we propose a heuristic algorithm that is based on the recently developed convex relaxation of the ac optimal power flow problem. The algorithm is computationally efficient and scales linearly with the number of redundant lines. It requires neither parameter tuning nor initialization for different networks. It successfully computes an optimal configuration on all four networks we have tested. Moreover, we have proved that the algorithm solves the feeder reconfiguration problem optimally under certain conditions for the case where only a single redundant line needs to be opened. We also propose a more computationally efficient algorithm and show that it incurs a loss in optimality of less than 3% on the four test networks.
    No preview · Article · Jul 2015 · IEEE Transactions on Power Systems
  • Yunjian Xu · Na Li · Steven H. Low
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    ABSTRACT: We study the problem faced by an operator who aims to allocate a certain amount of load adjustment (either load reduction or increment) to multiple consumers so as to minimize the aggregate consumer disutility. We propose and analyze a simple uniform-price market mechanism where every consumer submits a single bid to choose a supply function from a group of parameterized ones. These parameterized supply functions are designed to ensure that every consumer's load adjustment is within an exogenous capacity limit that is determined by the current power system operating condition. We show that the proposed mechanism yields bounded efficiency loss at a Nash equilibrium. In particular, the proposed mechanism is shown to achieve approximate social optimality at a Nash equilibrium, if the total capacity limit excluding the consumer with the largest one is much larger than the total amount of load to be adjusted. We complement our analysis through numerical case studies.
    No preview · Article · May 2015 · IEEE Transactions on Power Systems
  • Changhong Zhao · Enrique Mallada · Steven H. Low
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    ABSTRACT: We design a distributed secondary frequency control scheme for both generators and controllable loads. The proposed scheme operates via local sensing and computation, and neighborhood communication. Equilibrium and stability analysis of the closed-loop system is performed with a power network model including turbines and governors of generators and nonlinear AC power flows. After a change in power supply or demand, the proposed scheme is able to stabilize the system, restore bus frequencies and net inter-area power exchanges, and minimize total generation cost minus user utility at equilibrium.
    No preview · Article · Apr 2015
  • Qiuyu Peng · Anwar Walid · Jaehyun Hwang · Steven H. Low
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    ABSTRACT: Multi-path TCP (MP-TCP) has the potential to greatly improve application performance by using multiple paths transparently. We propose a fluid model for a large class of MP-TCP algorithms and identify design criteria that guarantee the existence, uniqueness, and stability of system equilibrium. We clarify how algorithm parameters impact TCP-friendliness, responsiveness, and window oscillation and demonstrate an inevitable tradeoff among these properties. We discuss the implications of these properties on the behavior of existing algorithms and motivate a new design that generalizes existing algorithms and strikes a good balance among TCP-friendliness, responsiveness, and window oscillation. We have implemented our algorithm in the Linux kernel. We use our prototype to compare the new algorithm with existing MP-TCP algorithms.
    No preview · Article · Jan 2015 · IEEE/ACM Transactions on Networking
  • Samira Sojoudi · Steven H. Low · John C. Doyle
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    ABSTRACT: Many existing fluid-flow models of the Internet congestion control algorithms make simplifying assumptions on the effects of buffers on the data flows. In particular, they assume that the flow rate of a TCP flow at every link in its path is equal to the original source rate. However, a fluid flow in practice is modified by the queueing processes on its path, so that an intermediate link will generally not see the original source rate. In this paper, a more accurate model is derived for the behavior of the network under a congestion controller, which takes into account the effect of buffering on output flows. It is shown how this model can be deployed for some well-known service disciplines such as first-in–first-out and generalized weighted fair queueing. Based on the derived model, the dual and primal-dual algorithms are studied under the common pricing mechanisms, and it is shown that these algorithms can become unstable. Sufficient conditions are provided to guarantee the stability of the dual and primal-dual algorithms. Finally, a new pricing mechanism is proposed under which these congestion control algorithms are both stable.
    No preview · Article · Dec 2014 · IEEE/ACM Transactions on Networking
  • Source
    Enrique Mallada · Changhong Zhao · Steven H. Low
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    ABSTRACT: Frequency control rebalances supply and demand while maintaining the network state within operational margins. It is implemented using fast ramping reserves that are expensive and wasteful, and which are expected to grow with the increasing penetration of renewables. The most promising solution to this problem is the use of demand response, i.e. load participation in frequency control. Yet it is still unclear how to efficiently integrate load participation without introducing instabilities and violating operational constraints. In this paper we present a comprehensive load-side frequency control mechanism that can maintain the grid within operational constraints. Our controllers can rebalance supply and demand after disturbances, restore the frequency to its nominal value and preserve inter-area power flows. Furthermore, our controllers are distributed (unlike generation-side), can allocate load updates optimally, and can maintain line flows within thermal limits. We prove that such a distributed load-side control is globally asymptotically stable and robust to unknown load parameters. Simulations are used to illustrate the properties of our solution.
    Full-text · Article · Oct 2014
  • Qiuyu Peng · Minghua Chen · Anwar Walid · Steven H. Low
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    ABSTRACT: Most mobile devices today come with multiple access interfaces, \emph{e.g.}, 4G and WiFi. Multipath TCP (MP-TCP) can greatly improve network performance by exploiting the connection diversity of multiple access interfaces, at the expense of higher energy consumption. In this paper, we design MP-TCP algorithms for mobile devices by jointly considering the performance and energy consumption. We consider two main types of mobile applications: realtime applications that have a fixed duration and file transfer applications that have a fixed data size. For each type of applications, we propose a two-timescale algorithm with theoretical guarantee on the performance. We present simulation results that show that our algorithms can reduce energy consumption by up to 22$\%$ without sacrificing throughput compared to a baseline MP-TCP algorithm.
    No preview · Article · Aug 2014
  • Chengdi Lai · Steven H. Low · Ka-Cheong Leung · Victor O.K. Li
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    ABSTRACT: The combination of loss-based TCP and drop-tail routers often results in full buffers, creating large queueing delays. The challenge with parameter tuning and the drastic consequence of improper tuning have discouraged network administrators from enabling AQM even when routers support it. To address this problem, we propose a novel design principle for AQM, called the pricing-link-by-time (PLT) principle. PLT increases the link price as the backlog stays above a threshold β, and resets the price once the backlog goes below β. We prove that such a system exhibits cyclic behavior that is robust against changes in network environment and protocol parameters. While β approximately controls the level of backlog, the backlog dynamics are invariant for β across a wide range of values. Therefore, β can be chosen to reduce delay without undermining system performance. We validate these analytical results using packet-level simulation.
    No preview · Article · Jun 2014 · ACM SIGMETRICS Performance Evaluation Review
  • Zhenhua Liu · Iris Liu · Steven Low · Adam Wierman
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    ABSTRACT: Demand response is crucial for the incorporation of renewable energy into the grid. In this paper, we focus on a particularly promising industry for demand response: data centers. We use simulations to show that, not only are data centers large loads, but they can provide as much (or possibly more) flexibility as large-scale storage if given the proper incentives. However, due to the market power most data centers maintain, it is difficult to design programs that are efficient for data center demand response. To that end, we propose that prediction-based pricing is an appealing market design, and show that it outperforms more traditional supply function bidding mechanisms in situations where market power is an issue. However, prediction-based pricing may be inefficient when predictions are inaccurate, and so we provide analytic, worst-case bounds on the impact of prediction error on the efficiency of prediction-based pricing. These bounds hold even when network constraints are considered, and highlight that prediction-based pricing is surprisingly robust to prediction error.
    No preview · Article · Jun 2014 · ACM SIGMETRICS Performance Evaluation Review
  • Source
    Lingwen Gan · Steven H. Low
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    ABSTRACT: Distribution networks are usually multiphase and radial. To facilitate power flow computation and optimization, two semidefinite programming (SDP) relaxations of the optimal power flow problem and a linear approximation of the power flow are proposed. We prove that the first SDP relaxation is exact if and only if the second one is exact. Case studies show that the second SDP relaxation is numerically exact and that the linear approximation obtains voltages within 0.0016 per unit of their true values for the IEEE 13, 34, 37, 123-bus networks and a real-world 2065-bus network.
    Preview · Article · Jun 2014
  • Lingwen Gan · Steven H. Low
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    ABSTRACT: We formulate optimal power flow problem for unbalanced multiphase radial networks. We show that there is an equivalent single-phase mesh network that has a radial structure at the macro-level and a clique structure corresponding to each line in the radial network. Existing sufficient conditions for exact semidefinite relaxation are therefore applicable to unbalanced multiphase networks. In particular, they imply that if a semidefinite relaxation is exact over each of the cliques in the mesh equivalent network, then it is exact for the entire network.
    No preview · Conference Paper · Jun 2014
  • Na Li · Lijun Chen · Changhong Zhao · Steven H. Low
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    ABSTRACT: Automatic generation control (AGC) regulates mechanical power generation in response to load changes through local measurements. Its main objective is to maintain system frequency and keep energy balanced within each control area so as to maintain the scheduled net interchanges between control areas. The scheduled interchanges as well as some other factors of AGC are determined at a slower time scale by considering a centralized economic dispatch (ED) problem among different generators. However, how to make AGC more economically efficient is less studied. In this paper, we study the connections between AGC and ED by reverse engineering AGC from an optimization view, and then we propose a distributed approach to slightly modify the conventional AGC to improve its economic efficiency by incorporating ED into the AGC automatically and dynamically.
    No preview · Conference Paper · Jun 2014
  • Source
    Steven H. Low
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    ABSTRACT: This tutorial summarizes recent advances in the convex relaxation of the optimal power flow (OPF) problem, focusing on structural properties rather than algorithms. Part I presents two power flow models, formulates OPF and their relaxations in each model, and proves equivalence relations among them. Part II presents sufficient conditions under which the convex relaxations are exact.
    Preview · Article · Jun 2014 · IEEE Transactions on Control of Network Systems
  • Changhong Zhao · Ufuk Topcu · Na Li · Steven Low
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    ABSTRACT: We present a systematic method to design ubiquitous continuous fast-acting distributed load control for primary frequency regulation in power networks, by formulating an optimal load control (OLC) problem where the objective is to minimize the aggregate cost of tracking an operating point subject to power balance over the network. We prove that the swing dynamics and the branch power flows, coupled with frequency-based load control, serve as a distributed primal-dual algorithm to solve OLC. We establish the global asymptotic stability of a multimachine network under such type of load-side primary frequency control. These results imply that the local frequency deviations on each bus convey exactly the right information about the global power imbalance for the loads to make individual decisions that turn out to be globally optimal. Simulations confirm that the proposed algorithm can rebalance power and resynchronize bus frequencies after a disturbance with significantly improved transient performance.
    No preview · Article · May 2014 · IEEE Transactions on Automatic Control
  • Source
    Qiuyu Peng · Steven H. Low
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    ABSTRACT: The optimal power flow (OPF) problem is fundamental in power system operations and planning. Large-scale renewable penetration calls for real-time feedback control, and hence the need for fast and distributed solutions for OPF. This is difficult because OPF is nonconvex and Kirchhoff's laws are global. In this paper we propose a solution for radial networks. It exploits recent results that suggest solving for a globally optimal solution of OPF over a radial network through the second-order cone program (SOCP) relaxation. Our distributed algorithm is based on alternating direction method of multiplier (ADMM), but unlike standard ADMM algorithms that often require iteratively solving optimization subproblems in each ADMM iteration, our decomposition allows us to derive closed form solutions for these subproblems, greatly speeding up each ADMM iteration. We present simulations on a real-world 2,065-bus distribution network to illustrate the scalability and optimality of the proposed algorithm.
    Preview · Article · Apr 2014
  • Qiuyu Peng · Steven H. Low
    [Show abstract] [Hide abstract]
    ABSTRACT: The optimal power flow (OPF) problem is fundamental in power system operations and planning. Large-scale renewable penetration calls for real-time feedback control, and hence the need for fast and distributed solutions for OPF. This is difficult because OPF is nonconvex and Kirchhoff's laws are global. In this paper we propose a solution for radial networks. It exploits recent results that suggest solving for a globally optimal solution of OPF over a radial network through the second-order cone program (SOCP) relaxation. Our distributed algorithm is based on alternating direction method of multiplier (ADMM), but unlike standard ADMM algorithms that often require iteratively solving optimization subproblems in each ADMM iteration, our decomposition allows us to derive closed form solutions for these subproblems, greatly speeding up each ADMM iteration. We present simulations on a real-world 2,065-bus distribution network to illustrate the scalability and optimality of the proposed algorithm.
    No preview · Article · Mar 2014 · Proceedings of the IEEE Conference on Decision and Control
  • Source
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    ABSTRACT: We study the role of a market maker (or market operator) in a transmission constrained electricity market. We model the market as a one-shot networked Cournot competition where generators supply quantity bids and load serving entities provide downward sloping inverse demand functions. This mimics the operation of a spot market in a deregulated market structure. In this paper, we focus on possible mechanisms employed by the market maker to balance demand and supply. In particular, we consider three candidate objective functions that the market maker optimizes - social welfare, residual social welfare, and consumer surplus. We characterize the existence of Generalized Nash Equilibrium (GNE) in this setting and demonstrate that market outcomes at equilibrium can be very different under the candidate objective functions.
    Preview · Article · Mar 2014 · Proceedings of the IEEE Conference on Decision and Control

Publication Stats

10k Citations
158.96 Total Impact Points

Institutions

  • 1970-2015
    • California Institute of Technology
      • • Division of Chemistry and Chemical Engineering
      • • Division of Engineering and Applied Science
      Pasadena, California, United States
  • 1992-2011
    • University of California, Berkeley
      • Department of Electrical Engineering and Computer Sciences
      Berkeley, CA, United States
  • 2008
    • KTH Royal Institute of Technology
      • School of Electrical Engineering (EE)
      Tukholma, Stockholm, Sweden
  • 2007
    • Pusan National University
      • Division of Electrical and Electronics Engineering
      Pusan, Busan, South Korea
    • CA Technologies
      New York, New York, United States
  • 2006
    • Princeton University
      • Department of Electrical Engineering
      Princeton, New Jersey, United States
  • 2005
    • Rensselaer Polytechnic Institute
      • Department of Electrical, Computer, and Systems Engineering
      Troy, NY, United States
  • 2001
    • University of California, Los Angeles
      • Department of Electrical Engineering
      Los Angeles, CA, United States
  • 1996-2001
    • University of Melbourne
      • Department of Electrical and Electronic Engineering
      Melbourne, Victoria, Australia
  • 1993-1995
    • AT&T Labs
      Austin, Texas, United States