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Feng Qiu

Publications and source records attributed to Feng Qiu.

85 records · Page 5Linked to original sources
arXiv2018

Distributed fiber sparse-wideband vibration sensing by sub-Nyquist additive random sampling

The round trip time of the light pulse limits the maximum detectable vibration frequency response range of phase-sensitive optical time domain reflectometry (ϕ-OTDR). Unlike the uniform laser pulse interval in conventional ϕ-OTDR, we randomly modulate the pulse interval, so that an equivalent sub-Nyquist additive random sampling (sNARS) is realized for every sensing point of the long interrogation fiber. For an ϕ-OTDR system with 10 km sensing length, the sNARS method is optimized by theoretical analysis and Monte Carlo simulation, and the experimental results verify that a wide-band spars signal can be identified and reconstructed. Such a method can broaden the vibration frequency response range of ϕ-OTDR, which is of great significance in sparse-wideband-frequency vibration signal detection, such as rail track monitoring and metal defect detection.

physics.ins-det↗
arXiv2018

Scheduling Post-Disaster Repairs in Electricity Distribution Networks

Natural disasters, such as hurricanes, earthquakes and large wind or ice storms, typically require the repair of a large number of components in electricity distribution networks. Since power cannot be restored before these repairs have been completed, optimally scheduling the available crews to minimize the cumulative duration of the customer interruptions reduces the harm done to the affected community. Considering the radial network structure of the distribution system, this repair and restoration process can be modeled as a scheduling problem with soft precedence constraints. As a benchmark, we first formulate this problem as a time-indexed ILP with valid inequalities. Three practical methods are then proposed to solve the problem: (i) an LP-based list scheduling algorithm, (ii) a single to multi-crew repair schedule conversion algorithm, and (iii) a dispatch rule based on $ρ$-factors which can be interpreted as Component Importance Measures. We show that the first two algorithms are $2$ and $\left(2 - \frac{1}{m}\right)$ approximations respectively. We also prove that the latter two algorithms are equivalent. Numerical results validate the effectiveness of the proposed methods.

math.OC↗
arXiv2017

Risk-Based Distributionally Robust Optimal Power Flow With Dynamic Line Rating

In this paper, we propose a risk-based data-driven approach to optimal power flow (DROPF) with dynamic line rating. The risk terms, including penalties for load shedding, wind generation curtailment and line overload, are embedded into the objective function. To hedge against the uncertainties on wind generation data and line rating data, we consider a distributionally robust approach. The ambiguity set is based on second-order moment and Wasserstein distance, which captures the correlations between wind generation outputs and line ratings, and is robust to data perturbation. We show that the proposed DROPF model can be reformulated as a conic program. Considering the relatively large number of constraints involved, an approximation of the proposed DROPF model is suggested, which significantly reduces the computational costs. A Wasserstein distance constrained DROPF and its tractable reformulation are also provided for practical large-scale test systems. Simulation results on the 5-bus, the IEEE 118-bus and the Polish 2736-bus test systems validate the effectiveness of the proposed models.

math.OC↗
arXiv2016

Multi-Period Do-Not-Exceed Limit for Variable Renewable Generation Dispatch Considering Discrete Recourse Controls

The do-not-exceed (DNE) limit method was proposed to accommodate more variable renewable generation (VRG) securely. However, the lack of involving discrete recourse control precludes this method from gaining more flexibility for better VRG integration. This letter formulates a multi-period DNE limit model considering continuous and discrete recourse controls. This model belongs to two-stage robust optimization with mixed integer recourse. A nested column-and-constraint generation approach is employed to solve this model. Case studies show the effectiveness of the proposed method.

eess.SY↗
arXiv2016

Scaled VIP Algorithms for Joint Dynamic Forwarding and Caching in Named Data Networks

Emerging Information-Centric Networking (ICN) architectures seek to optimally utilize both bandwidth and storage for efficient content distribution over the network. The Virtual Interest Packet (VIP) framework has been proposed to enable joint design of forwarding and caching within the Named Data Networking (NDN) architecture. The virtual plane of the VIP framework captures the measured demand for content objects, but does not reflect interest collapse and suppression in the NDN network. We aim to further improve the performance of the existing VIP algorithms by using a modified virtual plane where VIP counts are appropriately scaled to reflect interest suppression effects. We characterize the stability region of the modified virtual plane with VIP scaling, develop a new distributed forwarding and caching algorithm operating on the scaled VIPs, and demonstrate the throughput optimality of the scaled VIP algorithm in the virtual plane. Numerical experiments demonstrate significantly enhanced performance relative to the existing VIP algorithm, as well as a number of other baseline algorithms.

cs.IT↗
arXiv2016

An SQP Method Combined with Gradient Sampling for Small-Signal Stability Constrained OPF

Small-Signal Stability Constrained Optimal Power Flow (SSSC-OPF) can provide additional stability measures and control strategies to guarantee the system to be small-signal stable. However, due to the nonsmooth property of the spectral abscissa function, existing algorithms solving SSSC-OPF cannot guarantee convergence. To tackle this computational challenge of SSSC-OPF, we propose a Sequential Quadratic Programming (SQP) method combined with Gradient Sampling (GS) for SSSCOPF.At each iteration of the proposed SQP, the gradient of the spectral abscissa unction is randomly sampled at the current iterate and additional nearby points to make the search direction computation effective in nonsmooth regions. The method can guarantee SSSC-OPF is globally and efficiently convergent to stationary points with probability one. The effectiveness of the proposed method is tested and validated on WSCC 3-machine 9-bus system, New England 10-machine 39-bus system, and IEEE 54-machine 118-bus system.

math.OC↗
arXiv2016

Robust Defense Strategy for Gas-Electric Systems Against Malicious Attacks

This paper proposes a methodology to identify and protect vulnerable components of connected gas and electric infrastructures from malicious attacks, and to guarantee a resilient operation by deploying valid corrective actions (while accounting for the interdependency of gas pipeline network and power transmission network). The proposed mathematical formulation reduces to a tri-level optimization problem, where the lower level is a multiperiod economic dispatch of the gas-electric system, the middle level distinguishes the most threatening attack on the coupled physical infrastructures, and the upper level provides optimal preventive decisions to reinforce the vulnerable components and increase the system resilience. By reformulating the lower level problem as a mixed integer linear programming (MILP), a nested column-and-constraint generation (C\&CG) algorithm is developed to solve the min-max-min model. Case studies on two test systems demonstrate the effectiveness and efficiency of the proposed methodology.

math.OC↗
arXiv2016

Robust Risk-Constrained Unit Commitment with Large-scale Wind Generation: An Adjustable Uncertainty Set Approach

This paper addresses two vital issues which are barely discussed in the literature on robust unit commitment (RUC): 1) how much the potential operational loss could be if the realization of uncertainty is beyond the prescribed uncertainty set; 2) how large the prescribed uncertainty set should be when it is used for RUC decision making. In this regard, a robust risk-constrained unit commitment (RRUC) formulation is proposed to cope with large-scale volatile and uncertain wind generation. Differing from existing RUC formulations, the wind generation uncertainty set in RRUC is adjustable via choosing diverse levels of operational risk. By optimizing the uncertainty set, RRUC can allocate operational flexibility of power systems over spatial and temporal domains optimally, reducing operational cost in a risk-constrained manner. Moreover, since impact of wind generation realization out of the prescribed uncertainty set on operational risk is taken into account, RRUC outperforms RUC in the case of rare events. Three algorithms based on column and constraint generation (C&CG) are derived to solve the RRUC. As the proposed algorithms are quite general, they can also apply to other RUC models to improve their computational efficiency. Simulations on a modified IEEE 118-bus system demonstrate the effectiveness and efficiency of the proposed methodology

math.OC↗
arXiv2016

Data-Driven Real-Time Power Dispatch for Maximizing Variable Renewable Generation

Traditional power dispatch methods have difficulties in accommodating large-scale variable renewable generation (VRG) and have resulted in unnecessary VRG spillage in the practical industry. The recent dispatchable-interval-based methods have the potential to reduce VRG curtailment, but the dispatchable intervals are not allocated effectively due to the lack of exploiting historical dispatch records of VRG units. To bridge this gap, this paper proposes a novel data-driven real-time dispatch approach to maximize VRG utili-zation by using do-not-exceed (DNE) limits. This approach defines the maximum generation output ranges that the system can ac-commodate without compromising reliability. The DNE limits of VRG units and operating base points of conventional units are co-optimized by hybrid stochastic and robust optimization, and the decision models are formulated as mixed-integer linear programs by the sample average approximation technique exploiting historical VRG data. A strategy for selecting historical data samples is also proposed to capture the VRG uncertainty more accurately under variant prediction output levels. Computational experiments show the effectiveness of the proposed methods.

eess.SY↗
arXiv2015

Robust Unit Commitment Considering Strategic Wind Generation Curtailment

Wind generation is traditionally treated as a non-dispatchable resource and is fully absorbed unless there are security issues. To tackle the operational reliability issues caused by the volatile and non-dispatchable wind generation, many dispatch frameworks have been proposed, including robust unit commitment (RUC) considering wind variation. One of the drawbacks that commonly exist in those dispatch frameworks is increased demand on flexibility resources and associated costs. To improve wind dispatchability and reduce flexibility resource costs, in this paper, we propose a novel RUC model considering strategic wind generation curtailment (WGC). Strategic WGC can reduce wind uncertainty and variability and increase the visibility of wind generation capacity. As a result, the ramping requirement for wind generation will be reduced and ramp-up capability of wind generation can be increased, leading to reduced day-ahead operational cost with guaranteed operational reliability requirement of power systems. The economic benefits also include profits gained by wind farm by providing ramping-up capacities other auxiliary services. We also propose a solution algorithm based on the column and constraint generation (C&CG). Simulations on the IEEE 39-bus system and two larger test systems demonstrate the effectiveness of the proposed RUC model and efficiency of the proposed computational methodology.

math.OC↗
arXiv2014

Self-Organized Vortices of Circling Self-Propelled Particles and Curved Active Flagella

Self-propelled point-like particles move along circular trajectories when their translocation velocity is constant and the angular velocity related to their orientation vector is also constant. We investigate the collective behavior of ensembles of such circle swimmers by Brownian dynamics simulations. If the particles interact via a "velocity-trajectory coordination" rule within neighboring particles, a self-organized vortex pattern emerges. This vortex pattern is characterized by its particle-density correlation function $G_ρ$, the density correlation function $G_c$ of trajectory centers, and an order parameter $S$ representing the degree of the aggregation of the particles. Here, we systematically vary the system parameters, such as the particle density and the interaction range, in order to reveal the transition of the system from a light-vortex-dominated to heavy-vortex-dominated state, where vortices contain mainly a single and many self-propelled particles, respectively. We also study a semi-dilute solution of curved, sinusoidal-beating flagella, as an example of circling self-propelled particles with explicit propulsion mechanism and excluded-volume interactions. Our simulation results are compared with previous experimental results for the vortices in sea-urchin sperm solutions near a wall. The properties of the vortices in simulations and experiments are found to agree quantitatively.

physics.bio-ph↗
arXiv1999

Simulation of Hard Particles in a Phase-Separating Binary Mixture

We simulate the motion of spherical particles in a phase-separating binary mixture. By combining cell dynamical equations with Langevin dynamics for particles, we show that the addition of hard particles significantly changes both the speed and the morphology of the phase separation. At the late stage of the spinodal decomposition process, particles significantly slow down the domain growth, in qualitative agreement with earlier experimental data.

cond-mat.stat-mech↗