All Years Seminars
[INMA] 2021-04-20 (14h) : Computation of Convex Hull Prices in Electricity Markets with Non-Convexities
At MS Teams
Speaker :
Panagiotis Andrianesis (Boston University, MA, USA)
Abstract : The presence of non-convexities in electricity markets has been an active research area for about two decades. The— inevitable under current marginal cost pricing — problem of guaranteeing that no market participant incurs losses in the day-ahead market is addressed in current practice through make-whole payments a.k.a. uplift. Alternative pricing rules have been studied to deal with this problem. Among them, Convex Hull (CH) prices associated with minimum uplift have attracted significant attention. Several US Independent System Operators (ISOs) have considered CH prices but resorted to approximations, mainly because determining exact CH prices is computationally challenging, while providing little intuition about the price formation rationale. In this paper, we describe the CH price estimation problem by relying on Dantzig-Wolfe decomposition and Column Generation, as a tractable, highly paralellizable, and exact method — i.e., yielding exact, not approximate, CH prices — with guaranteed finite convergence. Moreover, the approach provides intuition on the underlying price formation rationale. A test bed of stylized examples provides an exposition of the intuition in the CH price formation. In addition, a realistic ISO dataset is used to support scalability and validate the proof-of-concept.
[INMA] 2021-04-13 (14h) : Welcome Seminar for new postdocs (#2)
At MS Teams
Section 1:Event-Triggered Tracking Control of Networked Control Systems
Speaker :
Wei Ren
Abstract : In this talk, I will show how to deal with the tracking control problem of networked control systems under both multiple networks and event-triggered mechanisms. Multiple networks are to connect the plant and reference system with decentralized controllers to guarantee their information transmission, whereas event-triggered mechanisms are to reduce the information transmission via multiple networks. All networks are independent and asynchronous and have local event-triggered mechanisms, which are based on local measurements and determine whether the local measurements need to be transmitted. I will implement an emulation-based approach to develop a novel hybrid model for tracking control of networked control systems. Then, sufficient conditions are derived and decentralized event-triggered mechanisms are designed to ensure the tracking performance.
This is a joint work with Dimos V. Dimarogonas (KTH) and Raphael Jungers (UCLouvain).
Section 2:Uniform Signal Recovery from Non-Linear Observations
Speaker :
Stollenwerk, Alexander
Abstract : In this talk, I will consider the problem of estimating high-dimensional signal vectors from few non-linear measurements.
The focus will be on uniform recovery guarantees, that is, results which show that recovery succeeds for an entire class of signal vectors using a fixed
measurement ensemble. In the linear case, classical compressed sensing theory shows that efficient recovery algorithms exist, which are able to robustly estimate signals from very few measurements. The standing assumption in these type of results is that the signal vectors exhibit some form of low-complexity (e.g. sparsity), which the algorithm may exploit. In contrast to the well-understood linear case and despite significant results in various special cases, a general understanding of uniform recovery from non-linear observations is still missing. Taking a step in that direction, I will present a unified approach to this problem under the assumption of i.i.d. sub-Gaussian measurement vectors. This is joint work with Martin Genzel from Utrecht University.
[INMA] 2021-03-30 (14h) : Advanced analytics for Energy and Life Sciences applications
At MS Teams
Speaker :
Damien Lepage (N-SIDE)
,
and
Alexis Davin (N-SIDE)
Abstract :
N-SIDE is a spinoff from UCLouvain that combines advanced analytics with business know-how to deliver optimization solutions to actors of the Energy and Life Sciences industries. Damien Lepage and Alexis Davin (both graduated from EPL - UCLouvain) will present how they use Applied Mathematics in their daily jobs to solve the challenges of those actors.
In the Energy sector, we will present how mixed-integer programming can reduce investment costs in electrical grids at European level. We will also give an example of how Machine Learning can be used for time-series forecasting of interconnectors load.
In the Life Sciences sector we will talk about Monte Carlo simulations and optimization techniques to reduce waste and lower risk in clinical trials.
[INMA] 2021-03-23 (14h) : Computational Sensing via Signal Folding: Variations on a Theme
At MS Teams
Speaker :
Ayush Bhandari (Imperial College London, UK)
Abstract :
Digital data capture is the backbone of all modern day systems and “Digital Revolution” has been aptly termed as the Third Industrial Revolution. Underpinning the digital representation is the Shannon-Nyquist sampling theorem and more recent developments such as compressive sensing approaches. The fact that there is a physical limit to which sensors can measure amplitudes poses a fundamental bottleneck when it comes to leveraging the performance guaranteed by recovery algorithms. In practice, whenever a physical signal exceeds the maximum recordable range, the sensor saturates, resulting in permanent information loss. Examples include (a) dosimeter saturation during the Chernobyl reactor accident, reporting radiation levels far lower than the true value and (b) loss of visual cues in self-driving cars coming out of a tunnel (due to sudden exposure to light).
To reconcile this gap between theory and practice, we introduce the Unlimited Sensing framework or the USF that is based on a co-design of hardware and algorithms. On the hardware front, our work is based on a radically different analog-to-digital converter (ADC) design, which allows for the ADCs to produce modulo or folded samples. On the algorithms front, we develop new, mathematically guaranteed recovery strategies.
In the first part of this talk, we prove a sampling theorem akin to the Shannon-Nyquist criterion followed by certain variations on the theme. We show that, remarkably, despite the non-linearity in the sensing pipeline, the sampling rate only depends on the signal’s bandwidth. Our theory is complemented with a stable recovery algorithm. We then discuss sampling of sparse and parametric signals. Beyond the theoretical results, we will also present a hardware demo that shows our approach in action.
Moving further, we reinterpret the unlimited sensing framework as a generalized linear model that motivates a new class of inverse problems. We conclude this talk by presenting a research overview in the context of single-shot high-dynamic-range (HDR) imaging, sensor array processing and HDR computed tomography based on the modulo Radon transform.
[INMA] 2021-03-16 (14h) : Keep the phase! Signal recovery in phase-only compressive sensing
At MS Teams
Speaker :
Jacques, Laurent
Abstract :
In this seminar, we show how a sparse signal can be estimated from the phase of complex random measurements, in a "phase-only compressive sensing" (PO-CS) scenario. With high probability and up to a global unknown amplitude, we can perfectly recover such a signal if the sensing matrix is a complex Gaussian random matrix and the number of measurements is large compared to the signal sparsity. Our approach consists in recasting the (non-linear) PO-CS scheme as a linear compressive sensing model. We built it from a signal normalization constraint and a phase-consistency constraint. Practically, we achieve stable and robust signal direction estimation from the basis pursuit denoising program. Numerically, robust signal direction estimation is reached at about twice the number of measurements needed for signal recovery in compressive sensing.
This is a joint work with T. Feuillen (UClouvain)
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