Roberto Mínguez

University Carlos III de Madrid | UC3M

Intensity-duration-frequency (IDF) curves are commonly used in engineering practice for the hydraulic design of flood protection infrastructures and flood risk management. IDF curves are simple functions between the rainfall intensity, the timescale at which the rainfall process is studied, and the return period. This work proposes and tests a new...

Recent advances in Transmission Network Expansion Planning (TNEP) have demonstrated that two-stage adaptive robust optimization (ARO) renders the expansion planning problem tractable for real systems and, at the same time, constitutes a relevant approach to deal with uncertain demand and generation capacity in the TNEP problem. However, the use of...

A significant share of stochastic optimization problems in practice can be cast as two-stage stochastic programs. If uncertainty is available through a finite set of scenarios, which frequently occurs, and we are interested in accounting for risk aversion, the expectation in the recourse cost can be replaced with a worst-case function (i.e., robust...

Recent advances in cutting-plane strategies applied to robust optimization problems show that they are competitive with respect to problem reformulations and interior-point algorithms. However, although its application with polyhedral uncertainty sets guarantees convergence, finite termination when using ellipsoidal uncertainty sets is not theoreti...

This paper addresses the transmission network expansion planning problem under uncertain demand and generation capacity. A two-stage adaptive robust optimization framework is adopted whereby the worst-case operating cost is accounted for under a given user-defined uncertainty set. This work differs from previously reported robust solutions in two r...

Leak detectability or leakage awareness refers to the capability of sensing losses from a water supply system. Several methods exist in the technical literature to tackle this problem, but only few address it with a state estimation approach. The aim of this paper is to present a new methodology that enables probabilistic assessment of the extent t...

State estimation (SE) techniques can be applied to compute the most likely hydraulic state of a water distribution system from the available measurements at a given time. Different approaches exist in the technical literature to undertake such an analysis, but in all of them it is assumed that pump and valve statuses are known beforehand. Such cons...

The implementation of state estimation techniques to water systems enables the hydraulic state of a given network to be computed at any time. However, errors in both measurements and model parameters can severely affect the quality of the state estimate, thus sensitivity analysis is crucial to assess its performance. The aim of this paper is to pro...

Calibration of model parameters is of utmost importance to ensure the good performance of hydraulic simulation models. In this work, calibration is conceived within a joint multi-period parameter and state estimation approach, where model parameters (i.e. roughness coefficients) and hydraulic variables should be computed from available measurements...

Las técnicas de estimación de estado permiten determinar el estado hidráulico más probable de una red de abastecimiento a partir de las medidas disponibles en tiempo real. Pese a su interés a nivel académico, en el que estas técnicas han sido ampliamente trabajadas, apenas han sido implementadas en sistemas reales a nivel operacional. Esto supone u...

Recent breakthroughs in Dynamic Transmission Network Expansion Planning (DTNEP) have demonstrated that the use of robust optimization, while maintaining the full temporal dynamic complexity of the problem, renders the capacity expansion planning problem considering uncertainties computationally tractable for real systems. In this paper an adaptive...

State estimation techniques have been widely discussed in academia in the context of water distribution systems, but there are few real-life applications. The aim of this paper is to show the potential advantages of systematically implementing state estimation techniques for on-line monitoring water distribution systems. With this purpose, two stat...

Two-stage robust optimization has emerged as a relevant approach to deal with uncertain demand and generation capacity in the transmission network expansion planning problem. Unfortunately, the solution of practical large-scale instances remains a challenge. In order to address this issue, this paper presents an alternative column-and-constraint ge...

The aim of observability analysis (OA) is to determine if a given measurement setting is sufficient to compute the current status of a water distribution network. There are several approaches in the technical literature to making such an analysis. With all of them there is an assumption that the lie of the land of the network in terms of the status...

Nowadays, the transition from a conventional generation system to a renewable generation system is one of the most difficult challenges for system operators and companies. There are several reasons: the long-standing impact of investment decisions, the proper integration of renewable sources into the system, the present and future uncertainties, an...

Recent breakthroughs in Transmission Network Expansion Planning (TNEP) have demonstrated that the use of robust optimization, as opposed to stochastic programming methods, renders the expansion planning problem considering uncertainties computationally tractable for real systems. However, there is still a yet unresolved and challenging problem as r...

Implementation of state estimation (SE) techniques to water networks seems to be the best way to obtain as much information as possible from current monitoring systems. However, to guarantee the correct implementation of SE, the measurement configuration must be adequate, i.e., the network must be observable, as not any measurement distribution wou...

In this paper, an alternative uncertainty treatment for the traditional unconstrained weighted-least-squares (WLS) method is presented. This treatment enables hydraulic constraints (i.e., null demands at transit nodes or null flows at closed pipes, pumps, or valves, etc.), high-precision measurements, and upper and lower variable bounds (i.e., head...

Este artículo presenta una técnica alternativa a los métodos existentes en la literatura para el análisis de observabilidad (AO) de redes de agua, paso previo imprescindible para la adaptación de las técnicas de estimación de estado (EE) a estos sistemas. La metodología propuesta parte de un estado de flujo conocido y asume distribuciones aleatoria...

Robust optimization is a framework for modeling optimization problems involving data uncertainty and during the last decades has been an area of active research. If we focus on linear programming (LP) problems with i) uncertain data, ii) binary decisions and iii) hard constraints within an ellip-soidal uncertainty set, this paper provides a differe...

State estimation (SE) techniques are being applied to different network systems in order to convert system measurements into real information about the network state. SE applications to water systems are relatively novel, but these techniques have been implemented in other fields for decades. In those applications, observability analysis (OA) is re...

Recent advances on Transmission Network Expansion Planning (TNEP) demonstrate that the use of robust optimization, in contrast with respect to stochastic programming methods, make the expansion planning problem computationally tractable for real systems. State-of-the-art robust methods treat the problem as stationary during the study period, making...

This paper shows the complementary roles of mathematical and engineering points of view when dealing with truss analysis problems involving systems of linear equations and inequalities. After the compatibility condition and the mathematical structure of the general solution of a system of linear equations is discussed, the truss analysis problem is...

Structural reliability and decomposition techniques have recently proved to be appropriate tools for solving robust uncertain mixed-integer linear programs using ellipsoidal uncertainty sets. In fact, its computational performance makes this type of problem to be an alternative method in terms of tractability with respect to robust problems based o...

Recent advances about the problem of transmission network expansion planning propose the use of robust optimization techniques, as an alternative to stochastic mathematical programming methods, to make the problem tractable in realistic systems. They consider different sources of uncertainty, mainly related to the capacity and availability of gener...

Lagrangian trajectory models have been demonstrated to be a useful tool in oil spill response. Despite the improvements in this kind of models, surface drift prediction remains a difficult task plagued with uncertainties. This work presents a Stochastic Lagrangian Trajectory Model (SLTM) that quantifies the uncertainties in trajectory simulations a...

Structural-reliability based techniques has been an area of active research in structural design during the last decades, and different methods have been developed, such as First Order Second Moment (FOSM) or First Order Reliability (FORM) methods. The same has occurred with robust optimization, which is a framework for modeling optimization proble...

Mixed extreme value models (Mínguez et al., Stoch Environ Res Risk Assess 27:757–768, 2013b) have proved to be an appropriate tool for dealing with wave maxima because they take full advantage of upper tail information from both (1) hindcast or wave reanalysis and (2) instrumental records, which reduces the uncertainty on return level estimates. Ho...

Extreme sea conditions in the nearshore zone are required for coastal flood risk analysis and structural design. Many multivariate extreme value methods that have been applied in the past have been limited by assumptions relating to the dependence structure in the extremes. A conditional extremes statistical model overcomes a number of these previo...

This paper presents a detailed hindcast for the generation and propagation of sea state variables-significant wave height Hs, peak period Tp,mean direction θ, and spectral shape γ -σ -associated with cyclonic events to numerically diagnose their possible hydrodynamic effects over the northeastern Atlantic. An example of such cyclonic events is Hurr...

Engineering design of structural elements entails the satisfaction of different requirements during each of the phases that the structure undergoes: construction, service life and dismantling. Those requirements are settled in form of limit states, each of them with an associated probability of failure. Depending on the consequences of each failure...

This paper shows how Benders decomposition can be used for estimating the parameters of a fatigue model. The objective function of such model depends on five parameters of different nature. This makes the parameter estimation problem of the fatigue model suitable for the Benders decomposition, which allows us to use well-behaved and robust paramet...

The optimal engineering design problem consists in minimizing the expected total cost of an infrastructure or equipment, including construction and expected repair costs, the latter depending on the failure probabilities of each failure mode. The solution becomes complex because the evaluation of failure probabilities using First-Order Reliability...

The state estimator is a key tool in the operation of any real-world electric energy system. In this paper, a state estimator based on a weighted least squares model is proposed which is robust against outliers. This algorithm presents two relevant features: robustness that is achieved by readjusting measurement weights, and accuracy that is attain...

Accurate wave climate characterization, which is vital to understand wave-driven coastal processes and to design coastal and offshore structures, requires the availability of long term data series. Where existing data are sparse, synthetically generated time series offer a practical alternative. The main purpose of this paper is to propose a method...

A fully nonlinear Boussinessq-type model with several free coe�cients is con- sidered as a departure point. The model is monolayer and low order so as to simplify numerical solvability. The coe�cients of the model are here consid- ered functions of the local water depth. In doing so, we allow to improve the dispersive and shoaling properties for na...

This paper explores a new approach to lumped hydrological modelling based on general laws of growth, in particular using the classic logistic equation proposed by Verhulst. By identifying homologies between the growth of a generic system and the evolution of the flow at the outlet of a river basin, and adopting some complementary hypotheses, a comp...

The design of maritime structures requires information on sea state conditions that influence its behavior during its life cycle. In the last decades, there has been a increasing development of sea databases (buoys, reanalysis, satellite) that allow an accurate description of the marine climate and its interaction with a given structure in terms of...

Atmospheric particulate matter (PM) is made up of a mixture of solid and aqueous species which enter the atmosphere by anthropogenic and natural pathways. The levels and composition of ambient air PM depend on the climatology and on the geography (topography, soil cover, proximity to arid zones or to the coast) of a given region. Spain has particul...

Autoregressive logistic regression models have been successfully applied in medical and pharmacology research fields, and in simple models to analyze weather types. The main purpose of this paper is to introduce a general framework to study atmospheric circulation patterns capable of dealing simultaneously with: seasonality, interannual variability...

The extreme wave climate is of paramount importance for: (i) off-shore and coastal engineering design, (ii) ship design and maritime transportation, or (iii) analysis of coastal processes. Identifying the synoptic patterns that produce extreme waves is necessary to understand the wave climate for a specific location. Thus, a characterization of the...

Análisis Matemático y Estadístico de Variables Ambientales AMEVA. AMEVA es un software que está formado por un conjunto de funciones desarrollada en Matlab que in-tegra las diversas metodologías de análisis estadístico implementadas por los investigadores del Instituto de Hidráulica Ambiental, con el objeto de estudiar y caracterizar variables medi...

Wind wave reanalyses have become a valuable source of information for wave climate research and ocean and coastal applications over the last decade. Nowadays, wave reanalyses databases generated with third generation models provide useful wave climate information to complement, both in time and space, the instrumental measurements (buoys and alimet...

In the last decades, several tools for managing risks in competitive markets, such as the conditional value-at-risk, have been developed. These techniques are applied in stochastic programming models primarily based on scenarios and/or finite sampling, which in case of large-scale models increase considerably their size according to the number of s...

Hindcast or wave reanalysis databases (WRDB) constitute a powerful source with respect to instrumental records in the design of offshore and coastal structures, since they offer important advantages for the statistical characterization of wave climate variables, such as continuous long time records of significant wave heights, mean and peak periods...

The development of numerical wave prediction models for hindcast applications allows a detailed description of wave climate in locations where long-term instrumental records are not available. Wave hindcast databases (WHDBs) have become a powerful tool for the design of offshore and coastal structures, offering important advantages for the statisti...

This paper analyzes the multiple bad data originated by a gross error in any voltage or current transformer of the measurement equipment. Considering the statistical correlations among measurements, an identification algorithm based on the largest normalized residual test is specifically designed to deal with multiple bad data. Two case studies are...

This paper analyzes changes of maximum temperatures in Europe, which are evaluated using two state-of-the-art regional climate models from the EU ENSEMBLES project. Extremes are expressed in terms of return values using a time-dependent generalized extreme value (GEV) model fitted to monthly maxima. Unlike the standard GEV method, this approach all...

The prediction of drifting object trajectories in the ocean is a complex problem plagued with uncertainties. This problem is usually solved simulating the possible trajectories based on wind and advective numerical and/or instrumental data in real time, which are incorporated into Lagrangian trajectory models. However, both data and Lagrangian mode...

This paper proposes a decentralized state-estimation approach that relies on an elaborated instance of the Lagrangian relaxation decomposition technique. The proposed algorithm does notrequireacentralcoordinatorbutjusttomoderateinterchanges of information among neighboring regions, and exploits the struc- ture of the problem to achieve a fast and a...

Wave reanalysis databases (WRDBs) offer important advantages for the statistical characterization of wave climate (continuous time series, good spatial coverage, constant time span, homogeneous forcing, and more than a 40-yr-long time series) and for this reason, they have become a powerful tool for the design of offshore and coastal structures. Ho...

This paper analyzes and prospects about the application and development of some new key Information and Communication Technology (ICT) tools, at present and in the future, integrated in a new common platform, to improve costs, health and safety in offshore renewable energy infrastructure logistics process, installation tasks and maintenance operati...

In this work, we make use of two wave databases, satellite measurements and numerical modeling, to develop a methodology to obtain reliable estimates of the spatial and temporal variability of global wave energy resources. As a result, the global distribution of wave energy resources has been evaluated (since 1948) at a global scale analyzing its v...

Hindcast or Wave Reanalysis DataBases (WRDB) have become a powerful tool for the design of offshore and coastal structures, since they offer important advantages for the statistical characterization of extreme events (continuous time series, good spatial coverage, constant time span, homogeneous forcing, >; 40 year long time series). However, WRDB...

An important part of the future expansion of wind energy utilisation will come from offshore sites. The economic viability of offshore wind farms depends on the favourable wind conditions compared to sites on land, compensating the additional installation and maintenance costs. For project planning and sitting, especially for large projects, a reli...

Wind power is a renewable energy source increasingly attractive from an economic viewpoint and constitutes an alternative of growing relevance in current electric energy systems. The majority of operating wind farm turbines are on land, but it is expected that an important part of the future expansion of wind energy utilization, mainly in Europe, w...

In state estimation, the covariance matrix of residuals is used to compute the normalized residuals and to detect erroneous measurements. This paper describes a method based on sensitivity analysis that allows computing the residual covariance matrix. The proposed method is estimator-independent, i.e., it is suitable for most solution approaches ba...

Reliability based techniques has been an area of active research in structural design during the last decade, and different methods have been developed. The same has occurred with stochastic programming, which is a framework for modeling optimization problems involving uncertainty. The discipline of stochastic programming has grown and broadened to...

This paper presents a methodology based on transforming estimation methods in optimization problems in order to incorporate in a natural way some constraints that contain extra information not considered by standard estimation methods, with the aim of improving the quality of the parameter estimates. We include here three types of such information:...

Recent advances in the description of environmental and geophysical extreme events allow incorporating smooth time variations for the parameters of the GEV distribution using harmonic functions, long-term trends and covariates (North Atlantic Oscillation, El Niño, etc.). Most of the proposed models rely on the maximum likelihood estimation method f...

Currents, voltages, and voltage-current phase angles are directly measured in substations and converted through current complex measurement systems into power injection and power-flow measurements. Since voltages, currents, and phase angles are directly measured, they are affected by errors that are statistically independent and generally Gaussian...

Recent advances in the description of the natural variability of extreme events associated with ocean climate variables include time-dependent variations within a certain time scale (year, season or month). These models allow incorporating smooth time variations of the parameters of the GEV distribution and also the influence of covariates (NAO, El...

A probabilistic power flow model that takes into account spatially correlated power sources and loads is proposed. It is particularly appropriate to assess the impact of intermittent generators such as wind power ones on a power network. The proposed model is solved using an extended point estimate method that accounts for dependencies among the in...

Coastal zones are particularly vulnerable to climate variability and change. One of the major concerns is sea level rise and how climate change effects will vary by region, and over time. A key issue within risk assessment methods in coastal areas is the characterization of sea level, i.e., the probability distribution of sea level in a given horiz...

In recent years, the availability of spatial observations from satellite and information provided by reanalysis models allows us to use gridded data records of different geophysical variables, such as sea level, sea surface temperature, significant wave height, etc., which require new methods capable of exploring both the global and local character...

It is well known that the seasonal-to-interannual variability of extreme wave climate is linked to the anomalies of the atmosphere circulation. In this work, we analyze the relationships between extreme significant wave height at a particular site and the synoptic-scale weather type. We combine a time-dependent Generalized Extreme Value (GEV) model...

In recent years, there has been an increasing interest in studying the impacts of climate extremes in different sectors (agriculture, energy, insurance, etc.). In particular, extreme temperatures and heat waves have had a big impact in European socioeconomic activities during the last years (e.g. the 2003 heat wave in France); moreover, climate cha...

Wind power – a renewable energy source increasingly attractive from an economic viewpoint – constitutes an electricity production alternative of growing relevance in current electric energy systems. However, wind power is an intermittent source that cannot be dispatched at the will of the producer. Modeling wind power production requires characteri...

During the last decade, there has been a substantial interest in how to determine the optimal number and locations of traffic counters for origin-destination (OD) trip matrices estimation. On the contrary, the optimal allocation of plate scanning devices has received very limited attention, even though several authors have demonstrated that plate s...