arXiv subjects

Roberto Minguez

Publications and source records attributed to Roberto Minguez.

3 recordsLinked to original sources

arXiv2025

Mixed extreme wave climate model for reanalysis databases

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, etc. However, reanalysis data is less accurate than instrumental records, making extreme data analysis derived from WRDB prone to under predict design return period values. This paper proposes a mixed extreme value model to deal with maxima, which takes full advantage of both (i) hindcast or wave reanalysis and (ii) instrumental records, reducing the uncertainty in its predictions. The resulting mixed model consistently merges the information given by both kinds of data sets, and it can be applied to any extreme value analysis distribution, such as generalized extreme value, peaks over threshold or Pareto-Poisson. The methodology is illustrated using both synthetically generated and real data, the latter taken from a given location on the northern Spanish coast.

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arXiv2025

Offshore wind farm layout optimization using mathematical programming techniques

Offshore wind power is a renewable energy of growing relevance in current electric energy systems, presenting favorable wind conditions in comparison with the sites on land. However, the higher energy yield has to compensate the increment in installation and maintenance costs, thus the importance of optimizing resources. One relevant aspect to increase profitability is the wind farm layout. The aim of this paper is to propose a new method to maximize the expected power production of offshore wind farms by setting the appropriate layout, i.e. minimizing the wake effects. The method uses a sequential procedure for global optimization consisting of two steps: i) an heuristic method to set an initial random layout configuration, and ii) the use of nonlinear mathematical programming techniques for local optimization, which use the random layout as an initial solution. The method takes full advantage of the most up-to-date mathematical programming techniques while performing a global optimization approach, which can be easily parallelized. The performance of the proposed procedure is tested using the German offshore wind farm Alpha Ventus, located in the North Sea, yielding an increment of expected annual power production of 3.52% with respect to the actual configuration. According to current electricity prices in Germany, this constitutes an expected profit increment of almost 1 M per year.

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arXiv2015

Robust Transmission Network Expansion Planning in Energy Systems: Improving Computational Performance

In recent advances in solving the problem of transmission network expansion planning, the use of robust optimization techniques has been put forward, as an alternative to stochastic mathematical programming methods, to make the problem tractable in realistic systems. Different sources of uncertainty have been considered, mainly related to the capacity and availability of generation facilities and demand, and making use of adaptive robust optimization models. The mathematical formulations for these models give rise to three-level mixed-integer optimization problems, which are solved using different strategies. Although it is true that these robust methods are more efficient than their stochastic counterparts, it is also correct that solution times for mixed-integer linear programming problems increase exponentially with respect to the size of the problem. Because of this, practitioners and system operators need to use computationally efficient methods when solving this type of problem. In this paper the issue of improving computational performance by taking different features from existing algorithms is addressed. In particular, we replace the lower-level problem with a dual one, and solve the resulting bi-level problem using a primal cutting plane algorithm within a decomposition scheme. By using this alternative and simple approach, the computing time for solving transmission expansion planning problems has been reduced drastically. Numerical results in an illustrative example, the IEEE-24 and IEEE 118-bus test systems demonstrate that the algorithm is superior in terms of computational performance with respect to existing methods.

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