http://hdl.handle.net/11531/816 Sun, 05 Apr 2026 17:18:29 GMT 2026-04-05T17:18:29Z http://hdl.handle.net/11531/24527 Título : Resilience in the Internet of things Autor : Vázquez Blanco, Antonio Resumen : Abstract—More than 6 billion pervasive devices have already been deployed as of 2017. The capacity of IoT to monitor and automatize any “thing” of the user every day life makes this technology appealing to users and manufacturers. Accordingly, companies can now offer offer new services, making them more competitive and customer oriented. At the same time, this paradigm attempts to combine opposing properties such as affordability and security. Consequently, IoT is still facing challenges regarding reliability and quality of service. This paper provides a survey of IoT technologies and their security as well as a summary of efforts made to increase failure tolerance of pervasive computational systems. Descripción : Master in Research in Engineering Systems Modeling Sun, 01 Jan 2017 00:00:00 GMT http://hdl.handle.net/11531/24527 2017-01-01T00:00:00Z http://hdl.handle.net/11531/24425 Título : Representation of storage operations in network-constrained optimization models for medium- and long-term operation Autor : Tejada-Arango, Diego A. Resumen : This paper proposes a model to carry out analysis of storage facilities operation including a transmission network. The model represents short-term storage operation in an approxi-mated way that reduces computational requirements, which makes it suitable for medium and long-term operational planning in power systems with a high level of renewable energy penetra-tion. In the proposed model, we cluster hourly data using the so-called system-states framework developed in previous work. Within this framework, non-consecutive similar time periods are grouped, while chronological information is represented by a tran-sition matrix among states. We extend the system-state framework from a single-bus system to a transmission network. We define and analyze two alternative sets of representative variables for clustering hours to obtain system states when the transmission network is considered. This extension of the system states framework allows us to evaluate the impact of transmission congestions in medium- and long-term planning models in a rea-sonable computation time. A case study shows that the proposed model is 235 times faster than an hourly approach, used as benchmark, whereas the overall system cost is approximated with less than 2% error. The overall charging/discharging trends are similar enough to those of the hourly model, being hydro storage better approximated than fast-ramping batteries. Besides, for the analyzed case study, it is shown how congestion in the transmission network in fact improves the accuracy of the proposed approach. Descripción : Master in Research in Engineering Systems Modeling Sun, 01 Jan 2017 00:00:00 GMT http://hdl.handle.net/11531/24425 2017-01-01T00:00:00Z http://hdl.handle.net/11531/24424 Título : Multi-area electricity market equilibrium model and its application to the European case : an efficient approach to study non-perfect competition Autor : Orgaz, Alberto Resumen : This paper presents an efficient approach for computing medium-term market equilibrium models under nonperfect competition, with a focus on multi-area systems, with multiple market splitting options. In accordance to the new policies and regulations aimed at creation of the Internal Electricity Market (IEM), Europe is evolving towards an integration of the electricity markets under a unified framework. Integrating the electricity markets already existing in the European countries represents a great challenge, since multiple agents’ strategic behaviors may appear depending on the state of the interconnections. When modeling this effect, the aim is to characterize each strategy by means of a conjectured price response, as a function of the states of the network. The methodology introduced in this paper reduces the possible network configurations thereby making the problem computationally tractable. Finally, this methodology has been applied to a two-year planning model for a set of nine European countries. Descripción : Master in Research in Engineering Systems Modeling Sun, 01 Jan 2017 00:00:00 GMT http://hdl.handle.net/11531/24424 2017-01-01T00:00:00Z http://hdl.handle.net/11531/24423 Título : Valuation of an american option for the spanish secondary reserve market using a machine learning model Autor : Malpica Morales, Antonio Resumen : This paper presents an original methodology to compute a financial product that could enhance the demand side participation in ancillary services, specially for industrial consumers. The financial product consists in an american option on the Spanish secondary reserve market for the following day, where the buyer has the right but not the obligation to offer part of its capacity to the system operator. Considering this approach, an industrial consumer would receive an economic incentive to offer its flexibility to the system without changing its production planning, paying an upfront premium. The computation of the american option is leveraged on a Monte Carlo simulation approach where the random paths are obtained from a machine learning model. The machine learning model attempts to forecast the 24-hour secondary band prices of the following day using a combination of different algorithms; the output of the model is used as a baseline to perform the Monte Carlo simulation that computes the option value. Descripción : Master in Research in Engineering Systems Modeling Sun, 01 Jan 2017 00:00:00 GMT http://hdl.handle.net/11531/24423 2017-01-01T00:00:00Z