Polytechnic University of Catalonia

About: Polytechnic University of Catalonia is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Finite element method & Population. The organization has 16006 authors who have published 45325 publications receiving 949306 citations. The organization is also known as: UPC - BarcelonaTECH & Technical University of Catalonia.

Mixed-Integer-Linear-Programming-Based Energy Management System for Hybrid PV-Wind-Battery Microgrids: Modeling, Design, and Experimental Verification

Abstract: Microgrids are energy systems that aggregate distributed energy resources, loads, and power electronics devices in a stable and balanced way. They rely on energy management systems to schedule optimally the distributed energy resources. Conventionally, many scheduling problems have been solved by using complex algorithms that, even so, do not consider the operation of the distributed energy resources. This paper presents the modeling and design of a modular energy management system and its integration to a grid-connected battery-based microgrid. The scheduling model is a power generation-side strategy, defined as a general mixed-integer linear programming by taking into account two stages for proper charging of the storage units. This model is considered as a deterministic problem that aims to minimize operating costs and promote self-consumption based on 24-hour ahead forecast data. The operation of the microgrid is complemented with a supervisory control stage that compensates any mismatch between the offline scheduling process and the real time microgrid operation. The proposal has been tested experimentally in a hybrid microgrid at the Microgrid Research Laboratory, Aalborg University.

Analysis and Control of DC-Capacitor-Voltage-Drift Phenomenon of a Passive Front-End Five-Level Converter

Abstract: The phenomenon of dc-capacitor-voltage drift is the main technical drawback of a passive front-end multilevel diode-clamped converter (DCC). This paper formulates and analyzes the dc-capacitor-voltage-drift phenomenon of a passive front-end five-level DCC, which operates based on a sinusoidal pulsewidth-modulation (SPWM) switching strategy. The analysis shows dependence of the voltage drift on the modulation index and the ac-side power factor of the DCC. The analysis concludes that an SPWM strategy, without the use of auxiliary power circuitry, is not able to prevent the voltage-drift phenomenon of a five-level DCC. This paper also proposes a space-vector-modulation (SVM)-based switching strategy that takes advantage of redundant switching vectors of the SVM method to counteract the voltage-drift phenomenon. The limit to the range of operation of a five-level DCC, which is based on the proposed SVM strategy, is also presented. The salient feature of the proposed strategy is that it enables voltage balancing of the dc capacitors with no requirements for additional controls or auxiliary-power circuitry, within the specified range of operation. The performance of a DCC under various operating conditions, based on time-domain simulation studies in the MATLAB/SIMULINK environment, is evaluated. This paper demonstrates capability of the proposed SVM strategy to control and maintain voltage balance of dc capacitors.

Adaptive information extraction

Abstract: The growing availability of online textual sources and the potential number of applications of knowledge acquisition from textual data has lead to an increase in Information Extraction (IE) research. Some examples of these applications are the generation of data bases from documents, as well as the acquisition of knowledge useful for emerging technologies like question answering, information integration, and others related to text mining. However, one of the main drawbacks of the application of IE refers to its intrinsic domain dependence. For the sake of reducing the high cost of manually adapting IE applications to new domains, experiments with different Machine Learning (ML) techniques have been carried out by the research community. This survey describes and compares the main approaches to IE and the different ML techniques used to achieve Adaptive IE technology.