Uncertainty Analysis of the Adequacy Assessment Model of a Distributed Generation System

Due to the inherent aleatory uncertainties in renewable generators, the reliability/adequacy assessments of distributed generation (DG) systems have been particularly focused on the probabilistic modeling of random behaviors, given sufficient informative data. However, another type of uncertainty (epistemic uncertainty) must be accounted for in the modeling, due to incomplete knowledge of the phenomena and imprecise evaluation of the related characteristic parameters. In circumstances of few informative data, this type of uncertainty calls for alternative methods of representation, propagation, analysis and interpretation. In this study, we make a first attempt to identify, model, and jointly propagate aleatory and epistemic uncertainties in the context of DG systems modeling for adequacy assessment. Probability and possibility distributions are used to model the aleatory and epistemic uncertainties, respectively. Evidence theory is used to incorporate the two uncertainties under a single framework. Based on the plausibility and belief functions of evidence theory, the hybrid propagation approach is introduced. A demonstration is given on a DG system adapted from the IEEE 34 nodes distribution test feeder. Compared to the pure probabilistic approach, it is shown that the hybrid propagation is capable of explicitly expressing the imprecision in the knowledge on the DG parameters into the final adequacy values assessed. It also effectively captures the growth of uncertainties with higher DG penetration levels

Impact of Embedded Carbon Fiber Heating Panel on the Structural/Mechanical Performance of Roadway Pavement

INE/AUTC 12.3

Assessing the overall perceived quality of the undergraduate students

Purpose - The paper is twofold aimed: (i) defining and validating a scale to assess the quality of the university experienced by students and (ii) analyzing the role of the aforementioned di- mensions and their impact on students’ satisfaction. Methodology/Approach - A survey of 2,557 undergraduate students that finished their degrees in 2013 at universities located in the region of Catalonia has been analyzed using Structural Equation Modeling (SEM). An exploratory analysis suggests the final dimensions that were confirmed in a confirmatory analysis. The psychometric characteristics of the scale are provided to show reliability and validity of the constructs. An extra model (also using SEM) assesses the impact of these dimensions on overall satisfac- tion. Findings - The quality is a multifactor construct composed by: (i) “syllabus”, which refers to the quality of the learning methods and the coordination efforts through the whole study period; (ii) “skills development”, referring to the skills that students might acquire along their studies and (iii) “services and facilities” of the university. Moreover, the first and third factors act as “enablers” for the second factor one. Nevertheless, only “Syllabus” dimension affects significantly on students’ satisfaction, whereas “services and facilities” do not have a significant role, although they are necessary in order to provide a good service. Research Limitation/implication - Although the sample is large enough to draw robust re- sults, it is limited the Catalonia. The paper provides recommendations for university managers and public administration authorities in order to allocate the available resources. Originality/Value of paper - In an era of global competition, universities are trying to adapt to these new requirements by expanding they academic offer, introducing innovative teaching methods, providing teaching resources to lecturers, and updating the general services of the university among others. All these services will be considered when students evaluate their experience at the university. The paper contributes with an assessment scale for the holistic service provided by the university within the period that the student is in the university. These findings can be applied to help define attractive academic programs and provide useful insights on how the supporting facilities should be designed to allow students take advantage of their learning process at universities.Postprint (published version

Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: a review

YesDistributed generators (DGs) are a reliable solution to supply economic and reliable electricity to customers. It is the last stage in delivery of electric power which can be defined as an electric power source connected directly to the distribution network or on the customer site. It is necessary to allocate DGs optimally (size, placement and the type) to obtain commercial, technical, environmental and regulatory advantages of power systems. In this context, a comprehensive literature review of uncertainty modeling methods used for modeling uncertain parameters related to renewable DGs as well as methodologies used for the planning and operation of DGs integration into distribution network.This work was supported in part by the SITARA project funded by the British Council and the Department for Business, Innovation and Skills, UK and in part by the University of Bradford, UK under the CCIP grant 66052/000000

The attractiveness of countries for FDI. A fuzzy approach

This paper presents a new method for measuring the attractiveness of countries for FDI. A ranking is built using a fuzzy expert system whereby the function producing the final evaluation is not necessarily linear and the weights of the variables, usually defined numerically, are replaced by linguistic rules. More precisely, weights derive from expert opinions and from econometric tests on the determinants of countries’ FDI. As a second step, the view-point of investors from two different investing economies, the UK and Italy, are taken into account. Country-specific factors, such as the geographic, cultural and institutional distances existing between the investing and the partner economies are included in the analysis. This shows how the base ranking changes with the investor’s perspective.foreign direct investments; fuzzy expert systems; attractiveness

The Attractiveness of Countries for FDI. A Fuzzy Approach

This paper presents a new method for measuring the attractiveness of countries for FDI. A ranking is built using a fuzzy expert system whereby the function producing the final evaluation is not necessarily linear and the weights of the variables, usually defined numerically, are replaced by linguistic rules. More precisely, weights derive from expert opinions and from econometric tests on the determinants of countries’ FDI. As a second step, the view-point of investors from two different investing economies, the UK and Italy, are taken into account. Country-specific factors, such as the geographic, cultural and institutional distances existing between the investing and the partner economies are included in the analysis. This shows how the base ranking changes with the investor’s perspectiveforeign direct investments; fuzzy expert systems; attractiveness;

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

Make-or-buy configurational approaches in product-service ecosystems and performance

This research examines firm boundary configurations for manufacturers' product-service offerings. We argue that the building of a product-service ecosystem through collaboration with service providers in certain types of business services can increase performance as a result of the superior knowledge-based resources coming from specialized partners. By using fuzzy set qualitative analysis on a sample of 370 multinational manufacturing enterprises (MMNEs), the results reveal that effective servitization is heterogeneous across manufacturing industries and across business service offerings. The findings indicate that most industries achieve their highest performance through collaborations with value-added service providers in two out of three of the service continuum stages (Base and Intermediate services); while keeping the development of Advanced services in-house. The results help to contextualize the best practices for implementing service business models in MMNEs by detailing which service capabilities should be retained in-house and which should be outsourced to specialized partners in various industrial contexts.Peer ReviewedPreprin