Power quality disturbances assessment during unintentional islanding scenarios. A contribution to voltage sag studies

This paper presents a novel voltage sag topology that occurs during an unintentional islanding operation (IO) within a distribution network (DN) due to large induction motors (IMs). When a fault occurs, following the circuit breaker (CB) fault clearing, transiently, the IMs act as generators due to their remanent kinetic energy until the CB reclosing takes place. This paper primarily contributes to voltage sag characterization. Therefore, this novel topology is presented, analytically modelled and further validated. It is worth mentioning that this voltage sag has been identified in a real DN in which events have been recorded for two years. The model validation of the proposed voltage sag is done via digital simulations with a model of the real DN implemented in Matlab considering a wide range of scenarios. Both simulations and field measurements confirm the voltage sag analytical expression presented in this paper as well as exhibiting the high accuracy achieved in the three-phase model adopted.Postprint (published version

Evolution and Modern Approaches for Thermal Analysis of Electrical Machines

In this paper, the authors present an extended survey on the evolution and the modern approaches in the thermal analysis of electrical machines. The improvements and the new techniques proposed in the last decade are analyzed in depth and compared in order to highlight the qualities and defects of each. In particular, thermal analysis based on lumped-parameter thermal network, finite-element analysis, and computational fluid dynamics are considered in this paper. In addition, an overview of the problems linked to the thermal parameter determination and computation is proposed and discussed. Taking into account the aims of this paper, a detailed list of books and papers is reported in the references to help researchers interested in these topics

Determination of stress concentration factors in offshore wind welded structures through a hybrid experimental and numerical approach

Offshore wind turbine (OWT) monopile support structures generally consist of steel cans connected together through circumferential welding joints. One critical factor to evaluate the localised increase in stresses is the stress concentration factor (SCF) which depends on the welding quality. The complex welding profiles in OWT monopiles makes the accurate calculation of SCF quite challenging. In this work, an innovative approach for the calculation of SCFs in offshore welded structures is proposed based on combined 3D (three-dimensional) laser scanning technology (LST) and 3D finite element analysis (FEA). The precise geometry of the welded specimens is captured using 3D LST, and then imported into a finite element software to perform 3D FEA modelling to accurately calculate SCFs. A 2D (two-dimensional) FEA model of a typical offshore welded structure with ideal geometry is also developed in this work. In addition to numerically calculate SCFs, the 2D FEA model is further combined with non-linear RSM (response surface method) to derive analytical equations, expressing SCFs of offshore welded structures in terms of key welding parameters. Both LST-FEA3D and RSM-FEA2D models are applied to calculate SCFs in large-scale S-N fatigue welded specimens. The results indicate that the LST-FEA3D approach is capable of capturing the variation of SCFs along the width of the welded specimens and identifying the critical points where fatigue crack is most likely to initiate; and the RSM-FEA2D is valuable and efficient in deriving analytical parametric equations for SCFs

Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

Alternative Approaches to the Empirical Validation of Agent-Based Models

This paper draws on the metaphor of a spectrum of models ranging from the most theory-driven to the most evidence-driven. The issue of concern is the practice and criteria that will be appro- priate to validation of different models. In order to address this concern, two modelling approaches are investigated in some detailed – one from each end of our metaphorical spectrum. Windrum et al. (2007) (http://jasss.soc.surrey.ac.uk/10/2/8.html) claimed strong similarities between agent based social simulation and conventional social science – specifically econometric – approaches to empirical modelling and on that basis considered how econometric validation techniques might be used in empirical social simulations more broadly. An alternative is the approach of the French school of \'companion modelling\' associated with Bousquet, Barreteau, Le Page and others which engages stakeholders in the modelling and validation process. The conventional approach is con- strained by prior theory and the French school approach by evidence. In this sense they are at opposite ends of the theory-evidence spectrum. The problems for validation identified by Windrum et al. are shown to be irrelevant to companion modelling which readily incorporate complexity due to realistically descriptive specifications of individual behaviour and social interaction. The result combines the precision of formal approaches with the richness of narrative scenarios. Companion modelling is therefore found to be practicable and to achieve what is claimed for it and this alone is a key difference from conventional social science including agent based computational economics.Social Simulation, Validation, Companion Modelling, Data Generating Mechanisms, Complexity

Exploiting Qualitative Information for Decision Support in Scenario Analysis

The development of scenario analysis (SA) to assist decision makers and stakeholders has been growing over the last few years through mainly exploiting qualitative information provided by experts. In this study, we present SA based on the use of qualitative data for strategy planning. We discuss the potential of SA as a decision-support tool, and provide a structured approach for the interpretation of SA data, and an empirical validation of expert evaluations that can help to measure the consistency of the analysis. An application to a specific case study is provided, with reference to the European organic farming business

Semantic-driven Configuration of Internet of Things Middleware

We are currently observing emerging solutions to enable the Internet of Things (IoT). Efficient and feature rich IoT middeware platforms are key enablers for IoT. However, due to complexity, most of these middleware platforms are designed to be used by IT experts. In this paper, we propose a semantics-driven model that allows non-IT experts (e.g. plant scientist, city planner) to configure IoT middleware components easier and faster. Such tools allow them to retrieve the data they want without knowing the underlying technical details of the sensors and the data processing components. We propose a Context Aware Sensor Configuration Model (CASCoM) to address the challenge of automated context-aware configuration of filtering, fusion, and reasoning mechanisms in IoT middleware according to the problems at hand. We incorporate semantic technologies in solving the above challenges. We demonstrate the feasibility and the scalability of our approach through a prototype implementation based on an IoT middleware called Global Sensor Networks (GSN), though our model can be generalized into any other middleware platform. We evaluate CASCoM in agriculture domain and measure both performance in terms of usability and computational complexity.Comment: 9th International Conference on Semantics, Knowledge & Grids (SKG), Beijing, China, October, 201

Performance requirements verification during software systems development

Requirements verification refers to the assurance that the implemented system reflects the specified requirements. Requirement verification is a process that continues through the life cycle of the software system. When the software crisis hit in 1960, a great deal of attention was placed on the verification of functional requirements, which were considered to be of crucial importance. Over the last decade, researchers have addressed the importance of integrating non-functional requirement in the verification process. An important non-functional requirement for software is performance. Performance requirement verification is known as Software Performance Evaluation. This thesis will look at performance evaluation of software systems. The performance evaluation of software systems is a hugely valuable task, especially in the early stages of a software project development. Many methods for integrating performance analysis into the software development process have been proposed. These methodologies work by utilising the software architectural models known in the software engineering field by transforming these into performance models, which can be analysed to gain the expected performance characteristics of the projected system. This thesis aims to bridge the knowledge gap between performance and software engineering domains by introducing semi-automated transformation methodologies. These are designed to be generic in order for them to be integrated into any software engineering development process. The goal of these methodologies is to provide performance related design guidance during the system development. This thesis introduces two model transformation methodologies. These are the improved state marking methodology and the UML-EQN methodology. It will also introduce the UML-JMT tool which was built to realise the UML-EQN methodology. With the help of automatic design models to performance model algorithms introduced in the UML-EQN methodology, a software engineer with basic knowledge of performance modelling paradigm can conduct a performance study on a software system design. This was proved in a qualitative study where the methodology and the tool deploying this methodology were tested by software engineers with varying levels of background, experience and from different sectors of the software development industry. The study results showed an acceptance for this methodology and the UML-JMT tool. As performance verification is a part of any software engineering methodology, we have to define frame works that would deploy performance requirements validation in the context of software engineering. Agile development paradigm was the result of changes in the overall environment of the IT and business worlds. These techniques are based on iterative development, where requirements, designs and developed programmes evolve continually. At present, the majority of literature discussing the role of requirements engineering in agile development processes seems to indicate that non-functional requirements verification is an unchartered territory. CPASA (Continuous Performance Assessment of Software Architecture) was designed to work in software projects where the performance can be affected by changes in the requirements and matches the main practices of agile modelling and development. The UML-JMT tool was designed to deploy the CPASA Performance evaluation tests

Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded. The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded

Development of a stochastic computational fluid dynamics approach for offshore wind farms

In this paper, a method for stochastic analysis of an offshore wind farm using computational fluid dynamics (CFD) is proposed. An existing offshore wind farm is modelled using a steady-state CFD solver at several deterministic input ranges and an approximation model is trained on the CFD results. The approximation model is then used in a Monte-Carlo analysis to build joint probability distributions for values of interest within the wind farm. The results are compared with real measurements obtained from the existing wind farm to quantify the accuracy of the predictions. It is shown that this method works well for the relatively simple problem considered in this study and has potential to be used in more complex situations where an existing analytical method is either insufficient or unable to make a good prediction