Optimal PID power system stabilizer tuning based on particle swarm optimization

Abstract Power system stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the low frequency oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this conventional PSS (CPSS) has some problems. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this paper a PID type PSS is considered for damping electric power system oscillations. The parameters of this PID type PSS are tuned based on particle swarm optimization method. The proposed PSS (PSO-PSS) is evaluated against the conventional power system stabilizer (CPSS) at a single machine infinite bus power system considering system parametric uncertainties. The simulation results clearly indicate the effectiveness and validity of the proposed method

Power System Dynamic Stability Enhancement Using a New PID Type PSS 1

Abstract: Power System Stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the Low Frequency Oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this Conventional PSS (CPSS) has some problems. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this paper a PID type PSS (PID-PSS) is considered for damping electric power system oscillations. The parameters of this PID type PSS (PID-PSS) are tuned based on Hybrid Genetic Algorithm optimization method. The proposed PID-PSS is evaluated against the conventional power system stabilizer (CPSS) at a single machine infinite bus power system considering system parametric uncertainties. The simulation results clearly indicate the effectiveness and validity of the proposed method

How to quantify student's regularity?

Studies carried out in classroom-based learning context, have consistently shown a positive relation between students' conscientiousness and their academic success. We hypothesize that time management and regularity are main constructing blocks of students' conscientiousness in the context of online education. In online education, despite intuitive arguments supporting on-demand courses as more flexible delivery of knowledge, completion rate is higher in the courses with rigid temporal constraints and structure. In this study, we further investigate how students' regularity affects their learning outcome in MOOCs. We propose several measures to quantify students regularity. We validate accuracy of these measures as predictors of students' engagement and success in the course

Screen or Tabletop: An Eye-Tracking Study of the Effect of Representation Location in a Tangible User Interface System

This article presents a comparison of the effects of input-output location (co-located versus discrete) on user performance in a tangible user interface (TUI) system. We conducted a mobile eye-tracking study with two different versions of a TUI system and, despite similar performances in both conditions, our findings revealed differences in the users’ gaze patterns, shedding new light on the underlying cognitive processes

My Hands or my Mouse: Comparing a Tangible and Graphical User Interface using Eye-Tracking Data

Tangible User Interfaces (TUIs) have drawn the interest of HCI and learning communities because of their potential positive impact on the learning experience. In this paper, we describe a preliminary study of a TUI ap- plication for training spatial skills of carpenter apprentices. We designed a tangible interface to perform a CAD mod- elling activity in a way that resembles what apprentices do in the workspace: shaping a wooden brick through sequen- tial cuts by using a saw. The core of the study is to compare the effects of TUI and GUI on the user experience, by tak- ing advantage of eye-tracking data. We report two main findings: first, the successful employment of eye-gaze tool in TUI research which represents a novelty per-se. Second, a significant impact of the TUI on the user experience which gives some insights about the cognitive benefit of tangibles

Monitoring, Awareness and Reflection in Blended Technology Enhanced Learning: a Systematic Review

Education is experiencing a paradigm shift towards blended learning models in technology-enhanced learning (TEL). Despite the potential benefits of blended learning, it also entails additional complexity in terms of monitoring, awareness and reflection, as learning happens across different spaces and modalities. In recent years, literature on Learning Analytics (LA) and Educational Data Mining (EDM) has gained momentum and started to address the issue. To provide a clear picture of the current state of the research on the topic and to outline open research gaps, this paper presents a systematic literature review of the state-of-the-art of research in LA and EDM on monitoring, awareness and reflection in blended TEL scenarios. The search included six main academic databases in TEL that were enriched with the proceedings of the workshop on ’Awareness and Reflection in TEL’ (ARTEL), resulting in 1089 papers out of which 40 papers were included in the final analysis

Understanding learning at a glance: An overview of learning dashboard studies

Research on learning dashboards aims to identify what data is meaningful to different stakeholders in education, and how data can be presented to support sense-making processes. This paper summarizes the main outcomes of a systematic literature review on learning dashboards, in the fields of Learning Analytics and Educational Data Mining. The query was run in five main academic databases and enriched with papers coming from GScholar, resulting in 346 papers out of which 55 were included in the final analysis. Our review distinguishes different kinds of research studies as well as different aspects of learning dashboards and their maturity in terms of evaluation. As the research field is still relatively young, many of the studies are exploratory and proof-of-concept. Among the main open issues and future lines of work in the area of learning dashboards, we identify the need for longitudinal research in authentic settings, as well as studies that systematically compare different dashboard design options

Ein Beitrag zum Entladungsverhalten langer Luftfunkenstrecken bei Blitzspannung

Für die Menschen zählen Gewitter mit Donner und Blitz zu den ältesten bekannten Phänomenen der Natur. Die Tatsache, dass Blitze dennoch bis heute nicht abschließend erforscht sind, liegt in dem äußerst komplexen, schnellen und stochastischen Verhalten der Blitzentladung begründet. Der Autor befasste sich in Rahmen dieser Arbeit u.a. mit der Entwicklung eines modernen Messsystems, durch das die Erfassung von sowohl elektrischen als auch optischen Parametern der im Nanosekundenbereich ablaufenden Prozesse der Entladungen möglich wurde. Es handelt sich um technisch anspruchsvolle Messungen von hohen Stoßspannungen und schwachen Vorentladungsströmen in einem großen Frequenzbereich. Außerdem gelang es durch eine geschickte Synchronisation, die Entladungsprozesse präzise und erstmalig in einer Fotosequenz aufzunehmen. Auf Grundlage der Messergebnisse konnte der Entladungsprozess in mehrere Phasen der Vorentladung unterteilt und beschrieben werden. Vor allem beweisen die Messergebnisse die Existenz einer kanalartigen Vorentladung, die nicht zwingend zu einem Durchschlag führt. Dieser Mechanismus, der bei langsam ansteigenden Spannungen als stabile Leaderentladung benannt und mit Thermoionisation gekennzeichnet ist, war bei Blitzstoßspannungen bisher umstritten.The breakdown behavior of long air gaps by Lightning Voltages has been investigated and the results of a new measurement system are reported. A series of up to eight photos (made by a high-speed camera) have recorded the expansion of discharge activities during the breakdown process. The pre-discharge current and voltage have been measured as well. The modern measurement techniques have made possible the synchronization of the photos with the current and voltage measurements in nanosecond-ranges. The combination of the measured current, voltage, and photos can precisely explain the breakdown process. The experiments have been carried out with the lightning impulses up to 2.4 MV and the air gaps up to 4 m. Despite of such high voltages, the experimental system has been verified to be appropriate for measuring the pre-discharge current in mA-ranges

Discovering Interaction Patterns in Online Learning Environments:A Learning Analytics Research

The increasing amount of data collected in online learning environments provides unique opportunities to better understand the learning processes in different educational settings. Learning analytics research aims at understanding and optimizing learning and the environments in which it occurs. A crucial step towards this goal is to adapt and develop adequate computational methods to process and analyze the learning-related data and to present information in intelligible ways to educational stakeholders. In this thesis we investigate interaction patterns of learners in two different online learning environments: Massive Open Online Courses (MOOCs) and Realto, an online platform for integrated Vocational Education and Training (VET). We analyze interaction patterns across three principal dimensions: time, activity, and social. To obtain a better understanding of the complex learning behaviours, it is essential to consider these different aspects of the educational data. We develop novel methods and use existing techniques from sequential pattern mining, content analysis, and social network analysis to model and track interaction patterns of learners across the three mentioned dimensions. As regards the time dimension, we present methods to model temporal patterns of learners' participation. We introduce novel techniques to discover and quantify online regularity in terms of following a certain daily or weekly time schedule. We investigate the relation between students' regularity level and their performance in a MOOC course. Concerning the activity dimension, we analyze learners' activity sequences in order to identify and track the evolution of their study approaches over time. By clustering study pattern sequences in a MOOC course, we extract different engagement profiles among learners and describe their properties. Furthermore, we propose a complete processing pipeline for the unsupervised discovery of study patterns from sequential interaction logs. This pipeline is applicable at different levels of actions granularity and time resolution and enables to perform temporal analysis of learners' interaction patterns throughout the course duration. For the social dimension, we explore the attributes of social interactions among learners. In the MOOC context, we combine content and social network analyses to study dynamics of forum discussions and the evolution of students' roles over time. In the context of Realto, we employ social network analysis to model the social interactions among learners and to study the structure of Realto-mediated communication among different stakeholders in the VET system. Using the presented analytic methods, we provide novel insights into the interaction patterns of learners in MOOCs and Realto. Moreover, we present an implementation of these methods into an analytics dashboard for Realto researchers

Multi Area Load Frequency Control using Simulated Annealing

Abstract: In multi area electric power systems if a large load is suddenly connected (or disconnected) to the system, or if a generating unit is suddenly disconnected by the protection equipment, there will be a long-term distortion in the power balance between that delivered by the turbines and that consumed by the loads. This imbalance is initially covered from the kinetic energy of rotating rotors of turbines, generators and motors and, as a result, the frequency in the system will change. Therefore The Load Frequency Control (LFC) problem is one of the most important subjects in the electric power system operation and control. In practical systems, the conventional PI type controllers are applied for LFC. In order to overcome the drawbacks of the conventional PI controllers, numerous techniques have been proposed in literatures. In this paper a PI type controller is considered for LFC problem. The parameters of the proposed PI controller are tuned using Simulated Annealing (SA) optimization method. A multi area electric power system with a wide range of parametric uncertainties is given to illustrate proposed method. To show effectiveness of the proposed method, a PI type controller optimized by Genetic Algorithms (GA) is designed in order to comparison with the proposed PI controller. The simulation results visibly show the validity of SA-PI controller in comparison with the GA-PI controller