Modelling and analysis of type 4 wind turbine generator system for utilization in frequency regulation studies

Green energy targets for coming decades advocates high penetration of wind energy in main energy matrix which also pose incendiary threat to stability and reliability of modern electric grid if their dynamic performance aspects are not assessed beforehand. Considering increasing interest in dynamic performance along with ancillary service assessment related to frequency regulation, development of suitable generic modeling has gained high priority. This paper presents modeling of type 4 full converter wind turbine generator system suitable for frequency regulation focusing on active power control. Complete model is a modification of WECC generic model with additional aerodynamic and pitch control model. Descriptions of individual sub models are presented and performance results are compared manufacturer specific GE type 4 WTG generic model by means of simulations in the MATLAB ® Power System Block set.

Modeling, parameter measurement and sensorless speed estimation of IPM synchronous generator for direct drive variable speed wind turbine application

This paper presents simple methods of determining parameters of interior permanent magnet (IPM) synchronous generator such as magnet flux (λM), d-axis inductance (Ld) and q-axis inductance (Lq) of IPM synchronous generator, which are used to control the wind turbine generator. These methods are simple and do not require any complex theory, signal injection or special equipment. Moreover, a sensorless speed estimator is proposed to estimate the speed of the generator without using speed sensor. The measured parameters are used in this speed estimator. The elimination of speed sensor will enhance the system robustness and reduce the design complexity and system cost for a small-scale wind turbine considered in this paper. The effectiveness of parameter measurement methods and sensorless speed estimator is demonstrated by experimental results. Experimental results show that the proposed speed estimator that uses the measured parameters can estimate the generator speed with a small error.

Full converter based wind turbine generator system generic modelling: Variations and applicability

Wind energy system integration can lead to adverse effects on modern electric grid so it is imperative toassess their dynamic performance before actual plant startup. Transmission system operators all over theworld stress the need for a proper wind turbine generator model for dynamic performance as well asancillary service assessments. Due to the bulk power system assessment requirements, developmentof suitable generic modeling has gained high priority. Generic modeling of type 4 full converter wind turbinegenerator system for application in frequency ancillary service investigations under varying windspeed and varying reference power has been presented in this study. Prevalent generic model, manufacturerspecific proprietary generic model along with detailed wind turbine model with synchronous generatoris also provided to highlight various modelling framework difference. Descriptions of individualsub models of proposed generic model are presented in detail and performance results are comparedand validated with GE’s proprietary generic model and detailed WTG model by means of simulationsin the MATLAB Power System Block set.

Identifying key success factors for the adoption and implementation of a chemotherapy ordering system: a case study from the Australian private healthcare sector

This paper is designed to systematically assess the benefits of a chemotherapy ordering system (COS) for the private healthcare sector in Australia. By taking a rational economic perspective and modeling the principle-agent relationships using an actor network framework, it is possible to evaluate various scenarios and thereby assess the benefits, barriers and facilitators, possible COS can have. In this study, four hypotheses are tested using a mixed methodology which will serve to facilitate the decision making processes regarding the choice and implementation of the appropriate COS for Epworth.

Modeling relevant legal information for consumer disputes

Accessing relevant legal information found in text excerpts from heterogeneous sources is essential to the decision making process in consumer disputes. The Ontology of Relevant Legal Information in Consumer Disputes (ric) is the domain-independent ontology modeling this relevant legal information comprising rights, their requisites, exceptions, constraints, enforcement procedures, legal sources. Its use is exemplified with one extension thereof, the Air Transport Passenger Incidents Ontology (ric-atpi), representing both the possible incidents triggered by a complaint in the air transport passenger domain and the related legal information that might be applicable. The Ontology models the key provisions found in the hard law, and those in soft law, comprising heterogeneous sources in a structured manner. An ontology-based system provides the knowledge embedded in the legal sources and their relation to the specific scenario.

DIFFUSE-INTERFACE FIELD APPROACH TO MODELING SELF-ASSEMBLY OF HETEROGENEOUS COLLOIDAL SYSTEMS AND RELATED DIPOLE-DIPOLE INTERACTION PHENOMENA

Colloid self-assembly under external control is a new route to fabrication of advanced materials with novel microstructures and appealing functionalities. The kinetic processes of colloidal self-assembly have attracted great interests also because they are similar to many atomic level kinetic processes of materials. In the past decades, rapid technological progresses have been achieved on producing shape-anisotropic, patchy, core-shell structured particles and particles with electric/magnetic charges/dipoles, which greatly enriched the self-assembled structures. Multi-phase carrier liquids offer new route to controlling colloidal self-assembly. Therefore, heterogeneity is the essential characteristics of colloid system, while so far there still lacks a model that is able to efficiently incorporate these possible heterogeneities. This thesis is mainly devoted to development of a model and computational study on the complex colloid system through a diffuse-interface field approach (DIFA), recently developed by Wang et al. This meso-scale model is able to describe arbitrary particle shape and arbitrary charge/dipole distribution on the surface or body of particles. Within the framework of DIFA, a Gibbs-Duhem-type formula is introduced to treat Laplace pressure in multi-liquid-phase colloidal system and it obeys Young-Laplace equation. The model is thus capable to quantitatively study important capillarity related phenomena. Extensive computer simulations are performed to study the fundamental behavior of heterogeneous colloidal system. The role of Laplace pressure is revealed in determining the mechanical equilibrium of shape-anisotropic particles at fluid interfaces. In particular, it is found that the Laplace pressure plays a critical role in maintaining the stability of capillary bridges between close particles, which sheds light on a novel route to in situ firming compact but fragile colloidal microstructures via capillary bridges. Simulation results also show that competition between like-charge repulsion, dipole-dipole interaction and Brownian motion dictates the degree of aggregation of heterogeneously charged particles. Assembly and alignment of particles with magnetic dipoles under external field is studied. Finally, extended studies on the role of dipole-dipole interaction are performed for ferromagnetic and ferroelectric domain phenomena. The results reveal that the internal field generated by dipoles competes with external field to determine the dipole-domain evolution in ferroic materials.

Advanced Methodologies in Dynamic Traffic Assignment Modeling of Managed Lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.

GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.

Methods for Modeling and Analyzing Concurrent Software

Concurrent software executes multiple threads or processes to achieve high performance. However, concurrency results in a huge number of different system behaviors that are difficult to test and verify. The aim of this dissertation is to develop new methods and tools for modeling and analyzing concurrent software systems at design and code levels. This dissertation consists of several related results. First, a formal model of Mondex, an electronic purse system, is built using Petri nets from user requirements, which is formally verified using model checking. Second, Petri nets models are automatically mined from the event traces generated from scientific workflows. Third, partial order models are automatically extracted from some instrumented concurrent program execution, and potential atomicity violation bugs are automatically verified based on the partial order models using model checking. Our formal specification and verification of Mondex have contributed to the world wide effort in developing a verified software repository. Our method to mine Petri net models automatically from provenance offers a new approach to build scientific workflows. Our dynamic prediction tool, named McPatom, can predict several known bugs in real world systems including one that evades several other existing tools. McPatom is efficient and scalable as it takes advantage of the nature of atomicity violations and considers only a pair of threads and accesses to a single shared variable at one time. However, predictive tools need to consider the tradeoffs between precision and coverage. Based on McPatom, this dissertation presents two methods for improving the coverage and precision of atomicity violation predictions: 1) a post-prediction analysis method to increase coverage while ensuring precision; 2) a follow-up replaying method to further increase coverage. Both methods are implemented in a completely automatic tool.

A NOVEL MODELING AND STATE OF CHARGE ESTIMATION SCHEME FOR LITHIUM-ION BATTERIES

Lithium Ion (Li-Ion) batteries have got attention in recent decades because of their undisputable advantages over other types of batteries. They are used in so many our devices which we need in our daily life such as cell phones, lap top computers, cameras, and so many electronic devices. They also are being used in smart grids technology, stand-alone wind and solar systems, Hybrid Electric Vehicles (HEV), and Plug in Hybrid Electric Vehicles (PHEV). Despite the rapid increase in the use of Lit-ion batteries, the existence of limited battery models also inadequate and very complex models developed by chemists is the lack of useful models a significant matter. A battery management system (BMS) aims to optimize the use of the battery, making the whole system more reliable, durable and cost effective. Perhaps the most important function of the BMS is to provide an estimate of the State of Charge (SOC). SOC is the ratio of available ampere-hour (Ah) in the battery to the total Ah of a fully charged battery. The Open Circuit Voltage (OCV) of a fully relaxed battery has an approximate one-to-one relationship with the SOC. Therefore, if this voltage is known, the SOC can be found. However, the relaxed OCV can only be measured when the battery is relaxed and the internal battery chemistry has reached equilibrium. This thesis focuses on Li-ion battery cell modelling and SOC estimation. In particular, the thesis, introduces a simple but comprehensive model for the battery and a novel on-line, accurate and fast SOC estimation algorithm for the primary purpose of use in electric and hybrid-electric vehicles, and microgrid systems. The thesis aims to (i) form a baseline characterization for dynamic modeling; (ii) provide a tool for use in state-of-charge estimation. The proposed modelling and SOC estimation schemes are validated through comprehensive simulation and experimental results.

Modeling chemistry in massive star forming regions with internal PDRs

Over the past decades star formation has been a very attractive field because knowledge of star formation leads to a better understanding of the formation of planets and thus of our solar system but also of the evolution of galaxies. Conditions leading to the formation of high-mass stars are still under investigation but an evolutionary scenario has been proposed: As a cold pre-stellar core collapses under gravitational force, the medium warms up until it reaches a temperature of 100 K and enters the hot molecular core (HMC) phase. The forming central proto-star accretes materials, increasing its mass and luminosity and eventually it becomes sufficiently evolved to emit UV photons which irradiate the surrounding environment forming a hyper compact (HC) and then a ultracompact (UC) HII region. At this stage, a very dense and very thin internal photon-dominated region (PDR) forms between the HII region and the molecular core. Information on the chemistry allows to trace the physical processes occurring in these different phases of star formation. Formation and destruction routes of molecules are influenced by the environment as reaction rates depend on the temperature and radiation field. Therefore, chemistry also allows the determination of the evolutionary stage of astrophysical objects through the use of chemical models including the time evolution of the temperature and radiation field. Because HMCs host a very rich chemistry with high abundances of complex organic molecules (COMs), several astrochemical models have been developed to study the gas phase chemistry as well as grain chemistry in these regions. In addition to HMCs models, models of PDRs have also been developed to study in particular photo-chemistry. So far, few studies have investigated internal PDRs and only in the presence of outflows cavities. Thus, these unique regions around HC/UCHII regions remain to be examined thoroughly. My PhD thesis focuses on the spatio-temporal chemical evolution in HC/UC HII regions with internal PDRs as well as in HMCs. The purpose of this study is first to understand the impact and effects of the radiation field, usually very strong in these regions, on the chemistry. Secondly, the goal is to study the emission of various tracers of HC/UCHII regions and compare it with HMCs models, where the UV radiation field does not impact the region as it is immediately attenuated by the medium. Ultimately we want to determine the age of a given region using chemistry in combination with radiative transfer.

Control-oriented modeling of a polymeric soft robot

This article describes an efficient control-oriented model of a soft robot made of electroactive polymers. The proposed soft robot is constructed from two flexible links and has a multiphysics dynamic model consisting of both an electrochemical and electromechanical model. The electrochemical model is based on a distributed RC line approach, and the electromechanical model, considering the continuum vibration of the robot, is derived based on Hamilton's principle. The governing equation of the soft robot is solved by means of the Rayleigh-Ritz-Meirovitch substructure synthesis method, and the Laplace operator is used to obtain the transfer function of the soft robot as a 2 by 2 multiple-input multiple-output system.

Experimental and modeling studies of forced convection storage and drying systems for sweet potatoes

Sweet potato is an important strategic agricultural crop grown in many countries around the world. The roots and aerial vine components of the crop are used for both human consumption and, to some extent as a cheap source of animal feed. In spite of its economic value and growing contribution to health and nutrition, harvested sweet potato roots and aerial vine components has limited shelf-life and is easily susceptible to post-harvest losses. Although post-harvest losses of both sweet potato roots and aerial vine components is significant, there is no information available that will support the design and development of appropriate storage and preservation systems. In this context, the present study was initiated to improve scientific knowledge about sweet potato post-harvest handling. Additionally, the study also seeks to develop a PV ventilated mud storehouse for storage of sweet potato roots under tropical conditions. In study one, airflow resistance of sweet potato aerial vine components was investigated. The influence of different operating parameters such as airflow rate, moisture content and bulk depth at different levels on airflow resistance was analyzed. All the operating parameters were observed to have significant (P < 0.01) effect on airflow resistance. Prediction models were developed and were found to adequately describe the experimental pressure drop data. In study two, the resistance of airflow through unwashed and clean sweet potato roots was investigated. The effect of sweet potato roots shape factor, surface roughness, orientation to airflow, and presence of soil fraction on airflow resistance was also assessed. The pressure drop through unwashed and clean sweet potato roots was observed to increase with higher airflow, bed depth, root grade composition, and presence of soil fraction. The physical properties of the roots were incorporated into a modified Ergun model and compared with a modified Shedd’s model. The modified Ergun model provided the best fit to the experimental data when compared with the modified Shedd’s model. In study three, the effect of sweet potato root size (medium and large), different air velocity and temperature on the cooling/or heating rate and time of individual sweet potato roots were investigated. Also, a simulation model which is based on the fundamental solution of the transient equations was proposed for estimating the cooling and heating time at the centre of sweet potato roots. The results showed that increasing air velocity during cooling and heating significantly (P < 0.05) affects the cooling and heating times. Furthermore, the cooling and heating times were significantly different (P < 0.05) among medium and large size sweet potato roots. Comparison of the simulation results with experimental data confirmed that the transient simulation model can be used to accurately estimate the cooling and heating times of whole sweet potato roots under forced convection conditions. In study four, the performance of charcoal evaporative cooling pad configurations for integration into sweet potato roots storage systems was investigated. The experiments were carried out at different levels of air velocity, water flow rates, and three pad configurations: single layer pad (SLP), double layers pad (DLP) and triple layers pad (TLP) made out of small and large size charcoal particles. The results showed that higher air velocity has tremendous effect on pressure drop. Increasing the water flow rate above the range tested had no practical benefits in terms of cooling. It was observed that DLP and TLD configurations with larger wet surface area for both types of pads provided high cooling efficiencies. In study five, CFD technique in the ANSYS Fluent software was used to simulate airflow distribution in a low-cost mud storehouse. By theoretically investigating different geometries of air inlet, plenum chamber, and outlet as well as its placement using ANSYS Fluent software, an acceptable geometry with uniform air distribution was selected and constructed. Experimental measurements validated the selected design. In study six, the performance of the developed PV ventilated system was investigated. Field measurements showed satisfactory results of the directly coupled PV ventilated system. Furthermore, the option of integrating a low-cost evaporative cooling system into the mud storage structure was also investigated. The results showed a reduction of ambient temperature inside the mud storehouse while relative humidity was enhanced. The ability of the developed storage system to provide and maintain airflow, temperature and relative humidity which are the key parameters for shelf-life extension of sweet potato roots highlight its ability to reduce post-harvest losses at the farmer level, particularly under tropical climate conditions.

Extending the Simple Knowledge Organization System for Concept Management in Vocabulary Development Applications

In this article, we describe the development of an exten- sion to the Simple Knowledge Organization System (SKOS) to accommodate the needs of vocabulary devel- opment applications (VDA) managing metadata schemes and requiring close tracking of change to both those schemes and their member concepts. We take a neo- pragmatic epistemic stance in asserting the need for an entity in SKOS modeling to mediate between the abstract concept and the concrete scheme. While the SKOS model sufficiently describes entities for modeling the current state of a scheme in support of indexing and search on the Semantic Web, it lacks the expressive power to serve the needs of VDA needing to maintain scheme historical continuity. We demonstrate prelimi- narily that conceptualizations drawn from empirical work in modeling entities in the bibliographic universe, such as works, texts, and exemplars, can provide the basis for SKOS extension in ways that support more rig- orous demands of capturing concept evolution in VDA.

Otter (Lutra lutra) distribution modeling at two resolution scales suited to conservation planning in the Iberian Peninsula

We used the results of the Spanish Otter Survey of 1994–1996, a Geographic Information System and stepwise multiple logistic regression to model otter presence/absence data in the continental Spanish UTM 10 10-km squares. Geographic situation, indicators of human activity such as highways and major urban centers, and environmental variables related with productivity, water availability, altitude, and environmental energy were included in a logistic model that correctly classified about 73% of otter presences and absences. We extrapolated the model to the adjacent territory of Portugal, and increased the model’s spatial resolution by extrapolating it to 1 1-km squares in the whole Iberian Peninsula. The model turned out to be rather flexible, predicting, for instance, the species to be very restricted to the courses of rivers in some areas, and more widespread in others. This allowed us to determine areas where otter populations may be more vulnerable to habitat changes or harmful human interventions. # 2003 Elsevier Ltd. All rights reserved.