bluuebunny/crossref_metadata_2025 huggingface dataset:
Can censoring of research outputs be automated to ensure robust data protection?
Authors: Nicholas Michael , Davies Chris , Nock Kelly , Bailey Kerry , Barker Craig , Player Luke , Thomas Helen
Published: April 2017

ABSTRACT

BackgroundGuidance regarding research outputs recommends censoring so that even when aggregating anonymised linked data no cell should have less than 5 -10 units. This is recommended to decrease the likelihood of re- identification. Leaving those cells empty is not adequate if other cells can be used to identify the numerical value of that cell. Some outputs necessitate a large number of tables to be exported this will become more common. This was the case where the outputs from a research study involved several large tables which drove a front end interactive visualisation. As linked data outputs are used to make operational decisions which necessitates timely data outputs of large amount of aggregated data this issue will be more common. Human scanning of all tables may not be time or cost effective and can be subject to human error.

ApproachMany methods of censoring were considered including Barnardisation (adding or subtracting 1 randomly to small numbers) suppression and a combination of methods. It was then necessary to code the methods to ensure that censoring was implemented in all cells in the output and that the output was still meaningful. It was then necessary to check the outputs for quality and introduce an ‘audit’ system to ensure that the quality was maintained but did not impact on the outputs of the findings.

DiscussionSoftware engineers were able to develop an algorithm that performed safe censoring using a level of ‘10 or under’. It also ensured that the statistical tables were still functional. The presentation will describe how this was done and demonstrate some examples of the impact on the output. Some stakeholders felt that the censoring of the anonymised aggregated data went beyond the ‘reasonable effort’ required to re- identify individuals. Some expressed the opinion that the lack of detail and missing data that this method results in is excessive and has been sacrificed for the sake of minimal risk. Some stakeholders felt the risks had been allowed to outweigh the societal benefits. The team were assured that although the censoring may be considered excessive by some it did ensure safe censoring and offered as low a risk a possible for re-identification. However routine implementation of this method has not been agreed.
Involving People with Lived Experience of Homelessness in Electronic Health Records Research
Authors: Luchenski Serena , Clint Sharon , Aldridge Rob , Hayward Andrew , Maguire Nick , Story Alistair , Hewett Nigel
Published: April 2017

ABSTRACTObjectivesWe held a public engagement workshop to involve people with lived experiences of homelessness and social exclusion, experts by experience (EBE), in our research. The purpose of the workshop was to provide context to the findings of a review series on Inclusion Health and to inform future research using electronic health records (EHRs) of homeless and socially excluded people.

ApproachParticipants included 16 volunteers and one staff member from Groundswell (a registered charity that promotes inclusive solutions to homelessness), four academics, one clinical provider, and two note-takers/photographers. The full-day workshop was held at University College London. We used innovative participatory activities specifically designed for use with hidden and marginalised populations to stimulate open dialogue. Methods included general discussion, conceptual mapping, modelling, electronic voting, brainstorming, ranking, graphing, stakeholder analysis, and evaluation surveys. Activities were fast-paced and conducted in small groups, as the whole group, individually, or in pairs. The meaning of Inclusion Health, barriers that lead to exclusion, and values and actions that promote inclusion were discussed. Health statistics on homeless and other socially excluded groups were presented and informed conversations about EHR research, including data collection (new data versus collation of administrative data), data linkage, consent, anonymisation, data security, and ‘the surveillance society.’

ResultsNotes from the workshop and the evaluation surveys indicated that the workshop was engaging, inclusive, and successful. When clearly explained, EBE were positive towards research using EHRs to improve Inclusion Health, including data linkage of sensitive health and social data. EBE expressed that housing, advocacy, and psychosocial therapies were the most important interventions for improving health of people who are homeless; however, we found limited evidence for these interventions in our review. Overall, findings demonstrate the value of involving the people who have been socially excluded to develop research priorities and to interpret findings.

ConclusionUsing a participatory and dynamic approach to involve people with lived experience of homelessness and exclusion is an effective public engagement methodology for complex topics such as EHR research and data linkage. Information provided in the workshop was useful for interpreting findings, identifying strengths and gaps in health and social services, and developing research and practice recommendations.
Identifying Household Level Risk Factors for Unintentional House Fire Incidents, Injuries and Fatalities
Authors: Turner Samantha , Rodgers Sarah , Lyons Ronan
Published: April 2017

ABSTRACTObjectivesUnintentional house fire incidents, injuries and deaths are a serious public health concern in the UK, which disproportionally affect certain groups in the population. Whilst house fires have decreased in recent years; growing financial pressures in the Fire and Rescue Services (FRSs) have resulted in funds dedicated to fire preventative activities becoming increasingly limited. To ensure ever limiting resources are targeted towards those households at greatest risk, it is essential the FRSs’ are accurately informed about the types of household at increased risk. The aim of this project is to undertake a large-scale case-control study, to identify the distinguishing household level risk factors associated with unintentional house fire incidents, injuries and deaths.

ApproachUnintentional house fire incidents reported to the Welsh FRS between the years 2003-2008, were anonymised and incorporated into the Secure Anonymised Information Linkage (SAIL) Databank at the Farr Institute, Swansea University. 6943 case households (households which reported a fire to the FRS) were time-matched to 347,150 control households (case:control ratio 1:50). Individuals registered as living at these properties on the date of the fire were established using the Welsh Demographic Service (WDS) dataset. Household level variables will be created by linking case and control households to other demographic, health, educational and environmental datasets in SAIL. Conditional Logistic Regression will be used to estimate matched odds ratios and 95% confidence intervals.

ResultsPotential risk factor variables were selected on the basis of a systematic review and theoretically plausible variables. Covariates include: household composition (e.g. age and gender of residents), socioeconomic status, educational attainment, smoking, alcohol consumption, mental health conditions, other health related conditions, mobility and sensory impairments and property related characteristics. Fire related circumstances (e.g. fire ignition source, presence of a smoke alarm) will also be investigated in logistic regression models exploring risk factors for injury and death. Results will be presented at the conference.

ConclusionThis is the first large-scale analysis of risk factors for unintentional house fire incidents, injuries and deaths. The findings from this project will be translated into comprehensible infographics, designed to support the FRSs, other partner organisations and the general public, recognise high risk households in need of preventative interventions.
Administrative, legal, and organizational hurdles in data linkage: Experiences and lessons from the recent National Center for Health Statistics (NCHS) - U.S. Department of Housing and Urban Development (HUD) data linkage project
Authors: Sperling Jon , Lloyd Patricia , Helms Veronica , Brittain James
Published: April 2017

ABSTRACT

ObjectivesThrough a collaborative agreement between the NCHS and HUD, the first linkage of two national population health surveys to HUD administrative records of housing assistance was recently completed. Based on this multi-year effort, this paper emphasizes key requirements for making progress in and between regulatory and legal environments; confidentiality and data security.

BackgroundAs the principal health statistics agency in the United States, the National Center for Health Statistics (NCHS) collects and disseminates statistical information that guide actions and policies to improve the health of the American people. The mission of the U.S. Department of Housing and Urban Development (HUD) is to create strong, sustainable, inclusive communities and quality affordable homes for all. Prior to the release of the NCHS-HUD linked file, there was no existing data source to reliably estimate the prevalence of health conditions and outcomes for households receiving HUD housing assistance. Rather than conducting its own health survey, costing millions of dollars, HUD leveraged the existing NCHS and Census knowledge base, the data linking expertise of NCHS and its Research Data Center (RDC) infrastructure. With the NCHS-HUD linked data files, analysts and researchers can now examine health conditions, health behaviors, access to health services and use of health services in relation to housing.

ApproachWhile technical (e.g., temporal, spatial, definitional, linkage keys) challenges for linking national-level surveys and administrative data have been the subjects of many discussions, often the organizational, legal and behavioral issues are more daunting and usually determine success. To comply with regulations at NCHS and HUD, a memorandum of understanding clearly outlined the manner with which personally identifying information (PII) would be protected, and how data would be shared across agencies.

Results and ConclusionThrough this extraordinary and innovative, no-cost, collaborative and strategic research partnership with the Department of Health and Human Services/Centers for Disease Control and Prevention/NCHS, HUD is learning more about the health of tenants receiving housing assistance. The data linkage project is a model for data sharing that aligns with U.S. Office of Management and Budget (OMB) directives for sharing data across federal agencies to reduce respondent burden and improve federal programs and as well as the health of American people.
Codifying unstructured data: A Natural Language Processing approach to extract rich data from clinical letters
Authors: Lacey Arron , Lyons Jane , Akbari Ashley , Turner Samantha L , Walters Angharad M , Fonferko-Shadrach Beata , Pickrell Owen , Rees Mark I , Lyons Ronan A , Ford David V , Middleton Rod M
Published: April 2017

ABSTRACT

ObjectivesElectronic healthcare records (EHR) are the main data sources that facilitate epidemiology research. Routinely collected data such as primary and secondary care are now easily linked to produce novel and high impact research. There are, however, rich data locked in the free text of clinical letters that are not otherwise translated into EHRs. It is highly desirable to be able to extract this information to strengthen the body of information in existing EHRs.

The Swansea Collaborative in Analysis of NLP Research (SCANR) group at Swansea University has been established to evaluate the usage of Natural Language Processing platforms for obtaining new clinical data. To use Clix Enrich to extract SNOMED concepts from a variety of clinical free texts and produce EHRs from the extraction process.

Approach SNOMED concepts contain common items of interest such as diagnosis, medication and symptoms, as well as contextual concepts such as historical reference and negation. Clix Enrich uses the SNOMED dictionary to encode clinical free text (pre-co-ordinated) and find contextually correct SNOMED concepts (post co-ordinated). We used Clix Enrich to extract meaningful clinical terms from MS and Epilepsy consultant letters, as well as presenting complaint fields from a Welsh Emergency Department (ED).

ResultsWe tailored Clix Enrich to extract a wide variety of clinical terms from each source (fourty texts per source) and validated the extraction accuracy with clinical experts in each domain. Clix Enrich was able to accurately extract the correct diagnosis for MS, Epilepsy and ED attendance (100%, 95% and 80%), dosage and frequency of anti-epileptic medication and MS modifying therapy (90%, 100%) and EDDS score (94%). We note a probable source of discrepancy in extraction accuracy between letter sources in the frequency of abbreviated terms, particularly within the presenting complaint field of the ED sample.

ConclusionClix Enrich can be used to accurately extract SNOMED concepts from clinical letters. The resulting datasets are readily available to link to existing EHRs, and can be linked to EHRs that adopt the SNOMED coding structure, or backward compatible hierarchies. Clix Enrich comes with out-of-the-box extraction methods but the optimum way to extract the correct information would be to build in custom queries, thus requiring clinical expertise to validate extraction.
Primary care contact before and after emergency hospitalisation in children in English NHS hospitals: a linked administrative data study
Authors: Wijlaars Linda , Hardelid Pia , Gilbert Ruth
Published: April 2017

ABSTRACT

ObjectivesEmergency admissions for ambulatory care sensitive conditions (ACSCs) are thought to be preventable through preventive or early treatment interventions in primary care. However, evidence shows up to 70% of children with ACSCs admissions have underlying chronic conditions, suggesting that these admissions could be less amenable to primary care prevention than previously thought. We determined the extent to which primary care is involved in care by assessing primary care consultations before and after an emergency admission to hospital for an ACSC.

ApproachWe used a national general practice database (Clinical Practice Research Datalink) linked to hospital admissions data (Hospital Episode Statistics) and included children aged 0-19 years with emergency admissions for ACSCs or injury between 2000-2009. ACSCs were defined as acute infections (pneumonia and lower respiratory tract infections (LRTIs), dehydration and gastroenteritis (DGE), urinary tract infections (UTIs)), and asthma. We included injuries as a control group as we did not expect to see an increase in GP consultations for this group before emergency admission.

We calculated hospital admission rates by age, gender and area-level deprivation per 1,000 child-years and determined the proportion of children consulting their GP in the week before and week after emergency admission. We examined independent risk factors using zero-inflated negative binomial regression models.

ResultsWe extracted data for 1,664,555 children with 32,442 emergency admissions for ACSCs and 39,305 for injuries. There were clear socioeconomic gradients: LRTIs, UTIs and asthma were more prevalent in more deprived children, while rates for DGE and injuries were similar between deprivation quintiles. The majority of children with emergency admissions for ACSCs consulted their GP in the week before admission (range 58.3% (asthma) - 69.5% (LRTIs)), while 24.2% of children with injuries had a GP consultation. Children with ACSCs were more likely to consult their GP after discharge, with 37% (LRTIs) - 46% (UTI) of children consulting in the week after discharge, compared to 22% after injury admission. The proportion of children consulting their GP in the week before an emergency admission decreased. For LRTIs, this decreased from 71.7% in 2000 to 55.2% in 2009.

ConclusionThe majority of children consulted a GP both before and after an ACSC emergency admission. This suggest that the degree to which primary care can prevent ACSCs conditions in children might be less than previously thought. Further research is needed to determine which community or hospital based interventions, if any, can reduce ACSC emergency admissions.
Novel Tools Supporting Knowledge Translation for Public Health Practice in British Columbia, Canada
Authors: Stares Joanne , Sutherland Jenny
Published: April 2017

ABSTRACT

ObjectivesUnderlying the delivery of services by the universal Canadian health care system are a number of rich secondary administrative health data sets which contain information on persons who are registered for care and details on their contacts with the system. These datasets are powerful sources of information for investigation of non-notifiable diseases and as an adjunct to traditional communicable disease surveillance. However, there are gaps between public health practitioners, access to these data, and access to experts in the use of these secondary data. The data linkage requires in-depth knowledge of these data including usages, limitations and data quality issues and also the skills to extract data to support secondary usage. OLAP reports have been developed to support operation needs but not on advanced analytics reports for surveillance and cohort study. To fill these gaps, we developed a set of web-based modular, parameterized, extraction and reporting tools for the purpose of: 1) decreasing the time and resources necessary to fill general secondary data requests for public health audiences; 2) quickly providing information from descriptive analysis of secondary data to public health practitioners; 3) informing the development of data feeds for continued enhanced surveillance or further data access requests; 4) assisting in preliminary stages of epidemiological investigations of non-notifiable diseases; and, 5) facilitating access to information from secondary data for evidence-based decision making in public health.

ApproachWe intend to present these tools by case study of their application to small area analysis of secondary data in the context of air quality concerns. Data sources include individuals registered for health care coverage in BC, hospital separations, physician consultations, chronic disease registries, and drugs dispensation. Data sets contain complete information from 1992. Data were extracted and analyzed to describe the occurrence of health service utilization for cardiovascular and respiratory morbidity. Analysis was undertaken for BC residents in areas identified by local public health as priorities for monitoring. Health outcomes were directly standardized by age and compared to provincial trends by use of the comparative morbidity figure.

ResultsResults will include descriptive epidemiological analysis of secondary data relating to respiratory and cardiovascular morbidity in the context of air quality concerns, summary of next steps, as well as an assessment of tool performance.

ConclusionsWhere adopted tools such as these can make information from secondary data more accessible to support public health practice, particularly in regions with low analytical or epidemiological capacity.
Linkage of health insurance data to the Netherlands Twin Register
Authors: Van Grootheest Gerard , Ariel Adelaide , Glasner Tina , Verkerk Bep , Van Beijsterveldt Toos , Van der Laan Jan , De Groot Mark , Visser Sipke , Bakker Bart , Boomsma Dorret
Published: April 2017

ABSTRACTObjectivesWe compared four different approaches to record linkage, demonstrating its potential in enriching the Netherlands Twin Register (NTR) with healthcare data from a large health insurance provider (AHD), which covers approximately 26% of the population. Challenges included the fact that young twins share most of their linkage variables and overlapping identification numbers were absent. We extensively validated the linkage results and complemented them with an indicator of representativeness.ApproachSubjects born since 1986 were selected in the NTR (N=30,383) and AHD (N=1,532,675). Linkage variables were cleaned and harmonised and linkage keys were chosen that were strong enough to uniquely identify most subjects in either dataset. The four linkages were deterministic, probabilistic, probabilistic with Jaro-Winkler distance, and probabilistic using encrypted identifiers.Validation took place by reviewing linkage variables and information like family relations; linked record pairs were categorised into correct, possible or false links. Furthermore, the consistency of linked data was reviewed focusing on Attention Deficit Hyperactivity Disorder (ADHD), a prevalent condition among children. Finally, we quantified the impact of the linkage on representativeness of the target population.ResultsProbabilistic linkage with distance calculation linked 7944 NTR subjects to the AHD with 82% correct, 17% possible, and 1% false links. It encompassed nearly all links identified by any of the other methods, which were more conservative.Information about medication was available in the NTR dataset for 40% of the linked subjects. Validation of the information about ADHD inside linked records revealed few discrepancies between the two datasets. Linkage had a modest effect on the representativeness of the population. The current linkage has confirmed a number of known ADHD cases and identified 146 new subjects using methylphenidate and 101 receiving psychiatric care for ADHD, who were not previously recognized as ADHD cases within the NTR. ConclusionRecord linkage with sources of data such as a health insurance database can be an efficient way of data collection in cohort research. Our study shows that record linkage is also possible for twin pairs. Although a minority of all NTR subjects were covered by the AHD, the linkage resulted in an enrichment of the NTR dataset. Exact information about the dosage and frequency of drugs was obtained without contacting subjects with detailed questionnaires. With a total of almost eight thousand retrieved records, the size of the linked dataset is sufficiently large for epidemiological research of non-rare conditions.
Effects of fetal reduction in multi-fetal pregnancy on perinatal outcomes
Authors: Razaz Neda , Avitan Tehila , Pressey Tracy , Joseph K.S.
Published: April 2017

ABSTRACTBackgroundThere is currently insufficient evidence regarding the prognosis of multi-fetal pregnancies reduced to twins or singletons. We compared the perinatal outcomes of deliveries following fetal reduction with the perinatal outcomes of deliveries without fetal reduction.

MethodsWe carried out a retrospective cohort study of all births in British Columbia between 2009 and 2013, using information from a population-based database. Comparisons were made between all women who had a fetal reduction to a twin or a singleton pregnancy with those who did not undergo a fetal reduction procedure. The outcomes of interest were preterm delivery and composite severe neonatal morbidity or perinatal mortality. Generalized estimating equations adjusting for maternal age, parity, pre-pregnancy weight, use of in vitro fertilization and baby’s sex were used to estimate odds ratios (OR) and 95% confidence intervals (CI).

ResultsAmong 207,273 deliveries, 139 (0.07%) had a fetal reduction. Of these, 89 women delivered twins and 50 delivered singletons. Women who had a fetal reduction were more likely to have conceived with in vitro fertilization (77.6%) compared with those who did not (3.31%). Twins delivered after fetal reduction had lower rates of neonatal morbidity/mortality (OR 0.19, 95% CI 0.08-0.42) compared with unreduced triplets but rates similar to those of twins without a reduction procedure (OR 1.44, 95% CI 0.81-2.58). Singletons delivered after fetal reduction had non-significantly lower rates of neonatal morbidity/mortality than unreduced twins (OR 0.75, 95% CI 0.36-1.57) but significantly higher rates of neonatal morbidity/mortality (OR 3.98, 95% CI 1.91-8.30), preterm delivery and being small for gestational age than singleton pregnancies without a reduction procedure.

ConclusionPerinatal outcomes of twins delivered after fetal reduction are better than those of unreduced triplets and similar to those of unreduced twins.
Do socially complex patients seek primary care from clinics specifically designed to meet their needs?
Authors: Katz Alan , Chateau Dan , Taylor Carole , Valdivia Jeff
Published: April 2017

ABSTRACTObjectivesTo determine the relationship between known social complexity and model of primary care service deliveryApproachThe impacts of the social determinants of health are well described. To understand the contribution of specific factors on primary care service use we linked social data in the Population Health Research Data Repository at the Manitoba Centre for Health Policy to health system data. We included all patients visiting a Winnipeg clinic at least three times between 2010 and 2013. We allocated each participant to the primary care provider providing the majority of their care; and each provider was assigned to the model of care where they provided the majority of their clinical care. We developed eleven new indicators to describe social complexity such as: children in care, low income quintile, income assistance (welfare), high residential mobility, and involvement with the justice system. Results The cohort included 626,264 unique individuals of whom 53.1% were female. The majority of participants received their care from the fee for service (FFS) model (511,763) followed by 76,261 assigned to “reformed FFS”. 16,536 and 12,178 were assigned to the 2 team-based care alternative funded models and 9,526 to the teaching clinic model. Patients with social complexities, except for newcomers, were more likely to attend the alternative funded clinics. The patients these clinics served were generally very complex with over 15% having more than 5 complexities compared to less than 5% of those attending the FFS models. Twice as many patients in the FFS models (60%) had no complexities compared to the alternative funded models.ConclusionThe availability of social data in population health repositories provides new opportunities to understand the distribution of these social factors amongst care providers and the impact of each on the health of populations. This new understanding can support focused interventions to address specific social risk factors and provide the evidence to support different models of primary care service delivery.
Record Linkage Project Process Model
Authors: Trudeau Richard
Published: April 2017

ABSTRACTObjectivesIn April 2015, a Working Group on Record Linkage was created at Statistics Canada with the objective of achieving a common understanding of the concepts and processes involved in record linkage projects at Statistics Canada. ApproachA generic record linkage process model was mapped to reflect the general practices and activities involved in record linkage at Statistics Canada. The model was developed with a view for more general use by other statistical agencies involved in record linkage. It was built on the Generic Statistical Business Process Model v5.0 developed by the Joint UNECE/Eurostat/OECD Work Session on Statistical Metadata (METIS) for survey purposes. It also builds on international models of record linkage from Australia and the United States as well as record linkage methodology used at Statistics Canada. In addition, it was informed by the relevant legal and policy frameworks that govern all of Statistics Canada statistical activities. Over one hundred people involved in all aspects of record linkage at Statistics Canada were consulted during this process.ResultsAn activity-oriented Record Linkage Project Process Model was drafted and proposed as a standard for the agency. It breaks down the record linkage process into three meta-phases: project planning, record linkage, post-linkage activities. Each meta-phase is further divided into phases and sub-phases that describe the activities of the record linkage project from specification of needs to project close-out and evaluation. An additional feature of the model is a description of the outcome of each phase that can be used as a milestone marker or as a gateway to the next phase. ConclusionAs a descriptive model, the Record Linkage Project Process Model will inform management on the range of activities related to a record linkage project that go well beyond the function of matching records between two data files. It can also be used as a prescriptive model that will provide guidance to individuals engaging in a record linkage project.
Using Bayesian Model Averaging to Analyse Hierarchical Health Data: model implementation and application to linked health service use data
Authors: Hassani-Mahmooei Behrooz , Berecki-Gisolf Janneke , Collie Alex
Published: April 2017

ABSTRACTObjectiveThe majority of standard coding systems applied to health data are hierarchical: they start with several major categories and then each category is broken into subcategories across multiple levels. Running statistical models on these datasets, may lead to serious methodological challenges such as multicollinearity between levels or selecting suboptimal models as model space grows exponentially by adding each new level. The aim of this presentation is to introduce an analytical framework that addresses this challenge. ApproachData was from individuals who claimed Transport Accident Commission (TAC) compensation for motor vehicle accidents that occurred between 2010 and 2012 in the state of Victoria, Australia and provided consent for Pharmaceutical Benefits Scheme (PBS) and Medicare Benefits Schedule (MBS) linkage (n=738). PBS and MBS records dating from 12 months prior to injury were provided by the Department of Human Services (Canberra, Australia). Pre-injury use of health service items and pharmaceuticals were considered to indicate pre-existing health conditions. Both MBS and PBS listings have a hierarchical structure. The outcome was the cost of recovery; this was also hierarchical across four level (e.g. total, medical, consultations, and specialist). A Bayesian Model Averaging model was embedded into a data mining framework which automatically created all the cost outcomes and selected the best model after penalizing for multicollinearity. The model was run across multiple prior settings to ensure robustness. Monash University’s High Performance Computing Cluster was used for running approximately 5000 final models.ResultsThe framework successfully identified variables at different levels of hierarchy as indicators of pre-existing conditions that affect cost of recovery. For example, according to the results, on average, patients who received prescription pain or mental health related medication before the injury had 31.2% higher short-term and 36.9% higher long-term total recovery cost. For every anaesthetic in the year before the accident, post-injury hospital cost increased by 24%, for patients with anxiety it increased by 35.4%. For post-injury medical costs, every prescription of drugs used in diabetes (Category A10 in ATC) increased the cost by 8%, long term medical costs were affected by both pain and mental health. ConclusionBayesian model averaging provides a robust framework for mining hierarchically linked health data helping researchers to identify potential associations which may not have been discovered using conventional technique and also preventing them from identifying associations that are sporadic but not robust.
New Mode Transition of H-bridge Bi-directional DC-DC Converter in Distributed Generation System
Authors: A. Yi Lingzhi  , B. Chen Yu  , C. Ren Xuliang  , D. Zhang Hao
Published: April 2017

There are many problems in H-bridge bi directional DC-DC converter, such as slow dynamic response and bus-bar voltage overshoot etc. The proposed method of dual carrier modulation which can greatly simplify the control method, is used to smooth mode transition. Then a Fractional Order PID (FOPID) controller which can provide an excellent dynamic performance, more flexibility and robustness for the system, is investigated. Finally, simulation model has been built, and an 1kW experimental prototype has been built.
Evaluation of a new Power Quality index, based in Higher Order Statistics
Authors: J.M. Sierra-Fernández  , J.J. González De La Rosa  , A. Agüera-Pérez  , J.C. Palomares Salas  , O. Florencias Oliveros
Published: April 2017

The present works deals with the presentation and test of a novel Power Quality index, based in Higher-Order cumulants. Synthetics are used for test different start point, amplitude and length for the most common Power Grid disturbances (DIP, Oscillatory Transient, Harmonic Temporal Distortion and Impulsive Transient), obtaining a high accuracy (over 99% in some disturbances). Then real signals are used for confirm synthetics results. Finally, the Power Quality index presented, is confirmed with real signals as a good tool for detect imperfections in the power waveform.
A novel instrument for power quality monitoring based in higher-order statistics: a dynamic triggering index for the smart grid
Authors: Olivia Florencias-Oliveros  , Agustín Agüera-Pérez  , Juan-José González-de-la-Rosa  , José-Carlos Palomares Salas  , José-María Sierra-Fernández
Published: April 2017

This paper presents a novel virtual instrument for PQ assessment, based in higher-order statistics. It implements a new power-quality index, which is thought to trigger the measurement procedure when an electrical fault comes about. The user interfaces include not only the online variance charts but also the skewness and kurtosis graphs, along with hybrid representations of variance versus higher-order statistics. Designed on the basis of 85 signals recorded, 50 Hz real-time with different disturbances. The instrument validates the PQ procedure during online sessions. The new monitoring strategy activates the analysis of the signal once the PQ index overpassed a predefined threshold. Results show that voltage sags and transients are classified within different clusters, with low uncertainty, using different types of graphs. This flexibility may allow the operator to reduce the subjectivities during the online monitoring session with an optimal computational solution.
Implementation of High frequency SVM in a Digital System for CS-SiC Inverter.
Authors: E. Fernández  , A. Paredes V. Sala  , L. Romeral
Published: April 2017

The operation of current source inverters at high frequency allows to reduce the size of the input coil and output filters. These advantages allowed to obtain converters with better performance and to reduce the size and weight of the passives elements, decreasing the manufacturing costs and while keeping the current harmonic distortion low. For these reasons, it is necessary to implement a modulation technique that allows the converter to work at a higher frequency 100 KHz. This article presents the design and implementation of a Space Vector Modulation (SVM) technique for high switching frequencies for a Current Source Inverter (CSI) topology implemented with SiC devices. The technique is programmed and implemented in a PIC 24FJ256GA406 microcontroller, for the activation and control of SiC devices in each leg of power converter.
Power Hardware In The Loop Realization, Control and Simulation of Synchronous Generator Using Three Phase VSI for Microgrid Studies
Authors: B. Ojaghloo  , G.B. Gharehpetian
Published: April 2017

In subject of hardware in the loop (HIL) and power hardware in the loop (PHIL) systems, a part of system is a real physical subsystem and another subsystem is simulated in the processor. This paper discusses this concept for a synchronous generator and chooses the best options for different parts of software side for its PHIL implementation. The PHIL system is simulated in Matlab/Simulink environment and results are validated using Matlab synchronous generator block as reference system. Also, different disturbances are applied to reference and simulated systems and the results are compared. The results show synchronous generator internal and external variables are emulated correctly by realized PHIL.
GENERATION OF ELECTRICITY USING RENEWABLE ENERGY RESOURCES
Authors: Saifur Rahman  , Alwadie A.  , Faizan A Khan
Published: April 2017

The conventional energy resources are limited in nature, therefore it is essential to change the attention towards the other renewable energy resources. For the development of human progress energy has turn out to be an important part. Now days thrust for current renewable energy resources are leading to incessant and wide research. Wind energy, geothermal, biogas and Photovoltaic (PV)-alone are used as a single source for renewable energy. The financial features of these renewable energy tools are not fully promising. Renewable sources are under research now a days. The restriction on economic feature of various renewable sources like wind and solar PV is kept in mind and designed to develop a combined renewable energy systems. A technique is proposed in this paper which aims to improve power production by the renewable resources, like the combination of solar PV, speed breaker (roller) and sound of traffic. Using these renewable sources hybrid electricity is generated which is further utilized for street light application.
Validation of eAircraft battery simulation approach using field measurement data
Authors: T. Debreceni  , P. Szabó  , G. Gy. Balázs  , I. Varjasi
Published: April 2017

Due to the specifically high power pulse and long duration energy requirements against lithium battery systems in electric aircrafts, the electrical design cannot be realized without sufficient modeling and simulation of such batteries considering the nonlinear behavior of cells and mission profiles. This paper presents an overview of the simulation approach and confirms the performance for using it as a design tool. The validation process of the models and simulation environment in MATLAB/Simulink includes error analysis investigating real measurement data recorded during flights of a fully electric aircraft.
Implementation of a Generic Type I Wind Turbine Generator for Power System Stability Studies
Authors: R. Villena-Ruiz  , A. Lorenzo-Bonache  , A. Honrubia-Escribano  , E. Gómez-Lázaro
Published: April 2017

According to the International Electrotechnical Commission (IEC), the standardization and modelling of generic Wind Turbine Generators (WTG) is a key fact which allows the co-operation of international organizations in the electrical field. Thus, according to the IEC 61400-27-1, the generic Type 1 WTG model has been implemented and simulated in DIgSILENT PowerFactory (PF). In fact, PF is the preferred software tool for some of the European network operators. The process of structuring and construction of the different WTG components within PF are conveniently described in this paper. In order to correctly simulate the generic IEC WTG model in PF, aerodynamic and mechanical systems are also required. For this reason, the Dynamic Simulation Language (DSL) tool within PF has been used for modelling these non-electrical components. Moreover, this language allows the dynamic modelling of linear and non-linear systems. Finally, once all the WTG components have been defined, normal and fault conditions have been analyzed in order to study the WTG dynamic response.
The use of Model Predictive Control (MPC) in the optimal distribution of electrical energy in a microgrid located in southeastern of Spain: A case study simulation
Authors: César Hernández-Hernández  , Francisco Rodríguez  , José Carlos Moreno  , Paulo Renato da Costa Mendes  , Julio Elías Normey-Rico
Published: April 2017

The microgrids allow the integration of renewable sources of energy such as solar and wind and distributed energy resources such as combined heat and power, energy storage, and demand response. In addition, the use of local sources of energy to serve local loads helps reduce energy losses in transmission and distribution, further increasing efficiency of the electric delivery system. In this paper, the optimization problem of the energy in a microgrid (MG) located in southeastern of Spain, with Energy Storage System (ESS), which exchanges energy with the utility grid is developed using Model Predictive Control techniques. System modelling use the methodology of the Energy Hubs. The MPC techniques allow maximizing the economic benefit of the microgrid and to minimize the degradation of storage system.
Maximum Power Point Tracker Based Digital One Cycle Control Applied in PV Systems
Authors: A. C. Q. B. Leite  , A. O. Salazar  , J. T. Carvalho
Published: April 2017

The Photovoltaic energy shown an alternative to meet the growing energy demand and reduce dependence on fossil fuels. This paper makes an approach to the need to extract the maximum power of photovoltaic panels via algorithms, such as the constant voltage. It was also used a tracking algorithm based on temperature measurement, where it returns the value of the reference voltage when a temperature change occurs. To make the switching controller was used the one cycle control - OCC by presenting a higher speed of convergence, disturbance rejection of the source and no steady-state error. It was implemented in a DC-DC Boost converter to extract the maximum power of the panel and was observed that OCC is faster than PWM and the temperature algorithm was more efficient than a pure constant voltage method.
Optimization Measures for Increased Immunity against High Frequency Disturbances and Reduced Emission in the Range of 2 kHz to 150 kHz Realized on Different LED Lamps
Authors: Thomas Wohlfahrt  , Christian Waniek  , Johanna M.A. Myrzik
Published: April 2017

In this paper, optimization measures to increase the immunity against high frequency (HF) disturbances by simultaneously reducing the impact on the grid through non sinusoidal input currents in the frequency range of 2 kHz to 150 kHz are presented. Two different light-emitting diode (LED) lamps as an example for typical electronic mass-market products are optimized. Currently, LED lamps are state of the art in the range of efficient lamps. But long-term experiences concerning their immunity against HF disturbances are not investigated so far. In order to assess the additional stress on the built-in components of the LED lamps caused by HF disturbances, the power supplies of two exemplary LED lamps are considered and their input current, the current of the electrolytic capacitor and the current of the LED are depicted. Based on these measurements, the electrolytic capacitor can be identified as one mainly weak point of the LED lamp’s power supply. Subsequently, possible measures to increase the immunity of the identified stressed components and the LED lamp by itself are presented. Finally, the overall efficiency of the optimizations and their effect on the grid’s power quality are shown.
Study on Voltage Control of Distribution Network Using PV Generation Forecasting
Authors: H. Kobayashi  , M. Kato
Published: April 2017

With the expected spread of photovoltaic (PV) systems, high power generation in spring and summer is expected to cause abnormally high voltage in distribution systems. As described in herein, we propose a method to improve the utilization efficiency of a small-scale PV generator connected to a distribution system by short-term (30 min) forecasting of solar power generation output in a small area of a few kilometers. As a countermeasure against abnormally high voltage, a method exists to adjust the voltage by switching a tap of the substation transformer. However, the switching frequency of the tap with mechanical contact is limited to once or twice per hour. Under these conditions, if short-term forecasting of solar power generation were possible, then tap changing of a substation transformer efficiently could maintain voltage within an appropriate range, which enables effective use of solar power. This paper is organized as follows. After a short-term forecast method of solar power is proposed. The method of adjusting the sending end voltage of a distribution substation based on the PV output forecast data is proposed. Finally, reduction of the PV disconnection frequency is verified numerically.
Application of Double Fourier Series for Analyzing Harmonics of a Modular Multilevel Converter
Authors: Ngoc-Thinh Quach  , Sang Heon Chae  , Min-Hyeok Kang  , Dong Wan Kim  , Seung Hun Ko  , Eel-Hwan Kim
Published: April 2017

This paper presents an application of double Fourier series (DFS) algorithm for analyzing harmonics of a modular multilevel converter (MMC). By considering the effect of arm inductor, the application of DFS for calculating harmonics in the MMC is made. The DFS is then verified by comparing with simulation results used the fast Fourier transform (FFT) algorithm. Subsequently, the DFS will be used to analyze the effect of number of output voltage levels to the distribution of harmonics and total harmonic distortion (THD) in the MMC. The analytical results are performed in the Matlab programming in order to verify the theoretical analysis.
A Study on Wind Smoothing Control by Using Short-term Average Value through Detecting Wind Power Fluctuation Rate
Authors: Sang Heon Chae  , Eel-Hwan Kim
Published: April 2017

In order to increase grid stability, there are some methods to reduce wind power fluctuation by using energy storage system (ESS). Operating time of ESS will determine its losses and the lifetime of batteries. From this point, this paper proposes a wind power smoothing control by calculating short term average value of wind power. In this case, the operation of ESS will be decided through detecting wind fluctuation rate during 60 seconds. It means that the ESS will not operate at small fluctuation of wind power which does not affect the grid stability. The effectiveness of proposed method will be verified by comparing the conventional method with the proposed method. The wind power data were measured by power quality analysis device from 15 MW wind farm in Jeju Island located in South of Korea peninsula. The simulation results are carried out by using Matlab program.
Modular and Scalable FACTS Systems for Improving Stability in Distribution and Transmission Networks, Using the Example of a STATCOM System in an Offshore Distribution Network
Authors: Tobias Funk  , René Rund  , Thomas Röseler  , Tomaz Pfeifer
Published: April 2017

This article addresses the challenges faced by safe operation of offshore distribution networks supplied from the land, taking into consideration long sea cable connections, variations in supply and feed-in scenarios, and non-linear equipment characteristics. Delivering a suitable topology and variable control parameters, STATCOM systems make a significant contribution to the stable supply of offshore consumers in applications like these, with technical connection conditions taken into account. Using the design process as an example, this article presents various methods for designing and proving the stable operating behaviour of modular and scalable STATCOM systems.
First Order Integral Sliding Mode Control for Active and Reactive Current of A Multilevel Inverter Based Distributed Generation Unit
Authors: A. Elnady
Published: April 2017

This paper presents an innovative control scheme for Distributed Generation Systems, DGS, using an efficient version of the first order Sliding Mode Control, SMC. The control law of the SMC is modified in order to improve the tracking and reduce the chattering over the conventional SMC. The modification is focused on the definition of the sliding manifold, sliding surface, which contains an integral term of the error not a differential term like the conventional SMC. The proposed control scheme is applied to a multilevel diode clamped inverter based Distributed Generation Unit, DGU. The proposed control scheme is developed to control the active and reactive currents injected or absorbed by the power grid. Simulation results are provided to prove the viability of the proposed formulation and practicality of the presented sliding mode controller for the distributed generation system.