Identification of Load Power Quality Characteristics using Data Mining

The rapid increase in computer technology and the availability of large scale power quality monitoring data should now motivate distribution network service providers to attempt to extract information that may otherwise remain hidden within the recorded data. Such information may be critical for identification and diagnoses of power quality disturbance problems, prediction of system abnormalities or failure, and alarming of critical system situations. Data mining tools are an obvious candidate for assisting in such analysis of large scale power quality monitoring data. This paper describes a method of applying unsupervised and supervised learning strategies of data mining in power quality data analysis. Firstly underlying classes in harmonic data from medium and low voltage (MV/LV) distribution systems were identified using clustering. Secondly the link analysis is used to merge the obtained clusters into supergroups. The characteristics of these super-groups are discovered using various algorithms for classification techniques. Finally the a priori algorithm of association rules is used to find the correlation between the harmonic currents and voltages at different sites (substation, residential, commercial and industrial) for the interconnected supergroups

The technical and economic benefits of utility sponsored renewable energy integration

In recent years, Australian energy consumers have begun to install large amounts of distributed generation (DG), particularly residential solar photovoltaic (PV) systems. This rapid increase in DG, has led to the flow of power throughout low voltage (LV) networks to become bidirectional. This reverse power flow, along with the intermittent nature of solar PV and the inability for distribution network service providers (DNSPs) to control where this DG is installed, has led to voltage regulation issues throughout LV networks. Along with solar PV, energy storage (ES) is also becoming more prevalent among energy consumers. The combination of solar PV and ES allows customers to become more energy independent, relying less on utilising energy from the grid. This poses a major risk to DNSPs who rely on the income generated from customers based on kWh sales to build and maintain network infrastructure. This paper presents a coordinated reactive power control scheme to reduce voltage rise along LV distribution feeders with high penetrations of solar PV. The value of privately investing in solar PV and ES for the years 2015 and 2020 from the perspective of an average residential customer is determined. Finally, a business model is proposed outlining how utility sponsored residential solar PV and ES could be implemented by a DNSP. The business model is then evaluated from a technical and economic standpoint

Background Radio Frequency Interference Measurements for Wireless Devices in the Electricity Supply Industry

Incorporation of radio controller units into heavy equipment used in the electricity industry provides numerous advantages including: improved electrical isolation between plant and operator, ability to incorporate an additional remote operator, and reductions in vehicle wiring and hydraulic hoses for equipment control. However, secure operation of vehicles and plant incorporating radio control rely on establishing suitable levels of immunity to possible radio frequency interference. Interference levels in close proximity to high voltage power lines are of special concern to the electricity industry. This paper reports on a preliminary investigation into quantifying the levels of background radio interference at such locations in order to develop required immunity specifications for radio controlled equipment

Hybrid model predictive control of a residential HVAC system with PVT energy generation and PCM thermal storage

This paper describes an experimental investigation into the performance of a Hybrid Model Predictive Control (HMPC) system implemented to control a novel solar-assisted HVAC system servicing the Team UOW Solar Decathlon house, the overall winner of the Solar Decathlon China 2013 competition. This HVAC system consists of an air-based photovoltaic thermal (PVT) collector and a phase change material (PCM) thermal store integrated with a conventional ducted reverse-cycle heat pump system. The system was designed for operation during both winter and summer, using daytime solar radiation and night sky radiative cooling to increase the energy efficiency of the air-conditioning system. The PVT collector can exchange heat with the PCM thermal storage unit, and the stored heat can be used to condition the space or precondition the air entering the air handling unit (AHU). The HMPC controller includes two levels of control, where the high-level controller has a 24-hour prediction horizon and a 1-hour control step is used to select the operating mode of the HVAC system. Low-level controllers for each HVAC operational mode have a 1-hour prediction horizon and a 5-minute control step, and are used to track the trajectory defined by the high-level controller and to optimize the operating mode selected. The results from this preliminary experimental work have demonstrated the value of the HMPC approach in optimally controlling the solar-assisted HVAC system in the Solar Decathlon house. Results show that the HMPC controller successfully selected the appropriate operating mode to achieve multiple objectives, including: maintenance of indoor comfort conditions within a defined, and potentially variable, thermal comfort band; and optimization of the overall energy efficiency of the system using all available on-site energy resources

Hybrid model predictive control of a residential HVAC system with PVT energy generation and PCM thermal storage

This paper describes an experimental investigation into the performance of a Hybrid Model Predictive Control (HMPC) system implemented to control a novel solar-assisted HVAC system servicing the Team UOW Solar Decathlon house, the overall winner of the Solar Decathlon China 2013 competition. This HVAC system consists of an air-based photovoltaic thermal (PVT) collector and a phase change material (PCM) thermal store integrated with a conventional ducted reverse-cycle heat pump system. The system was designed for operation during both winter and summer, using daytime solar radiation and night sky radiative cooling to increase the energy efficiency of the air-conditioning system. The PVT collector can exchange heat with the PCM thermal storage unit, and the stored heat can be used to condition the space or precondition the air entering the air handling unit (AHU). The HMPC controller includes two levels of control, where the high-level controller has a 24-hour prediction horizon and a 1-hour control step is used to select the operating mode of the HVAC system. Low-level controllers for each HVAC operational mode have a 1-hour prediction horizon and a 5-minute control step, and are used to track the trajectory defined by the high-level controller and to optimize the operating mode selected. The results from this preliminary experimental work have demonstrated the value of the HMPC approach in optimally controlling the solar-assisted HVAC system in the Solar Decathlon house. Results show that the HMPC controller successfully selected the appropriate operating mode to achieve multiple objectives, including: maintenance of indoor comfort conditions within a defined, and potentially variable, thermal comfort band; and optimization of the overall energy efficiency of the system using all available on-site energy resources

Impact of inverter-based resources on transmission line relaying -part II: power swing protection

The power swing characteristic of transmission lines (TLs) can be affected by the large-scale integration of inverter-based resources (IBRs), resulting in the maloperation of the legacy power swing blocking (PSB) and out-of-step tripping (OST) functions. This paper presents a brief review of power swing phenomena and the impact on power swing protection functions. In this regard, the impact of IBR integration of type-III, and type-IV wind turbine generation (WTG) on legacy power swing protection functions has been scrutinized. To do so, the performance of impedance-based PSB and OST functions during the IBR integration has been investigated via comprehensive simulation studies. The results show that under a system contingency and high IBR penetration, depending on the IBR technology, the system experiences frequency oscillations and swinging impedance trajectories which are different from those from synchronous generators, such that the reliable operation of the legacy PSB and OST functions can be jeopardized. Moreover, during power swing phenomena, the simulation results have found that the security of distance protection cannot be guaranteed and the fault ride-through requirements cannot be maintained when a high share of IBRs have been integrated

Microgrids of commercial buildings: strategies to manage mode transfer from grid connected to islanded mode

Microgrid systems located within commercial premises are becoming increasingly popular and their dynamic behavior is still uncharted territory in modern power networks. Improved understanding in design and operation is required for the electricity utility and building services design sectors. This paper evaluates the design requirements for a commercial building microgrid system to facilitate seamless mode transition considering an actual commercial building microgrid system. A dynamic simulation model of the proposed microgrid system is established (utilizing DIgSILENT Power Factory) to aid the development of planning and operational philosophy for the practical system. An economic operational criterion is developed for the microgrid to incorporate selective mode transition in different time intervals and demand scenarios. In addition, a multi-droop control strategy has been developed to mitigate voltage and frequency variations during mode transition. Different system conditions considering variability in load and generation are analyzed to examine the responses of associated microgrid network parameters (i.e., voltage and frequency) with the proposed mode transition strategy during planned and unplanned islanding conditions. It has been demonstrated that despite having a rigorous mode transition strategy, control of certain loads such as direct online (DOL) and variable-speed-drive (VSD) driven motor loads is vital for ensuring seamless mode-transition, in particular for unplanned islanding conditions

Identification of Load Power Quality Characteristics using Data Mining

The rapid increase in computer technology and the availability of large scale power quality monitoring data should now motivate distribution network service providers to attempt to extract information that may otherwise remain hidden within the recorded data. Such information may be critical for identification and diagnoses of power quality disturbance problems, prediction of system abnormalities or failure, and alarming of critical system situations. Data mining tools are an obvious candidate for assisting in such analysis of large scale power quality monitoring data. This paper describes a method of applying unsupervised and supervised learning strategies of data mining in power quality data analysis. Firstly underlying classes in harmonic data from medium and low voltage (MV/LV) distribution systems were identified using clustering. Secondly the link analysis is used to merge the obtained clusters into supergroups. The characteristics of these super-groups are discovered using various algorithms for classification techniques. Finally the a priori algorithm of association rules is used to find the correlation between the harmonic currents and voltages at different sites (substation, residential, commercial and industrial) for the interconnected supergroups

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Novel Avian Influenza H7N3 Strain Outbreak, British Columbia

Genome sequences of chicken (low pathogenic avian influenza [LPAI] and highly pathogenic avian influenza [HPAI]) and human isolates from a 2004 outbreak of H7N3 avian influenza in Canada showed a novel insertion in the HA0 cleavage site of the human and HPAI isolate. This insertion likely occurred by recombination between the hemagglutination and matrix genes in the LPAI virus