Demand response for residential appliances via Customer Reward Scheme

This paper proposes a reward based demand response algorithm for residential customers to shave network peaks. Customer survey information is used to calculate various criteria indices reflecting their priority and flexibility. Criteria indices and sensitivity based house ranking is used for appropriate load selection in the feeder for demand response. Customer Rewards (CR) are paid based on load shift and voltage improvement due to load adjustment. The proposed algorithm can be deployed in residential distribution networks using a two-level hierarchical control scheme. Realistic residential load model consisting of non-controllable and controllable appliances is considered in this study. The effectiveness of the proposed demand response scheme on the annual load growth of the feeder is also investigated. Simulation results show that reduced peak demand, improved network voltage performance, and customer satisfaction can be achieved.

InsulLiving house post-occupancy energy performance report

This research was commissioned by Metecno Pty Ltd, trading as Bondor®. The InsulLiving house was designed and constructed by Bondor®. The house instrumentation (electricity circuits, indoor environment, weather station) was provided by Bondor and supplied and installed by independent contractors. This report contains analysis of data collected from the InsulLiving house at Burpengary during 1 year of occupancy by a family of four for the period 1 April 2012 – 31 March 2013. The data shows a daily average electricity consumption 48% less than the regional average. The analysis confirms that the 9 star house performed thermally slightly better than the simulated performance. The home was 'near zero energy', with its modest 2.1kW solar power system meeting all of the needs for space heating and cooling, lighting and most water heating.

An extensible framework for analysing resource behaviour using event logs

Business processes depend on human resources and managers must regularly evaluate the performance of their employees based on a number of measures, some of which are subjective in nature. As modern organisations use information systems to automate their business processes and record information about processes’ executions in event logs, it now becomes possible to get objective information about resource behaviours by analysing data recorded in event logs. We present an extensible framework for extracting knowledge from event logs about the behaviour of a human resource and for analysing the dynamics of this behaviour over time. The framework is fully automated and implements a predefined set of behavioural indicators for human resources. It also provides a means for organisations to define their own behavioural indicators, using the conventional Structured Query Language, and a means to analyse the dynamics of these indicators. The framework's applicability is demonstrated using an event log from a German bank.

Generating natural language texts from business process models

Process Modeling is a widely used concept for understanding, documenting and also redesigning the operations of organizations. The validation and usage of process models is however affected by the fact that only business analysts fully understand them in detail. This is in particular a problem because they are typically not domain experts. In this paper, we investigate in how far the concept of verbalization can be adapted from object-role modeling to process models. To this end, we define an approach which automatically transforms BPMN process models into natural language texts and combines different techniques from linguistics and graph decomposition in a flexible and accurate manner. The evaluation of the technique is based on a prototypical implementation and involves a test set of 53 BPMN process models showing that natural language texts can be generated in a reliable fashion.

Process compliance measurement based on behavioural profiles

Process compliance measurement is getting increasing attention in companies due to stricter legal requirements and market pressure for operational excellence. On the other hand, the metrics to quantify process compliance have only been defined recently. A major criticism points to the fact that existing measures appear to be unintuitive. In this paper, we trace back this problem to a more foundational question: which notion of behavioural equivalence is appropriate for discussing compliance? We present a quantification approach based on behavioural profiles, which is a process abstraction mechanism. Behavioural profiles can be regarded as weaker than existing equivalence notions like trace equivalence, and they can be calculated efficiently. As a validation, we present a respective implementation that measures compliance of logs against a normative process model. This implementation is being evaluated in a case study with an international service provider.

Numerical investigation of mechanical and thermal dynamic properties of the industrial transformer

Industrial transformer is one of the most critical assets in the power and heavy industry. Failures of transformers can cause enormous losses. The poor joints of the electrical circuit on transformers can cause overheating and results in stress concentration on the structure which is the major cause of catastrophic failure. Few researches have been focused on the mechanical properties of industrial transformers under overheating thermal conditions. In this paper, both mechanical and thermal properties of industrial transformers are jointly investigated using Finite Element Analysis (FEA). Dynamic response analysis is conducted on a modified transformer FEA model, and the computational results are compared with experimental results from literature to validate this simulation model. Based on the FEA model, thermal stress is calculated under different temperature conditions. These analysis results can provide insights to the understanding of the failure of transformers due to overheating, therefore are significant to assess winding fault, especially to the manufacturing and maintenance of large transformers.

Moving from outsider to insider : peer status and partnerships between electricity utilities and residential consumers

An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008. By 2011, both the peak demand and grid supplied electricity consumption had decreased to below pre-intervention levels. This case study research explored the relationship developed between the utility, community and individual consumer from the residential customer perspective through qualitative research of 22 residential households. It is proposed that an energy utility can be highly successful at peak demand reduction by becoming a community member and a peer to residential consumers and developing the necessary trust, access, influence and partnership required to create the responsive environment to change. A peer-community approach could provide policymakers with a pathway for implementing pro-environmental behaviour for low carbon communities, as well as peak demand reduction, thereby addressing government emission targets while limiting the cost of living increases from infrastructure expenditure.

Dispersion of corona ions downwind from a high-voltage power line

Corona discharge is responsible for the small ions found near overhead power lines, and these are capable of modifying the ambient electrical environment such as the dc electric field at ground level (Fews, Wilding et al. 2002). Once produced, small ions quickly attach to aerosol particles in the air, producing ‘large ions’ which are roughly 1 nm to 1 µm in diameter. However, very few studies have reported measurements of ions produced by power lines and its impact on particle charge concentrations. In this present study, the measurements were conducted as a function of normal downwind distance from a 275kV power line for investigating the effect of corona ions on air ions, aerosol particle charge concentration and dc e-filed.

Investigation of corona sources in high voltage power lines

This paper describes the results of experiments made in the vicinity of EHV overhead lines to investigate sources of clouds of charged particles using simultaneously-recording arrays of electric field meters to measure direct electric fields produced under ion clouds. E-field measurements, made at one metre above ground level, are correlated with wind speed and direction, and with measurements from ionisation counters and audible corona effects to identify possible positions of sources of corona on adjacent power lines. Measurements made in dry conditions on EHV lines in flat remote locations with no adjacent buildings or large vegetation indicate the presence of discrete ion sources associated with high stress points on some types of line hardware such as connectors and conductor spacers. Faulty line components such as insulators and line fittings are also found to be a possible source of ion clouds.

Air ion concentrations under overhead power lines

Corona discharge is responsible for the flux of small ions from overhead power lines, and is capable of modifying the ambient electrical environment, such as the air ion concentrations at ground level. Once produced, small ions quickly attach to aerosol particles in the air, producing ‘large ions’, approximately 1 nm to 1 µm in diameter. However, very few studies have measured air ion concentrations directly near high voltage transmission lines. The present study involved the simultaneously measurement of small ion concentration and net large ion concentration using air ion counters and an aerosol electrometer at four power line sites. Both positive and negative small ion concentration (<1.6nm), net large ion concentration (2nm-5μm) and particle number concentration (10nm-2μm) were measured using air ion counters and an aerosol electrometer at four power line sites. Measurements at sites 1 and 2 were conducted at both upwind and downwind sides. The results showed that total ion concentrations on the downwind side were 3-5 times higher than on the upwind side, while particle number concentrations did not show a significant difference. This result also shows that a large number of ions were emitted from the power lines at sites 1 and 2. Furthermore, both positive and negative ions were observed at different power line sites. Dominant positive ions were observed at site 1, with a concentration of 4.4 x 103 ions cm-3, which was 10 times higher than on the upwind side. Contrary to site 1, sites 2 to 4 showed negative ion emissions, with concentrations of -1.2 x 103, -460 and -410 ions cm-3, respectively. These values were higher than the background urban negative ion concentration of 400 cm-3. At site 1 and site 2, the net ion concentration and net particle charge concentration on downwind side of the lines showed same polarities. Further investigations were also conducted into the correlation between net ion concentration and net charge particle concentration 20 m downwind of the power lines at site 2. The two parameters showed a correlation coefficient of 0.72, indicating that a substantial number of ions could attach to particles and affect the particle charge status within a short distance from the source.

Charged particles produced by corona emission from an overhead high voltage powerline

High voltage powerlines may give rise to corona breakdown, resulting in the release of large concentrations of charged ions into the surrounding environment. These ions quickly attach to aerosols and the resulting charged particles are carried by prevalent winds. This paper describes a study carried out at a site near an overhead double circuit ac transmission voltage powerline to investigate factors that control the rate at which charged particles are produced, and to determine the total particle number concentrations, total particle charge concentrations and vertical dc electric fields in the proximity of the line. Measured mean values of these three parameters at a perpendicular distance of 50m from the line were 1.8 x 103 particle cm-3, 518 ions cm3 and 520 V m-1 respectively. The net electric charge was positive and the electric field was directed downwards. These parameters were correlated with each other and monitored at four different distances from the line. Effects of meteorological parameters such as wind speed and wind direction were also investigated.

The influence of atmospheric conditions on the leakage current of ceramic insulators on the Colombian Caribbean coast

The contamination of electrical insulators is one of the major contributors to the risk of operation outages in electrical substations, especially in coastal zones with high salinity levels and atmospheric pollution. By using the measurement of leakage-currents, which is one of the main indicators of contamination in insulators, this work seeks to the determine the correlation with climatic variables, such as ambient temperature, relative humidity, solar irradiance, atmospheric pressure, and wind speed and direction. The results obtained provide an input to the behaviour of the leakage current under atmospheric conditions that are particular to the Caribbean coast of Colombia. Spearman’s rank correlation coefficients and principal component analysis are utilised to determine the significant relationships among the different variables under consideration. The necessary information for the study was obtained via historical databases of both atmospheric variables and the leakage current measured in over a period of one year in a 220-kV potential transformer insulator. We identified the influencing factors of temperature, humidity, radiation, wind speed and direction on the magnitude of the leakage current as the most relevant.

A review selection method using product feature taxonomy

As of today, online reviews have become more and more important in decision making process. In recent years, the problem of identifying useful reviews for users has attracted significant attentions. For instance, in order to select reviews that focus on a particular feature, researchers proposed a method which extracts all associated words of this feature as the relevant information to evaluate and find appropriate reviews. However, the extraction of associated words is not that accurate due to the noise in free review text, and this affects the overall performance negatively. In this paper, we propose a method to select reviews according to a given feature by using a review model generated based upon a domain ontology called product feature taxonomy. The proposed review model provides relevant information about the hierarchical relationships of the features in the review which captures the review characteristics accurately. Our experiment results based on real world review dataset show that our approach is able to improve the review selection performance according to the given criteria effectively.

Graphene-based supercapacitor with carbon nanotube film as highly efficient current collector

Flexible graphene-based thin film supercapacitors were made using carbon nanotube (CNT) films as current collectors and graphene films as electrodes. The graphene sheets were produced by simple electrochemical exfoliation, while the graphene films with controlled thickness were prepared by vacuum filtration. The solid-state supercapacitor was made by using two graphene/CNT films on plastic substrates to sandwich a thin layer of gelled electrolyte. We found that the thin graphene film with thickness <1 μm can greatly increase the capacitance. Using only CNT films as electrodes, the device exhibited a capacitance as low as ~0.4 mF cm−2, whereas by adding a 360 nm thick graphene film to the CNT electrodes led to a ~4.3 mF cm−2 capacitance. We experimentally demonstrated that the conductive CNT film is equivalent to gold as a current collector while it provides a stronger binding force to the graphene film. Combining the high capacitance of the thin graphene film and the high conductivity of the CNT film, our devices exhibited high energy density (8–14 Wh kg−1) and power density (250–450 kW kg−1).

Design of a nonlinear excitation controller using inverse filtering for transient stability enhancement

This paper proposes a nonlinear excitation controller to improve transient stability, oscillation damping and voltage regulation of the power system. The energy function of the predicted system states is used to obtain the desired flux for the next time step, which in turn is used to obtain a supplementary control input using an inverse filtering method. The inverse filtering technique enables the system to provide an additional input for the excitation system, which forces the system to track the desired flux. Synchronous generator flux saturation model is used in this paper. A single machine infinite bus (SMIB) test system is used to demonstrate the efficacy of the proposed control method using time-domain simulations. The robustness of the controller is assessed under different operating conditions.