A review on chemical diagnosis techniques for transformer paper insulation degradation
- Authors: Abu Bakar, Norazhar , Abu Siada, Ahmed , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 2013 Australasian Universities Power Engineering Conference, AUPEC 2013; Hobart, Australia; 29th September-3rd October 2013 p. 1-6
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- Description: Energized parts within power transformer are isolated using paper insulation and are immersed in insulating oil. Hence, transformer oil and paper insulation are essential sources to detect incipient and fast developing power transformer faults. Several chemical diagnoses techniques are developed to examine the condition of paper insulation such as degree of polymerization, carbon oxides, furanic compounds and methanol. The principle and limitation of these diagnoses are discussed and compared in this paper.
Effects of transformer oil properties and contamination on its spectral response
- Authors: Abu Bakar, Norazhar , Abu-Siada, Ahmed , Islam, Syed , El-Naggar, M.
- Date: 2014
- Type: Text , Conference proceedings
- Relation: 2014 International Conference on Condition Monitoring and Diagnosis, CMD 2014; Jeju, Korea; 21st September 2014
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- Description: UV Spectrophotometry is a non-intrusive test that can be employed to determine power transformer’s integrity. Light transmitted through transformer oil sample containing various contaminations is decreased by that fraction being absorbed and is detected as a function of wavelength. This paper investigates the impact of various contaminations and oil properties such as water content, acidity, interfacial tension and average voltage breakdown on the spectral response of the transformer oil. In this regard, various transformer oil samples are collected from in-service transformers and the aforementioned parameters are measured. Same oil samples are scanned with UV-Vis spectroscopic and the spectral responses are obtained and analysed.
Effect of conducting materials on UV-Vis spectral response characteristics
- Authors: Abu Bakar, Norazhar , Abu-Siada, Ahmed , Das, Narottam , Islam, Syed
- Date: 2013
- Type: Text , Journal article
- Relation: Universal Journal of Electrical and Electronic Engineering Vol. 1, no. 3 (2013), p. 81-86
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- Description: Spectroscopic analysis is recently being employed to measure furan concentration in transformer oil. Light absorbance and spectral bandwidth are used as indicators to estimate furan concentration level in transformer oil. However, the possibility of dust and other conducting materials that might exist in transformer oil sample need to be considered as it may influence the spectroscopic performance. In this paper, series of tests are carried out to investigate the impact of dust on the transformer oil spectral response characteristics. Oil sample with various furan concentrations along with certain amount of copper powder are examined. Experimental results show that the spectral response characteristics only affected by dust at the beginning of mix process. However, the characteristic returns to the original one within a few minutes.
A new technique to measure interfacial tension of transformer oil using UV-Vis spectroscopy
- Authors: Abu Bakar, Norazhar , Abu-Siada, Ahmed , Islam, Syed , El-Naggar, Mohammed
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 22, no. 2 (2015), p. 1275-1282
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- Description: Interfacial tension (IFT) and acid numbers of insulating oil are correlated with the number of years that a transformer has been in service and are used as a signal for transformer oil reclamation. Oil sampling for IFT measurement calls for extra precautions due to its high sensitivity to various oil parameters and environmental conditions. The current used technique to measure IFT of transformer oil is relatively expensive, requires an expert to conduct the test and it takes long time since the extraction of oil sample, sending it to external laboratory and getting the results back. This paper introduces a new technique to estimate the IFT of transformer oil using ultraviolet-to-visible (UV-Vis) spectroscopy. UV-Vis spectral response of transformer oil can be measured instantly with relatively cheap equipment, does not need an expert person to conduct the test and has the potential to be implemented online. Results show that there is a good correlation between oil spectral response and its IFT value. Artificial neural network (ANN) approach is proposed to model this correlation.
A review of dissolved gas analysis measurement and interpretation techniques
- Authors: Abu Bakar, Norazhar , Abu-Siada, Ahmed , Islam, Syed
- Date: 2014
- Type: Text , Journal article
- Relation: IEEE Electrical Insulation Magazine Vol. 30, no. 3 (2014), p. 39-49
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- Description: Dissolved gas analysis (DGA) is used to assess the condition of power transformers. It uses the concentrations of various gases dissolved in the transformer oil due to decomposition of the oil and paper insulation. DGA has gained worldwide acceptance as a method for the detection of incipient faults in transformers.
Understanding power transformer frequency response analysis signatures
- Authors: Abu-Siada, Ahmed , Hashemnia, Naser , Islam, Syed , Masoum, Mohammad
- Date: 2013
- Type: Text , Journal article
- Relation: IEEE Electrical Insulation Magazine Vol. 29, no. 3 (2013), p. 48-56
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- Description: This paper presents a comprehensive analysis of the effects of various faults on the FRA signatures of a transformer simulated by a high-frequency model. The faults were simulated through changes in the values of some of the electrical components in the model. It was found that radial displacement of a winding alters the FRA signature over the entire frequency range (10 Hz-1 MHz), whereas changes due to axial displacement occur only at frequencies above 200 kHz. A Table listing various transformer faults and the associated changes in the FRA signature was compiled and could be used in the formulation of standard codes for power transformer FRA signature interpretation.
Image processing-based on-line technique to detect power transformer winding faults
- Authors: Abu-Siada, Ahmed , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 39th Annual Conference of the IEEE Industrial Electronics Society, IECON 2013; Vienna, Austria; 10th-14th November 2013 p. 1-6
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- Description: Frequency Response Analysis (FRA) has been growing in popularity in recent times as a tool to detect mechanical deformation within power transformers. To conduct the test, the transformer has to be taken out of service which may cause interruption to the electricity grid. Moreover, because FRA relies on graphical analysis, it calls for an expert person to analyse the results as so far, there is no standard code for FRA interpretation worldwide. In this paper an online technique is introduced to detect the internal faults within a power transformer by constructing the voltage-current (V-I) locus diagram to provide a current state of the transformer health condition. The technique does not call for any special equipment as it uses the existing metering devices attached to any power transformer to monitor the input voltage, output voltage and the input current at the power frequency and hence online monitoring can be realised. Various types of faults have been simulated to assess its impact on the proposed locus. A Matlab code based on digital image processing is developed to calculate any deviation of the V-I locus with respect to the reference one and to identify the type of fault.
A new fuzzy logic approach for consistent interpretation of dissolved gas-in-oil analysis
- Authors: Abu-Siada, Ahmed , Hmood, Sdood , Islam, Syed
- Date: 2013
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 20, no. 6 (2013), p. 2343-2349
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- Description: Dissolved gas analysis (DGA) of transformer oil is one of the most effective power transformer condition monitoring tools. There are many interpretation techniques for DGA results however all these techniques rely on personnel experience more than analytical formulation. As a result, various interpretation techniques do not necessarily lead to the same conclusion for the same oil sample. Furthermore, significant number of DGA results fall outside the proposed codes of the current based-ratio interpretation techniques and cannot be diagnosed by these methods. Moreover, ratio methods fail to diagnose multiple fault conditions due to the mixing up of produced gases. To overcome these limitations, this paper introduces a new fuzzy logic approach to reduce dependency on expert personnel and to aid in standardizing DGA interpretation techniques. The approach relies on incorporating all existing DGA interpretation techniques into one expert model. DGA results of 2000 oil samples that were collected from different transformers of different rating and different life span are used to establish the model. Traditional DGA interpretation techniques are used to analyze the collected DGA results to evaluate the consistency and accuracy of each interpretation technique. Results of this analysis were then used to develop the proposed fuzzy logic model.
Applications of power electronics in renewable energy systems
- Authors: Abu-Siada, Ahmed , Islam, Syed
- Date: 2023
- Type: Text , Book chapter
- Relation: Power Electronics Handbook Chapter 23 p. 797-843
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- Description: The Kyoto and Paris agreements on global reduction of greenhouse gas emissions have prompted renewed interest in the adoption of clean renewable energy systems worldwide. Many renewable energy technologies have been well developed over the years and become morereliable, and cost-competitive with conventional fuel-based generation. The cost of renewable energy technologies is on a falling trend and is expected to fall further with the increase in demand and production. There are many renewable energy sources (RES) such as biomass, solar, wind, mini-hydro, and tidal power. However, solar and wind energy systems make use of advanced power electronics technologies, and therefore, the focus in this chapter will be on solar photovoltaic and wind power systems. © 2024 Elsevier Inc. All rights reserved.
Improving voltage of remote connection using wind-solar farms equipped with new voltage control strategy based on virtual impedance monitoring enabled by IEC 61850 communication
- Authors: Aghanoori, Navid , Masoum, Mohammad , Islam, Syed , Abu-Siada, Ahmed , Nethery, Steven
- Date: 2019
- Type: Text , Journal article
- Relation: IET Generation, Transmission and Distribution Vol. 13, no. 11 (2019), p. 2112-2122
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- Description: This study explores how the voltage control of a remote part of the utility gird can be improved using more sophisticated voltage control on wind-solar farms equipped with fast communication platforms. The idea is to make renewable plant the master voltage controller during large disturbance events in the grid. This is done by proposing an enhanced voltage droop control strategy based on instantaneous reactive power consumption by monitoring the virtual impedance of the point of connection using a new customised data class model of IEC 61850 communication protocol. The conventional centralised voltage droop control strategy and the proposed instantaneous direct voltage control method are both implemented on the White Rock Solar Wind Farm in NSW, Australia and their performances are compared using both MATLAB Simulink simulations under 5% voltage step disturbances, single-phase-to-ground and three-phase-to-ground faults as well as some tests conducted in the field.
Investigation of microgrid instability caused by time delay
- Authors: Aghanoori, Navid , Masoum, Mohammad , Islam, Syed , Nethery, Steven
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 10th International Conference on Electrical and Electronics Engineering, ELECO 2017; Bursa, Turkey; 29th-2nd December 2017 Vol. 2018, p. 105-110
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- Description: This paper investigates the impact of time delay in the control of a grid-connected microgrid with renewable energy resources. The considered microgrid has a critical load that needs to be powered and protected in the event of grid voltage disturbance while the microgrid maintains connection to the grid. Three case studies are performed considering three different time delays to indicate the advantages of fast communication system in the performance of renewable microgrids. Detailed simulation results illustrate that the proposed communication system using IEC 61850 substation automation standard provides better voltage and current quality to the critical local load with larger phase and gain margins while keeping the microgid connected to main grid.
Enhancement of microgrid operation by considering the cascaded impact of communication delay on system stability and power management
- Authors: Aghanoori, Navid , Masoum, Mohammad , Abu-Siada, Ahmed , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: International Journal of Electrical Power and Energy Systems Vol. 120, no. (2020), p.
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- Description: Power management, system stability and communication structure are three key aspects of microgrids (MGs) that have been explored in many research studies. However, the cascaded effect of communication structure on system stability followed by the impact of stability on the power management has not been fully explored in the literature yet and needs more attention. This paper not only explores this cascaded impact, but also provides a comprehensive platform to optimally consider three layers of MG design and operation from this perspective. For generation cost minimization and stability assessment, the proposed platform uses an adaptive particle swarm optimization (PSO) while a new class of data exchange scheme based on IEC 61850 protocol is proposed to reduce the communication time delays among the inverters of distributed generations and the MG control center. This paper also considers the system stability using small-signal model of a MG in a real-time manner as an embedded function in the PSO. In this context investigations have been conducted by modeling an isolated MG with solar farm, fuel cell generator and micro-turbine in MATLAB Simulink. Detailed simulation results indicate the proposed power and stability management method effectively reduces the MG generation cost through maximizing the utilization of the available renewable generations while considering system stability. © 2020 Elsevier Ltd
Assessing transformer oil quality using deep convolutional networks
- Authors: Alam, Mohammad , Karmakar, Gour , Islam, Syed , Kamruzzaman, Joarder , Chetty, Madhu , Lim, Suryani , Appuhamillage, Gayan , Chattopadhyay, Gopi , Wilcox, Steve , Verheyen, Vincent
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 29th Australasian Universities Power Engineering Conference, AUPEC 2019
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- Description: Electrical power grids comprise a significantly large number of transformers that interconnect power generation, transmission and distribution. These transformers having different MVA ratings are critical assets that require proper maintenance to provide long and uninterrupted electrical service. The mineral oil, an essential component of any transformer, not only provides cooling but also acts as an insulating medium within the transformer. The quality and the key dissolved properties of insulating mineral oil for the transformer are critical with its proper and reliable operation. However, traditional chemical diagnostic methods are expensive and time-consuming. A transformer oil image analysis approach, based on the entropy value of oil, which is inexpensive, effective and quick. However, the inability of entropy to estimate the vital transformer oil properties such as equivalent age, Neutralization Number (NN), dissipation factor (tanδ) and power factor (PF); and many intuitively derived constants usage limit its estimation accuracy. To address this issue, in this paper, we introduce an innovative transformer oil analysis using two deep convolutional learning techniques such as Convolutional Neural Network (ConvNet) and Residual Neural Network (ResNet). These two deep neural networks are chosen for this project as they have superior performance in computer vision. After estimating the equivalent aging year of transformer oil from its image by our proposed method, NN, tanδ and PF are computed using that estimated age. Our deep learning based techniques can accurately predict the transformer oil equivalent age, leading to calculate NN, tanδ and PF more accurately. The root means square error of estimated equivalent age produced by entropy, ConvNet and ResNet based methods are 0.718, 0.122 and 0.065, respectively. ConvNet and ResNet based methods have reduced the error of the oil age estimation by 83% and 91%, respectively compared to that of the entropy method. Our proposed oil image analysis can calculate the equivalent age that is very close to the actual age for all images used in the experiment. © 2019 IEEE.
- Description: E1
Impact of insulating oil degradation on the power transformer frequency response analysis
- Authors: Aljohani, Omar , Abu-Siada, Ahmed , Islam, Syed
- Date: 2015
- Type: Text , Conference proceedings , Conference paper
- Relation: 11th IEEE International Conference on the Properties and Applications of Dielectric Materials, ICPADM 2015; Sydney, Australia; 19th-22nd July 2015 Vol. OCT, p. 396-399
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- Description: Frequency Response Analysis (FRA) has become a reliable tool to detect mechanical deformation within power transformers. Many researchers have investigated the impact of various mechanical winding and core deformations on transformer FRA signature using either simulation analysis or practical testing to establish a standard code for FRA signature interpretation. None of them however, have given attention to the impact of power transformer insulating oil degradation on the transformer FRA signature. This paper investigates the effect of insulating mineral oil degradation on power transformer FRA signature. In this regard, the physical geometrical dimension of a single-phase transformer filled with insulating mineral oil is simulated using three dimensional finite element analysis to emulate the real transformer operation. Transformer FRA signature is measured and analysed with various health conditions of the insulating oil. Results show that, insulating oil degradation has a significant impact on the transformer FRA signature.
Application of digital image processing to diagnose transformer winding deformation using FRA polar plot
- Authors: Aljohani, Omar , Abu-Siada, Ahmed , Islam, Syed
- Date: 2014
- Type: Text , Conference proceedings , Conference paper
- Relation: 2014 International Conference on Condition Monitoring and Diagnosis, CMD 2014; Jeju, Korea; 21st September 2014
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- Description: Digital image processing (DIP) technique has been growing rapidly as an essential tool to interpret various image features for many applications of science and engineering. Condition monitoring and diagnosis are considered the main areas that relay on DIP. Frequency response analysis (FRA) technique has become a popular and reliable diagnostic tool in detecting various winding deformations within power transformers. However, interpretation of FRA signatures still requires high expertise because of its reliance on graphical analysis. This paper presents a new technique for the interpretation of transformers FRA signatures. The proposed technique relies on incorporating both magnitude and angle of the FRA signature in one polar plot, which is manipulated to extract some unique features using DIP techniques. The proposed technique can assess in identifying and quantifying various winding deformation within power transformers. The proposed technique is easy to implement in any frequency response analyser.
An overview of demand response opportunities for commercial and industrial customers in the Australian NEM
- Authors: Amin, B.M. Ruhul , Shah, Rakibuzzaman , Hasan, Kaz , Tayab, Usman , Islam, Syed
- Date: 2022
- Type: Text , Conference paper
- Relation: 14th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2022, Melbourne, 20-23 November 2023, 2022 IEEE PES 14th Asia-Pacific Power and Energy Engineering Conference (APPEEC) Vol. 2022-November
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- Description: Different demand response (DR) mechanisms available in the Australian national electricity market (NEM), such as wholesale, ancillary, emergency, and network DR could provide significant flexibility to maintain and enhance power system security and reliability. Australian Energy Market Operator (AEMO) is continually reviewing global practices working with different states and territories, and revising the legislative and technical requirements for integrating more DR participants into the national electricity market (NEM). Commercial and Industrial (CandI) customers have a higher potential to participate in DR with flexible larger loads and onsite distributed energy resources (DERs). The CandI customers can reduce their energy bills and earn incentives from operators through DR participation. This paper provides a comprehensive review of different types of DR mechanisms that have been used in the Australian NEM. Technical and legislative requirements to participate in DR for CandI customers have been identified and summarised. Furthermore, the challenges for DR participation and potential benefits have been highlighted. Finally, a look-up table is prepared to identify the suitability of CandI customers to participate in one or multiple DR mechanisms potentially. The findings of this paper can be used as a guiding tool for CandI customers to understand technical and legislative requirements for participating in different DR mechanisms in Australia and select the most appropriate DR mechanisms for maximising their benefits. © 2022 IEEE.
Impact of buckling deformation on the FRA signature of power transformer
- Authors: Amini, Arman , Das, Narottam , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 2013 Australasian Universities Power Engineering Conference, AUPEC 2013; Hobart, Australia; 29th September-3rd October 2013 p. 1-4
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- Description: Power transformer is an important asset within the electrical power system network. Frequency Response Analysis (FRA) has been developing in popularity in recent years as a tool to detect mechanical deformation of power transformers winding. Since the FRA has been relying on graphical analysis, it calls for an expert person to analyze the results to detect the type of the fault and its location. There are no reliable guidelines for FRA signature in the event that a failure occurs in service and the impact can be far reaching. The concept of FRA has been successfully used as a diagnostic technique to detect the winding deformation, core and clamping structure for the power transformers. This paper investigated the impact of the forced and free winding buckling based on the variation of the electrical parameters to show how these faults vary the FRA signature.
Fuzzy logic approach in power transformers management and decision making
- Authors: Arshad, Muhammad , Islam, Syed , Khaliq, Abdul
- Date: 2014
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 21, no. 5 (2014), p. 2343-2354
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- Description: The degradation of insulation systems is a complex physical process, many parameters act at the same time thus making the interpretation extremely difficult. The insulation is very much responsive in transformer serving closer to design life. Strategic maintenance and operational procedures are best formulated where the condition of existing unit has been accurately assessed. To facilitate asset management and decision making, asset's condition assessment is vital using reliable, non-intrusive diagnostics and monitoring tools together with expert system. Transformer assessment can be carried out effectively by identifying and integrating its criticalities using fuzzy logic technique. In this research, asset management and decision making model has been developed using diagnostics and data interpretation techniques based on fuzzy logic approach. Enhance reliability could be achieved by integrating real time condition monitoring, maintenance, management activities and cost effective optimization techniques. This model facilitates effectively to address criticalities and allow better planning, maintenance approach as well as to predict the remnant life of the asset within a practical accuracy.
Identification of coherent generators by support vector clustering with an embedding strategy
- Authors: Babaei, Mehdi , Muyeen, S. , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 105420-105431
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- Description: Identification of coherent generators (CGs) is necessary for the area-based monitoring and protection system of a wide area power system. Synchrophasor has enabled smarter monitoring and control measures to be devised; hence, measurement-based methodologies can be implemented in online applications to identify the CGs. This paper presents a new framework for coherency identification that is based on the dynamic coupling of generators. A distance matrix that contains the dissimilarity indices between any pair of generators is constructed from the pairwise dynamic coupling of generators after the post-disturbance data are obtained by phasor measurement units (PMUs). The dataset is embedded in Euclidean space to produce a new dataset with a metric distance between the points, and then the support vector clustering (SVC) technique is applied to the embedded dataset to identify the final clusters of generators. Unlike other clustering methods that need a priori knowledge about the number of clusters or the parameters of clustering, this information is set in an automatic search procedure that results in the optimal number of clusters. The algorithm is verified by time-domain simulations of defined scenarios in 39 bus and 118 bus test systems. Finally, the clustering result of 39 bus systems is validated by cluster validity measures, and a comparative study investigates the efficacy of the proposed algorithm to cluster the generators with an optimal number of clusters and also its computational efficiency compared with other clustering methods.
The Impact of number of partitions on transient stability of intentional controlled islanding
- Authors: Babaei, Mehdi , Muyeen, S. , Islam, Syed
- Date: 2019
- Type: Text , Conference proceedings
- Relation: 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe); Genova, Italy;11-14 June 2019; p. 1-6
- Full Text: false
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- Description: Intentional Controlled Islanding (ICI) is the last protective measure that must be adopted in power systems to prevent forming unstable islands with load-generation imbalance power. If conventional protective schemes fail to save the power system against wide-area blackout, some cutsets are selected to keep the system operating while feeding essential loads. This paper investigates the effect of the number of partitions on the dynamic performance of controlled islanding and proposes a unified algorithm to identify the coherent generators, optimal cutsets, and timing of islanding in online applications. The algorithm provides an islanding solution with minimum power flow disruption while each island contains coherent groups of generators. The concept of Centre of Inertia (COI) referred angles of generators has been used to determine the critical timing of islanding. Different scenarios in NE 39-bus and IEEE 118-bus test systems were simulated in PowerFactory that led to instability in the power system, and then controlled islanding schemes with a different number of partitions were applied to create stable islands. To better demonstrate the shortcomings of the existing clustering techniques, the effect of the number of required islands on transient stability of controlled islanding and the necessity of devising an automatic method to recognise the number of islands is discussed.