Transformer health assessment and techno-economic end of life evaluation

Electrical power systems play a key role in production and services in both the industrial and commercial sectors and significantly affect the private lives of citizens. A major asset of any power delivery system is the transformer. Transformers represent extensive investment in any power delivery system, and because of the notable effect of a transformer outage on system reliability, careful management of this type of asset is critical. In North America, a large proportion of transformers is approaching the end of their life and should be replaced. In many cases, unexpected transformer outages can be catastrophic and cause both direct and indirect costs to be incurred by industrial, commercial, and residential sectors. Direct costs include but are not limited to loss of production, idle facilities and labour, damaged or spoiled product, and damage to equipment. For commercial customers, the effects may include damage to electrical and electronic equipment, and in some cases damage to goods. For residential customers, outages may cause food spoilage or damage to electrical equipment. In addition to direct costs, there are several types of indirect costs may also result, such as accidental injuries, looting, vandalism, legal costs, and increases in insurance rates. The main goal of this research was to assess the health and remaining lifetime of a working transformer. This information plays a very important role in the planning strategies of power delivery systems and in the avoidance of the potentially appalling effects of unexpected transformer outages. This thesis presents two different methods of assessing transformer end of life and three distinct methods of determining the health index and health condition of any working transformer. The first method of assessing transformer end of life is based on the use of Monte Carlo technique to simulate the thermal life of the solid insulation in a transformer, the failure of which is the main reason for transformer breakdown. The method developed uses the monthly average ambient temperature and the monthly solar clearness index along with their associated uncertainties in order to estimate the hourly ambient temperature. The average daily load curve and the associated uncertainties in each hourly load are then used to model the transformer load. The inherent uncertainties in the transformer loading and the ambient temperature are used to generate an artificial history of the life of the transformer, which becomes the basis for appraising its remaining lifetime. The second method of assessing transformer end of life is essentially an economic evaluation of the remaining time to the replacement of the transformer, taking into consideration its technical aspects. This method relies on the fact that a transformer fails more frequently during the wear-out period, thus incurring additional maintenance and repair costs. As well, frequent failures increase during this period also costs related to transformer interruptions. Replacing a transformer before it is physically damaged is therefore a wise decision. The bathtub failure model is used to represent the technical aspects of the transformer for the purposes of making the replacement decision. The uncertainties related to the time-to-failure, time-to-repair, time-to-switch, and scheduled maintenance time are modeled using a Monte Carlo simulation technique, which enables the calculation of the repair costs and the cost of interruptions. The repair, operation, and interruption costs are then used to generate equivalent uniform annual costs (EUACs) for the existing transformer and for a new transformer, a comparison of which enables the determination of the most economical replacement year. The case studies conducted using both methods demonstrate their reliability for determining transformer end of life for assessing the appropriate time for replacement. Diagnostic test data for 90 working transformers were used to develop three methods of estimating the health condition of a transformer, which utilities and industries can use in order to assess the health of their transformer fleet. The first method is based on building a linear relation between all parameters of diagnostic data in order to determine a transformer health index, from which the health condition of the transformer can be evaluated. The second method depends on the use of artificial neural networks (ANN) in order to find the health condition of any individual transformer. The diagnostic data for the 90 working transformers together with the health indices calculated for them by means of a specialized transformer asset management and health assessment lab, were used to train an ANN. After the training, the ANN can estimate a health index for any transformer, which can be used in order to determine the health condition of the transformer. The third method is based on finding a relation between the input data and the given health indices (calculated by the specialized transformer asset management and health assessment lab) using the least squares method. This relation then can be used to find the health index and health condition of any working transformer. The health condition determined based on these methods shows excellent correlation with the given health condition calculated by the specialized transformer asset management and health assessment lab

Multi-terminal Hvdc system with offshore wind farms under anomalous conditions: Stability assessment

Droop control is widely adopted to control Multi-Terminal high-voltage Direct Current (MTDC) systems with offshore wind farms. During permanent faults, the faulty line should be isolated promptly to preserve a high reliability of the MTDC system. This paper examines the MTDC system performance following a faulty line outage. This study aims to identify the outage types that may lead to a complete loss of system voltage stability and the outages that may have a secondary effect on the system. Moreover, strategies for dealing with outages that may lead to a complete shutdown of the system are also presented. Furthermore, the ranges of droop gains' values that can be employed following fault occurrence to preserve system transient stability are studied. Different scenarios are explored during faulty conditions such as surplus and sparsity of wind power, line overcurrent, outage of lines connected to wind farms, and outage of lines connected to AC grids to validate this study.MATLAB/Simulink platform has been employed to elucidate the presented concept.Qatar National Research FundScopu

An ANN-based protection technique for MTDC systems with multiple configurations

A unified protection technique for different configurations of Multi-Terminal high voltage Direct Current (MTDC) systems is presented in this paper. The technique is based on using positive and negative poles’ currents of one end for each line. The spectral energy of two distinct frequency bands captured from fault currents, together with the fault current initial slope, are used to supply a feed forward Artificial Neural Network (ANN) for identifying fault zone and classifying fault type. Different configurations of MTDC systems are used to train and test the proposed ANN including radial system, meshed system without Current Limiting Reactors (CLRs), and meshed system with CLRs. Different fault types, fault locations, fault inception times, and fault resistances are used to train and test the proposed ANN. The proposed algorithm showed an excellent performance in the identification of the fault zone and the classification of the fault type for various MTDC configurations. Moreover, the algorithm does not respond to non- DC fault abnormal conditions

Modern network reconfiguration techniques for service restoration in distribution systems: A step to a smarter grid

This paper presents state of the art reconfiguration techniques used for service restoration in distribution systems under different practical considerations. The different formulations of the problem together with the different solution methods are presented to show the advantages and disadvantages of each formulation and each solution. Other aspects that enhance the solution practicability such as load variations, load priority, cold load pickup, network connectivity representation, and existence of distributed generation are considered with directions for future research to convert current distribution system into an automatic self-healing system, which is the main pillar of the smart grid. The control method and the communication techniques used in the execution of the reconfiguration problem solution are highlighted and the new research directions in each issue are emphasized. The conclusion about the reconfiguration problem the formulation, the solution method, and the guidelines about unexplored research areas in this topic are presented at the end of the paper. � 2018 Faculty of Engineering, Alexandria UniversityScopu

Modern network reconfiguration techniques for service restoration in distribution systems: A step to a smarter grid

This paper presents state of the art reconfiguration techniques used for service restoration in distribution systems under different practical considerations. The different formulations of the problem together with the different solution methods are presented to show the advantages and disadvantages of each formulation and each solution. Other aspects that enhance the solution practicability such as load variations, load priority, cold load pickup, network connectivity representation, and existence of distributed generation are considered with directions for future research to convert current distribution system into an automatic self-healing system, which is the main pillar of the smart grid. The control method and the communication techniques used in the execution of the reconfiguration problem solution are highlighted and the new research directions in each issue are emphasized. The conclusion about the reconfiguration problem the formulation, the solution method, and the guidelines about unexplored research areas in this topic are presented at the end of the paper. Keywords: Distributed generation, IEC 61850, Network reconfiguration, Restoration, Smart gri

A New Six-Phase FSCW Layout for Permanent Magnet Synchronous Wind Generators

This paper proposes a new non-overlapped six-phase Fractional Slot Concentrated Winding (FSCW) layout for a Permanent Magnet (PM) synchronous wind generator with an outer rotor and surface mounted magnets. The proposed FSCW layout is originally an asymmetrical nine-phase winding where the nine phases are connected with a special connection as to provide an equivalent stator winding with six terminals only. The proposed winding successfully offers a high torque and voltage qualities with a low cogging torque. Besides, the stator and rotor core losses are reduced when compared with a three-phase counterpart. Finally, the high phase order of the proposed generator provides a better fault tolerant generator design. A 100kW PM generator with an outer rotor based on the proposed winding layout is designed and simulated using 2D Finite Element Analysis (FEA).Scopu

A directional protection technique for MTDC networks

This paper suggests a new protection algorithm for a multi-terminal direct current (MTDC) networks. The current values and directions at each bus connecting more than one line are determined. The measured values of line currents are used to detect faulty conditions based on a specific threshold value. The faulted line is identified using the current direction through each line during a fault. For lines linking buses that connect multiple lines, simple communication system is required between the ends of these lines to identify an internal fault. The communication time is compensated due to the fast decision. Communication between buses is not required during normal conditions; therefore, the communication task is simplified. Simulation results show that the proposed algorithm is effective in protection of MTDC.Scopu