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This article, presents a robust single-phase phase-locked loop (PLL)-less frequency, phase and amplitude estimation technique. The proposed scheme, unlike PLL approaches, does not require a rigorous design and tuning process in order to attain a better stability margin. It is important to note that, an improved discrete time oscillator is obtained by involving a comb filter, which helps improve the DC-offset rejection capability and transient response time. Moreover, the notch filter-like behavior and the introduction of imaginary zeros ensure better harmonic removal ability when compared to a known non-adaptive discrete time oscillator. The proposed scheme relies on an open-loop frequency estimation technique that does not involve an inverse trigonometric function for the estimation of fundamental frequency deviation. The feedback-less architecture of the scheme and the avoidance of inverse trigonometric function, therefore, assist in reducing the real-time implementation complexity. However, under off-nominal grid frequency deviations, the amplitude and the phase of the output of the pre-filter will suffer from errors. These errors are compensated by employing a mathematical regression approach. The results are experimentally validated and compared in order to prove the robustness and usefulness of the proposed scheme for single-phase applications.

This paper shows a proposal for a non-adaptive pre-filter based three-phase type-I synchronous reference frame-based phase locked-loop (PLL) algorithm. This solution is simpler than the widely accepted type-II PLL algorithms, which require a great deal of effort as regards tuning the proportional-integral gains. In the proposed approach, a type-I controller that is merely a proportional gain with a fixed magnitude is employed. Moreover, improvements are made to the implementation of the non-adaptive demodulation based pre-filtering approach, which consist of moving average filters and delayed signal cancellation operators. In the event of a fault, the improved pre-filter structure is still incapable of rejecting the fundamental negative sequence (FNS) component. We propose to overcome this issue by using a non-adaptive computationally simplified structure to improve the immunity to the adverse effects of FNS. It is consequently possible to avoid the dependence on the frequency feedback loop while involving a simple and fast feed-forward error compensation approach. Finally, the performance of the proposed PLL is experimentally verified using a real time controller to demonstrate its feasibility for grid synchronisation applications.

This letter reports a digital signal processing based frequency estimation technique that relies on the storage of fundamental three-phase grid voltage samples. Unlike phase-locked loop algorithms, the proposed algorithm does not require the phase error information when estimating the grid frequency. Moreover, only four consecutive samples of the fundamental orthogonal components are required in order to estimate the deviation in the grid frequency. The proposed scheme is facilitated with an inherent nonadaptive comb filtering behavior in order to reject the dc offset and harmonics while attaining a good immunity to voltage sag and the fundamental negative sequence component. Additionally, the off-nominal harmonic rejection capability of the proposed frequency estimator is enhanced by using a postfiltering method. The experimental validations reported in this study demonstrate that the proposed frequency estimator is suitable for three-phase grid applications.

Global solar radiation is variable in nature, hence its forecasting is very important. This paper aims to predict the global solar radiations using real experimental data collected over time by dev...

This article proposes a robust Lyapunov’s demodulator (LD) based on an orthogonal signal generation (OSG) approach for single-/three-phase applications. The LD is not normally capable of rejecting the dc-offset in the grid signal, and an additional estimation loop is, therefore, required, which may affect the dynamic performance. Nevertheless, an application of a harmonically polluted grid voltage signal to the LD may severely affect the steady-state performance of the parameters estimated. These issues are addressed by proposing an enhanced LD-based-OSG in which a moving average filter is incorporated into the LD-OSG structure. The rapid rejection of dc-offset and harmonics is, therefore, easily achieved without any additional loop. The proposed structure can accurately estimate the fundamental in-phase and quadrature components. However, these orthogonal components may suffer from amplitude imbalance and errors in the phase information under off-nominal frequency conditions. Nevertheless, the errors in the amplitude and the phase information are eliminated using an open-loop frequency deviation detector and a feed-forward curve-fitting approach. The dynamic performance of the proposed scheme has been validated by means of numerical and hardware studies whose results show that, with the less sensitivity toward the phase angle jump and good immunity to the fundamental negative sequence, the proposed scheme is a potential technique with which to synchronize single-/three-phase grid-connected power electronic equipment.

In this Letter, a demodulation based pre-filtering technique is proposed for fast detection of the single-phase grid variables. The estimation of grid voltage parameters is achieved through a Type-I synchronous reference frame phase-locked loop (PLL). The modified bandpass filter in the pre-filtering stage ensure a better rejection of the DC-offset and harmonics. Thus, the grid variables are estimated rapidly with the help of a simple proportional controller. Consequently, in-loop filtering burden and the effort required to tune the PLL is minimal. However, steady errors are witnessed in the fundamental amplitude and the phase information which are mitigated by a curve fitting technique. Importantly, the proposed PLL scheme has improved the dynamic performance under off-nominal frequency conditions with immunity against grid disturbances. The robustness of the proposed algorithm is experimentally verified vis-a-vis existing literature.

Dissolved gas analysis (DGA) is among the most essential techniques for diagnosis of incipient faults in power transformers. Here, a novel graphical DGA technique is proposed in which fault zones are distinguished based on certainty of prediction. The Duval Pentagon 1 and gas ratio combination methods are two most recent techniques with high prediction accuracy. In the Duval Pentagon 1, the rigidly separated distinct fault zones reduce the flexibility of analysis because the fault distributions themselves are not that strictly separated. This also prevents the full utilisation of the information available from the distribution patterns of the graphical representation. This problem has been addressed by overlapping individual fault zones and overlapping them using a multi-layer perceptron (MLP) network with fuzzy class boundaries. Then, in the regions, where multiple fault zones overlap, a modified gas ratio combination method is applied. Finally, a fuzzy decision-making system is developed for predicting the fault using information from both graphical distribution and gas ratios. The combined accuracy of the regions of certainty has been found exceptionally high (98.36%) compared to the regions of uncertainty (58.97%), whereas the overall prediction accuracy of the proposed technique is found comparatively higher (83%) than both the existing methods.

Physical degradation assessment of solid insulation in transformers is a challenge to the condition monitoring engineers. Solid insulation degradation in transformer is accessed indirectly by characterizing insulation oil. The present article describes application of dilatometry and X-ray diffraction (XRD) analysis as direct methods to characterize the degradation of transformer solid insulation. Experimental aging on oil/paper insulation has been simulated in laboratory conditions at elevated temperatures. Thermal expansion and shrinkage behavior of cellulose pressboards aged in mineral oil, synthetic ester, and mixed oil have been reported using dilatometry analysis. Measurement of change in cellulose crystal size and relative crystallinity of cellulose kraft papers have been reported using XRD analysis. The detailed procedure and interpretation of the dilatometry and diffractograph signatures for accessing the degradation of solid insulation are explicitly discussed. It is inferred that, dilatometry and XRD analysis provide a direct physical degradation assessment of transformer solid insulation.

In the present world, energy consumption is increasing day by day, and the primary source of energy is fossil-based resources, which will dwindle shortly. A new concept called “Energy Internet” (EI) has recently been introduced to deal with these challenges. The EI vision tends to overcome some critical problems, such as improving sustainable and eco-friendly energy sources, new models for hybrid energy sources, more secure and effective energy management, and control systems. Wired and wireless communication technologies, such as ZigBee, WiMAX, cognitive radio, cellular communications, and the software-defined network (SDN), which are managed via the network system, are applied in the EI system to carry out monitoring, controlling, and management transactions in real time.One of the most recent communication technologies is the Internet of Things (IoT) that has provided the development of numerous different communication protocols. The IoT can be exploited to ensure communication between devices employing dissimilar data types. Moreover, in order to present a communication platform in both machine-to-machine (M2M) and human-to-machine (H2M) environments, IoT technologies utilize several communication mediums, protocols, and layer architectures. Charging demands differ among different types of electric vehicles and are influenced by the charging location. Random variables, such as technical characteristics and drive patterns, are taken into account to estimate the electric vehicles’ charging demand over time. The optimal location of charging stations also plays a critical role. The time-of-use (ToU) price is applied to influence the charging behavior of electric vehicles (EV) owners so that the charging demand can be reduced during peak hours and shifted to the off-peak hours. Due to ToU, the overall power load can be cut down.The chapter begins with a brief overview of the process of power delivery from generation site to load center, the role of demand side management and the challenges and opportunities provided by electric vehicles to the grid. Subsequently, the fundamentals of electric vehicles have been discussed along with an extensive coverage of various practices associated with information sharing and energy management in plug-in hybrid electric vehicles using vehicle-to-grid technology. The Internet of Energy is also discussed along with the process of information flow and the various communication technologies. Lastly, a hypothetical analysis is shown to reflect the impact of exchange of information and energy between the vehicle and the grid is discussed for a city with significant number of electric vehicles.

In this article, a robust three-phase grid synchronization technique has been proposed for rapid detection of fundamental frequency, phase, and amplitude. The widely accepted phase locked-loop (PLL) algorithms possess complex architectures and require tedious tuning process for attaining a good stability margin. In order to surpass the shortfalls of PLL algorithms, a computationally efficient, stable, and open-loop scheme has been reported in this article. A novel two consecutive samples based frequency estimator is developed for fast detection of the fundamental frequency. Moreover, an efficient hybrid prefiltering approach is implemented based on the demodulation of the grid voltage signal. Additionally, the combination of a delayed signal cancellation operator and a band-pass filter allowed rapid rejection of dc-offset and harmonics, respectively. In the event of a grid voltage imbalance, the instantaneous symmetrical component method is a rescuer for the rejection of the fundamental negative sequence component without any delay. Subsequently, overall transient response time of the scheme is observed to be improved. On the other hand, the fundamental positive sequence component facilitates the estimation of amplitude and phase angle information. Importantly, the dynamic performance of the proposed scheme has been experimentally validated in presence of various grid disturbances.

This article proposes a robust and enhanced three-phase fundamental frequency estimation algorithm for the electric aircraft grid. Unlike conventional frequency-locked loops, the digital signal processing technique-based frequency estimator proposed relies on the storage of five consecutive samples of the fundamental grid voltage signal. Furthermore, the ability to successfully operate at a low sampling frequency, i.e. 8 kHz, makes it sufficiently attractive as regards reducing the memory storage in a low-cost real-time controller. The proposed frequency estimator can additionally eliminate the negative effects of the DC-offset and the fundamental negative sequence components present in the grid signal without any additional effort. Also, the tuning efforts are reduced for the frequency variation range of 350–900 Hz owing to the existence of a single tuning gain parameter. The proposed algorithm has also been found to have a fast dynamic response, which has been experimentally validated through the use of a real-time digital controller.

In this paper, a procedural analysis involved in the optimal design of the photovoltaic system (PV) is thoroughly described.The study has been carried out by following a proposed design procedure, involving different types of photovoltaic panelsand their tracking mechanisms. The proposed methodology is implemented in the twin districts of jammu & kashmir unionterritory (rajouri & poonch). The feasibility of the photovoltaic system has been made based on power output and the costof generation. A detailed financial analysis is also carried out to find the levelised cost of electricity, amortisation time, andinternal rate of return. This study will help the power utilities to mitigate their energy issues, by installing a photovoltaicsystem based on the proposed design methodology.

Transformers are strikingly reliable power transfer devices and are of preeminent importance in the seamless operation of electric arc furnaces. An arc furnace transformer is at a monophonic risk of failure due to the action of different stresses. Reliability is a decisive performance index to ensure that a component will perform the desired function at the coveted time. In this research, beginning with the development of a combined fault tree for arc furnace transformers, a straightforward and conceivable software model is developed to assess reliability. The model incorporates MATLAB Simulink and Fuzzy toolbox for reliability computation and assigning a fuzzified reliability level. Subsequently, reliability indices like availability, unavailability, etc. are computed. Finally, the model is implemented for electric arc furnace transformers installed in different locations of India. This research will be helpful for utilities and researchers associated with enhancing the reliability and availability of the transformer.

In this paper, the application of artificial intelligent techniques on condition monitoring and diagnosis of power transformer has been reported. Enormous technological innovations have been reported by researchers to quantify the health assessment methodologies for in-service power transformers such as Artificial Neural Network, Fuzzy logic, Clustering techniques, and Expert systems for precise diagnostics and prognostics tasks. Albeit, numerous reports, and studies, prediction of accurate health status of an in-service power apparatus like transformer is still a challenge. An effort has been made in this paper to compile the outcome of various research tools with practical in-service data to get an overall status of existing technological breakthroughs in the emerging field of condition monitoring of transformer for the benefit of utilities and researchers. The prospective of condition monitoring and diagnosis technologies of a power transformer can be emulated for asset management and prevent catastrophic failures of power transformers.

Electric arc furnace transformers are of prime importance in steel mill transformers that are designed inherently to supply high magnitude currents. Traditional maintenance strategy for steel mill transformers involves performing an offline diagnostic test and computing health index and remnant life using mathematical aggregations. Stresses in a transformer can be due to an individual or multiple factors which may lead to its deterioration. In order to avoid premature failure, computation of health index and remnant life by online monitoring of arc furnace transformers is imperative. Based on the optimum selection of single and multi-parameter sensors, an architecture for online monitoring is discussed in this paper. Subsequently, dedicated fuzzy models for computation of criticalities of various components, the overall health index, and remnant life are developed in this research. Also, the decision logic is established to identify faulty components based on information collected by online sensors. Weighted fuzzy rules and color code for health indication are some of the additives which enhance the significance of the model. This research will be helpful for maintenance engineers and researchers involved with the maintenance and overhaul of furnace transformers.

Failure mode and effects analysis is a compelling tool for boosting the reliability of a power system network. In this paper, a maintenance strategy is proposed based on the prioritization of maintenance work as per the fuzzy values of risk priority number. The fuzzified approach for the computation of risk assessment uproots the paradoxical behavior of the traditional approach under certain circumstances. Failure modes of each component of a transformer are identified and then occurrence, severity, and detection ratings are assigned for the development of a fuzzy inference system. Based on the input data set, the output surface plots for various parameters are plotted which is subsequently used for maintenance prioritization and suggesting recommended actions. Particular attention is given to the comparison between risk priority number values before and after maintenance or overhaul is performed. This paper will be helpful for researchers and utilities working on the development of optimum maintenance plans for any transformer.

Forecasting of intermittent power produced due to renewable energy resources is highly desirable to accurately determine its future values to be utilized for various purposes like scheduling, contingency solutions by the grid operators. Among the renewable resources, solar energy is the most widely used that has grown leaps and bounds over the past due to technology advancements and it is anticipated that it is going to dominate the future as well. This power is often used independently or integrated into the grid. Such integration of solar generation is demanding the reliable forecast of the same. Clearness index determination is very important for accurately forecasting the solar power. This paper presents a methodology to determine the clearness index values which is of paramount importance to handle the forecasting issue to provide better forecast of the Photovoltaic (PV) power. This method includes finding out the clearness index by estimating the Extra-terrestrial Radiations at a given location and using the Global Solar radiation past data available at a given site. This methodology has been implemented successfully for district Rajouri of Jammu & Kashmir state and clearness index values have been estimated for the same. Moreover the correlation between Extra-terrestrial radiation and the Global solar radiation from the past data for the chosen site was found around 0.95 which is quite high.

This paper encompasses experimental investigations carried out on two different properties like electrical and mechanical properties of Nomex paper insulations immersed in ester oil (rapeseed-based) by adopting accelerated thermally aged process. For sake of comparison, two different types of paper insulation (Nomex paper and Kraft insulation paper) of 5mil thick each have been used. Experimental testing like tan δ test and Tensile strength test were performed for time interval of 48, 72 & 96 h respectively to undergo impact of ageing due to thermal stresses. Test results acquired from electrical and mechanical tests at 120 °C & 150 °C considering thermally aged procedure has been analyzed and presented in this paper to highlight efficacy of such solid insulations for possible futuristic use in modern transformers.

Primarily, any electrical system is an assemblage of various electrical components which are interconnected in a specified manner to perform a specialized function. An electric system can be as simple as a torch on one hand and it can be as abstruse as a spacecraft, on the other. Detailed coverage of all these electrical systems is beyond the purview of this book and hence, a pragmatic review has been made to put together developments related to monitoring techniques of electrical power transmission systems here. This system performs a distinguishing role of ensuring reliable power supply for the utilization by consumers for various applications. The preponderance of faults can be minimized by monitoring certain critical parameters and predicting a fault before it is going to actually happen. In this chapter, an electric power transmission system is branched into Power Transformers, Transmission Lines, Power Transmission Towers and Protective Relays. The primarily focus has been laid to highlight perspective view on the techniques which assist in the development of health prognosis-based (or condition-based) maintenance tools and practices to safeguard the health of these systems in large interest of utilities.

Study of alternate fluids for transformer and their combination with traditional ones is an interesting area of research. The intent of this work is to investigate the thermal ageing performance of ester oils (synthetic and natural), and mixed oil vis-a-vis mineral oil. All the samples were thermally stressed at 110, 140, 160, and 185°C for 2 weeks each. Dissolved decay contents in oil and linear thermal expansion coefficients of solid insulation have been studied using ultraviolet visible infrared spectroscopy and dilatometry analysis, respectively, as per ASTM standards. Change in functional groups of the insulation oils with ageing have been understood by Fourier transform infrared spectroscopy analysis. Additionally, diffusion of oil-moisture mixture into paper with ageing and the corresponding effect on dielectric strength of paper has been also examined using ASTM standards. It is observed that the use of synthetic ester (SE) and addition of SE to mineral insulating oil lead to improved performance of oil-paper insulation system with retarding the rate of degradation of the insulation system.

This article proposes a robust open-loop frequency estimation method for a single-phase system in the presence of grid disturbances. An even harmonic generation scheme is formulated which enables to introduce the benefits of half-cycle delay orthogonal filters. In the proposed work, a digital signal processing approach is employed for fundamental frequency estimation. In order to reject grid disturbances sliding discrete Fourier transform (SDFT) filter (which acts as an orthogonal filter) and moving average filters (MAFs) are employed into the scheme. Finally, rigorous simulation test cases are carried out in MATLAB/Simulink environment in order to prove the robustness of the algorithm.

Transformers are lavish machines installed in a power system that is inherently designed to have high efficiency and reliability. But transformers contain inflammable oil in the vicinity of high voltage elements, which if mishandled, may result in transformer failures and catastrophic explosions. Thus, to enhance the safety and reliability of a transformer, its health assessment is imperative. For this purpose, Health index is an apt indicator. But traditional health index computational techniques have certain limitations which are surmounted using the approach mentioned in this research paper. The computational algorithm used to develop a fuzzy model in this paper eliminates need of a diagnostic expert and have the capability to assess arbitrarily complex diagnostic test results. A decision logic is established to select the non-routine diagnostic tests to be performed by assessing routine test results. Particular attention is given to take into account the effect of factors like operation and maintenance history, expected life, etc. for computation of health index. This paper will be helpful for researchers and electrical utilities involved with health assessment and optimum maintenance of transformers.

Phase-locked loops (PLLs) are often deployed in a specialized control unit of grid-connected converters (GCCs) for their control and protection purposes. Moreover, presence of DC-offset, fundamental negative sequence (FNS) component, and harmonics in the grid signal may hinder the dynamic performance of the PLLs. In this paper, a robust three-phase synchronous reference frame (SRF)–PLL algorithm has been presented. The proposed algorithm will be helpful for rapid tracking of fundamental grid voltage attributes with those including amplitude, phase, and frequency. This is achieved by employing a delayed signal cancellation (DSC) operator cascaded to a modified moving average filter based orthogonal signal generator (MAF–OSG) in the pre-filtering stage. This combination of filters improves the transient response time and demonstrate the potential performance of the scheme if fundamental positive sequence (FPS) component alone is present in the input signal. Also, an instantaneous symmetrical component method is applied to obtain FPS component which facilitates ease tuning of loop parameters. The proposed scheme is tested for nominal and off-nominal frequency conditions in MATLAB/Simulink environment.

This study reports experimental study of cellulose performance in mixture of mineral and synthetic ester (SE) oils. Solid insulation impregnated with mineral oil (MO) and mixture oil has been subjected to accelerated thermal stresses to understand the deterioration rate of cellulose. Diffusion of oil-moisture mixture into paper and corresponding variation in dielectric strength of paper has been examined. Compatibility of solid insulation with MO and mixture oil is analysed by thermal expansion coefficients, X-ray diffraction analysis and dissolved decay products. Furthermore, chemical functional groups present in aged oils are identified by Fourier transform infrared spectroscopy analysis. It is observed that the performance of cellulose insulation is improved with addition of SE to MO. This is achieved by higher water solubility of esters, which enables higher moisture consumption during hydrolysis and keeps cellulose dry.

In the present study, life estimation of accelerated aged insulating papers used in rotating machines is estimated by Arrhenius model. Various types of insulating papers used in rotating machines such as Mylar, Nomex-Mylar-Nomex(NMN), Leatheroid, Dacron-Mylar-Dacron(DMD), Mica Tape, and Kapton are thermally aged at 90°C, 130°C and 170°C with 300hrs duration of each sample. These insulating materials wrapped on copper conductor with single and double layer. Then, breakdown voltage test is performed at each temperature for both single and double layer papers to determine their dielectric strength. Further, correlation analysis between breakdown voltage and different applied temperatures is performed for all paper samples. Popular Arrhenius plot is drawn by short term test data on breakdown voltage for an extrapolation to long term performance of various types of insulating paper used in rotating machines. The results showed that the performance of double layer insulation is almost twice than single layer performance. The aging analysis and testing of insulating papers was performed in TIFAC-Core centre of NIT Hamirpur, H.P., India.

The demand for power is increasing day by day, and working with fossil fuels is associated with global warming problem, so renewable resource is better option to fulfil ever-increasing power demand without affecting climate. Among renewable resources, solar energy is widely adopted due to its availability in abundance. The power output for a solar photovoltaic (SPV) cell depends on the operating temperature, solar irradiation and load impedance. So maximum power point of SPV is not constant and keeps on changing under different conditions. Therefore, maximum power point tracking is used to uphold the point to extract maximum power from PV system under different working conditions. In this paper, we have described many maximum power point tracking algorithms commonly used for extracting maximum power out of a solar panel. We have also done a comparative analysis among them for various parameters using a common Simulink model in MATLAB. It has been found that among different methods, artificial intelligence method is most efficient compared to all existing methods and perform well under different conditions of solar irradiations and temperatures.

Solar power technology was present in India from a very long time, but due to its high purchase cost, only few were able to reap its benefits. It was very costly and less efficient during its early phase, but due to the increase in efficiency of solar modules and drop in the prices of solar PV along with various government schemes and policy implementations, solar PV technology has gained prime importance as a source of electricity. In this paper, we have carried out design, technical and financial analysis along with optimisation of solar PV plant for the School of Engineering and Technology, Baba Ghulam Shah Badshah University (BGSBU), Rajouri, Jammu and Kashmir, India. This paper uses two-way approaches for the design and analysis of feasibility of solar PV plant. We have not limited our design and analysis to the use of simulation software like PV GIS, etc., but also making use of the actual physical cost for the various items needed for building this plant prevailing these days in India. This has helped us to calculate the cost expenditures much closer to that would be spent in building this plant in the future. In this paper, we have estimated the energy demand of the School of Engineering and Technology, and based on the energy demand and location, we have proposed this solar PV system to solve much-awaited issue of power scarcity in such locations of educational and economic importance. This system will not only help the university to lower down the burden of money spent on the usage of electricity but will also help in reducing the quantity of carbon dioxide emission into the atmosphere.

In this paper, evolution of ester dielectrics highlighting the significant contributions towards replacement of mineral oils with ester oils was discussed. The citations listed in this survey provide a representative sample to current scenario pertaining to ester dielectrics in transformer insulation technology. Additionally, X-ray diffraction analysis highlighting the degradation rate of insulation paper in the presence of typical dielectric liquids, UV spectroscopy analysis of oils, interfacial tension variations, and diffusion characteristics of insulation paper were experimentally found by simulating accelerated thermal stresses. Furthermore, future challenges and outlook in accommodating ester dielectric liquids for safer and effective transformer technology were also discussed.

In this work mineral oil, natural ester, synthetic ester and a mixture of mineral oil and synthetic ester have been subjected to accelerated thermal stressing in presence of copper and cellulose. All these samples were subjected to 110°C, 150 °C, 170 °C and 200 °C thermal stressing for different test durations. Thermal degradation of the samples has been monitored continuously with UV Spectroscopy and visual inspections. Additionally interfacial tension of mineral oil and mixture oil has been monitored under the same test conditions to observe the miscible performance of the fluids. It has been found that the degree of degradation is less with synthetic esters than other samples. Interfacial tension and visual observations revealed less sludge formation in synthetic esters. Furthermore, aged insulation paper has been analyzed using X- ray diffraction technique to find the degradation rate of cellulose in various insulating fluids. It has been found that the rate of degradation is low in synthetic ester and performance of mixed oil is better than mineral oil.

Mineral oils have been used in transformers for cooling and insulation for many years. Despite their long-time success, mineral oils are facing critiques by the electrical power industry in terms of thermal performance—mineral oils have relatively low flashpoint and fire point and will burn in the event of a fault [1], [2], [3]; environmental performance—mineral oils are less biodegradable, toxic in nature, and hazardous in the soil and water [4]; and risk assessment—mineral oils are imperilling near hospitals, near high rise buildings, and in residential areas.

Dissolved Gas Analysis has been one of the most extensively used tools for health monitoring of power transformers. Since its introduction, researchers have been working on to increase its ability to predict the incipient faults more accurately. DGA methods have been shifting from off-line to online monitoring, and interpretation techniques from key gas and ratio methods to graphical methods and more advanced methods. But presently, the DGA data is used to interpret more detailed information about the faults like severity of the fault or involvement of solid insulation. In this paper, an effort has been made to cover some of such emerging techniques in the field of DGA along with issues like stray gassing problem, scheduling DGA inspection etc. With the development of alternate insulating liquids, DGA of such liquids is gaining importance and have been proactively covered in this paper. Further, the extensive implementation of AI techniques for more flexible interpretation of DGA data is also evaluated through this paper.

Performance of a fuzzy expert system is related with how good the membership functions are normalized, tuned for a problem statement and correlation of antecedents and consequents. This paper helps in tuning and designing the membership functions that are best suited for the problem statement by integrating subtractive clustering method for fuzzy expert system design. Subtractive clustering algorithm is used to generate the tuned membership functions automatically in accordance to the domain knowledge. The proposed integrated design of clustering based fuzzy expert system acts in improving the accuracy and leads to a precised decision making environment. A practical example for ageing assessment of transformer insulation oil has been included to illustrate the method much effectively; the discussed example has been validated practically in the laboratory and is found that the proposed method is efficient in decision making.

Present research work deals with the preparation and characterization of raw and surface modified Grewia optiva particle fibers reinforced unsaturated polyester (UPE) matrix based bio-composites. Raw and surface modified fibers have been used in different proportions for the preparation of these composites. The optimization of fiber proportions has been done in term of their mechanical properties i.e. tensile, compressive and flexural strength. After the optimization of fiber proportions, these optimized composite samples were characterized by TGA, DSC and SEM techniques. In addition, they were also evaluated for their dielectric properties. It has been found that the dielectric properties of the surface modified fibers reinforced composites increased considerably.

Mineral oil used in power transformer is having low temperature and environmental performance. The increase in power rating of transformers called for high temperature performance and environmental friendly insulating oils. Ester based dielectric fluids has been found to defeat mineral oils in all technical and environmental aspects. Hence there is a great need of research on ester oils. The present paper is bibliography of 150 published articles. Owing to a large number of contributions and limit to length of the documentation; exceptions were made to include a citation if a publication contributed a significantly unique; practically technical viewpoint on usage of esters based dielectric fluids for transformer insulation technology. The selected literature has been put in relevant sections to make researchers convenient in obtaining literature. Some of the contributions spanned for more than one section; efforts were made to include such citations in one of the most relevant section.