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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.

Esters based dielectric fluids have been widely researched since 1990’s for application in high voltage insulation applications. Since then, researchers are affirmative towards usage of ester based insulating fluids as a replicated to mineral insulation oils. The operating properties and aging performance of ester oils proved to be potential candidates for high voltage applications. In view of high temperatures and longevity of insulation systems, there also is a need to understand the chemical perspectives along with aging behaviour of ester oils. Accelerated aging of oil/paper insulation associated with mineral oil and synthetic ester with cellulose insulant has been experimentally simulated as per ASTM D 1934 at 115 ℃. Fourier Transform Infrared spectroscopy analysis of oils and cellulose papers is carried out at different aging factors. The compositional changes in oils and cellulose kraft paper with aging have been enumerated. The changes in the absorbance area for appropriate functional groups have been also reported. It is found that, the chemical stability of synthetic esters is superior to that of the mineral oil.

This paper presents the performance analysis of classical controllers tuned using heuristic approaches for frequency regulation. The system under study comprises of two areas each having one thermal turbine in each control area. The frequency regulation is achieved using different classical controllers whose controller gains have been optimized using heuristic techniques namely genetic algorithm (GA) and gravitational search algorithm (GSA). To overcome the concerns of local trapping in local minima, hybridized GSA incorporating the concept of opposition learning and disruption, i.e., disrupted oppositional learned gravitational search algorithm (DOGSA) has also been used for optimization of controller gains. The simulation results in terms of fitness value, settling time, and peak overshoot/undershoot depict the superiority of the DOGSA-optimized controllers under load perturbations in the system.

The article presents a novel bio-inspired Krill Herd (KH) algorithm to solve economic dispatch problems. KH algorithm is based on crowding behavior of the krill individuals and achieves a near global optimum solution by using three main actives. The proposed algorithm is tested by considering three and six generating unit systems on different loads on objective function. The attained results have proved that the KH algorithm provides remarkable results as compared with the other optimization algorithms reported in the literature.

A critical survey has been conducted on high energy-efficient bidirectional converters, various topologies that effectively meet the automated vehicle requirements, and 24 GHz/77 GHz low-profile antennas (for automotive radar applications). The present survey has been identified into two parts on the current topic of study as perspectives and challenges. Part 1 of this survey covers energy-efficient power electronic convertor topologies and condition monitoring aspects of convertors to enhance the lifespan and improve performance. Condition-monitoring issues concerning the abnormalities of electrical components, high switching frequencies, electromagnetic interference, leakage currents, and unwanted joint ruptures have also been emphasized. It is observed that composite converters are proficient for automated hybrid electric vehicles due to fast dynamic response and reduced component count. Importantly, electrical component failures in power electronic converters are most common and need attention for the effective operation of the bidirectional converters. Hence, condition monitoring implementation schemes have also been summarized. Part 2 of this survey focuses on 24 and 77 GHz low-profile (microstrip-based) antennas for automotive radar applications, types of antenna structures, feed mechanisms, dielectric material requirements, design techniques, and performance parameters. The discussion in Part 2 also covers feed methodologies, beam scanning concepts, and side-lobe levels on the autonomous vehicle communication activities.

Automated vehicles are becoming popular across the communities of e-transportation across the globe. Hybrid electric vehicles and autonomous vehicles have been subjected to critical research for decades. The research outcomes pertinent to this topic in the literature have been motivated by the industry and researchers to emphasize automated vehicles. Part 1 of this survey addressed the critical aspects that concern the bidirectional converter topologies and condition monitoring activities. In the present part, 24- and 77-GHz low-profile printed antennas are studied for automotive radar applications. These antennas are mounted on automated vehicles to avoid collision and are used for radio tracking applications. The present paper states the types of antenna structures, feed mechanisms, dielectric material requirements, design techniques, performance parameters, and challenges at 24- and 77-GHz resonating frequency applications. The recent developments in feed methodologies, beam scanning concepts, and the effect of sidelobe levels are addressed. Furthermore, the reasons behind the transition from 24 to 77 GHz are reported in detail. The recent advances in the application of various sensor schemes in an automated vehicle have also been discussed.

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.

This paper presents the automatic generation control (AGC) of an interconnected two-area multi-source hydro-thermal power system. The considered system performance is studied and analyzed with proportional-integral (PI), proportional-integral-derivative (PID) and 2 degree of freedom PID(2DOF PID). The gains of the controllers are optimized using dragonfly algorithm (DA). The performance of the DA algorithm is matched with the genetic algorithm (GA) and hybrid firefly and pattern search technique to state its superiority. The comparative results show that 2DOF PID scheme tuned using DA gives better results than the classical controllers.

This paper proposes a simple and heuristic-based solution method for solving economic load dispatch (ELD) in an islanded mode of microgrid. The economic dispatch for different combination of conventional and nonconventional sources is performed by using real-valued genetic algorithm (GA). This paper compares the total power generation cost for different combination of sources. Further, it considers the solar renewable energy credits (REC), provided by the government to encourage the usage of renewable energy sources in order to reduce the emission pollutants and to overcome the fuel availability problems. Thus, results show the integration of renewable sources and simultaneous consideration of solar credits gives more profit to the microgrid.

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.

Power Transformers are one of the most important and critical devices of any power system network so the interpretation of the faults and failures within transformers are of utmost importance. In monitoring the condition of the transformers sweep frequency response analysis has gained huge interest in assessing the core or winding disintigrity and deformations, open or shorted turns, axial or radial shifts etc. Changes in core and winding can be detected from the knowledge of poles and zeroes of the transfer function by statistical and mathematical indicators. In spite of efforts of researchers on SFRA there is no universally accepted or systematic method to detect deformations of winding and core of transformers. This new method is based on multiresolution decomposition technique using discrete wavelet transform. This method is further supported by statistical and mathematical indicators using the frequency band where faults actually exist which adds robustness and accuracy to the diagnosis of the fault. This methodology is tested for several cases of transformers and validated using two of the cases which show the difference between normal and abnormal condition of the transformers.

Determining the current prevailing conditions in the transformer is still a challenge and an attempt is made for meeting the same challenge. In this paper a novel system based on fuzzy logic is developed which considers thermal, electrical and mechanical conditions prevailing in the transformer and gives the critical status of the transformer at an aggregate. The developed system also facilitates to give the critical condition of Paper thermal, Oil thermal, Partial discharge, Electrical arching, Dissolved gas analysis(DGA), Break down voltage and sweep frequency response analysis(SFRA) individually so that corresponding preventive measures can be taken by the technologists. This system consists of 10 fuzzy logic controllers whose connections are made by considering technical conditions and reasons, the corresponding rule bases of these fuzzy logic controllers were developed by considering various standards and experience of TIFAC CORE in NIT-Hamirpur. This fuzzy logic based system is tested for various transformers and found that it is highly précised in classifying the critical statues of any transformer as well as all identifying the current prevailing conditions.

Power transformers are to be monitored frequently to avoid catastrophic failures which are more or less related to internal faults for which many techniques and tools are developed, somehow many of these techniques rely on experts analysis and are well effected by environmental conditions which leads to misdiagnosing of the unit. In this paper a new fuzzy logic algorithm (FLA) based technique is developed which gives the vulnerability status of internal faults by considering thermal, electrical and mechanical conditions prevailing in the transformer and integrating them. This system takes a set of test results of dissolved gas analysis, break down voltage, and sweep frequency response analysis so that aliasing effects and misdiagnosing can be reduced at a glance. It also facilitates to give current prevailing condition of Paper thermal, Oil thermal, Partial discharge, Electrical arching, oil break down voltage, and mechanical deformations related with core and windings individually so that corresponding remedies can be taken by the technologists. This system consists of 10 fuzzy logic controllers and is connected by considering technical conditions and reasons, the rule bases of these controllers were developed by considering various standards and experience of TIFAC CORE in NIT-Hamirpur. This fuzzy logic based system is tested and found that it is highly precise in classifying the critical statues of any transformer, reducing misdiagnosing and aliasing effects and identifying the current prevailing conditions.

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.

Ester based dielectric liquids with attractive environmental and temperature performance draw the attention for those interested in alternate dielectric liquids for transformers. In this paper Breakdown voltage and Spectroscopy analysis of Mineral Oil, Natural Ester and Synthetic Ester and mixture of mineral oil with Synthetic ester has been compared for fresh samples. Trending patterns of these samples at 110°C temperature stressed for duration of 24, 48, 72 and 96 hours in presence of copper-cellulose assembly has been evaluated using visible spectrophotometry. The present paper is the work done till date in investigating the ageing of the above said samples by accelerated thermal stresses in presence of copper and cellulose. Furthermore in this paper, major hypothetical findings of esters by other researchers relating to physiochemical aspects, Operational Aspects, Dielectric Aspects, Thermal aspects have been discussed in detailed. Design and condition monitoring related issues for ester oil filled transformers has been highlighted.

Ester based dielectric fluids were found to beat mineral oils in thermal and environmental aspects. Hence there is a great need of research on ester oils. The present paper is a review of 84 published articles. Owing to length of the document; exceptions were made to include a citation if a publication contributed a significantly technical viewpoint on usage of ester oils for transformer insulation technology. The selected literature has been classified into relevant sections to make researchers convenient in obtaining literature. Some citations spanned for more than one section, efforts were made to include such citations in one of the most relevant section. The present paper will be useful to the industry and researchers to know the significance and need of ester based dielectrics to the present day scenario.

Diagnostics and proper monitoring of power transformer plays a key role in the life expectancy of proper transformer. Mineral oil in transformer is the inseparable component of the dielectric insulation system. Information about the health of the power transformer that can be use to plan cost, maintenance, renovation and operational criteria can be accurately interpreted using UVSpectrophotometer. As UV scan can only show the pictorial information of the age of the oil hence it is not advantageous in all aspects. In the present paper a decision tree method to determine the age of the transformer oil is introduced. The decision tree uses the UV/VIS spectroscopy absorbance values of the transformer oil which are in service at several locations. The decision tree method is designed so that the results of transformer oil can be examined quickly and automatically. The results obtained are compared with the UV/VIS spectroscopy for testing the accuracy of the decision tree and found that it is 100% accurate.

The present paper introduces Subtractive clustering method for identifying the ageing of insulation oil of power transformers. This work handles the problem with complex dimensions to an efficient and accurate dimensional area. Feature selection for clustering is done by extracting values from Spectroscopy absorbance curves of various oil samples. Feature validation is done by designing a fuzzy inference engine; the results obtained from fuzzy inference engine are then compared with practical data to enhance/ensure the validity and found that these results were matched with practical data. These features are now plotted in a space as training data samples and further Subtractive clustering algorithm is applied for different radius values to generate an efficient inference engine. The oil groups viz new age, medium age and old age samples are identified and correspondingly centers have been plotted for each group. Verification for this work is done practically in the laboratory and has been found that the proposed methodology is efficient in diagnosing the ageing of insulation oil.

Power transformers are to be monitored frequently to avoid catastrophic failures which are more or less related to internal faults. Many techniques and tools are developed world wide and most of these techniques rely on expert's analysis and are well affected by environmental conditions which lead to misinterpretation of the test. In this paper a new fuzzy logic algorithm (FLA) based technique is developed which gives the vulnerability status of internal faults by considering thermal, electrical and mechanical conditions prevailing in the transformer and integrating them. This system takes a set of test results of dissolved gas analysis, insulating oil break down voltage, and sweep frequency response analysis so that aliasing effects and misinterpretions can be reduced at a glance. It also facilitates to give status of prevailing condition of Paper thermal, Oil thermal, Partial discharge, Electrical arching, oil break down voltage, and mechanical deformations related with core and windings individually. This system consists of 10 fuzzy logic controllers and they are connected by considering technical conditions and reasons, the rule bases of these controllers were developed by considering various standards and experience of TIFAC CORE in NIT-Hamirpur. The proposed system is tested and found that it is highly precise in classifying the situations of any transformer, reducing aliasing effects and identifying the current prevailing conditions.