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Towards next generation power grid transformer for renewables: Technology review

AbstractThis paper develops a technical framework for the next‐generation power grid transformer (NGPGT) for grid renewables. This framework is structured to overcome the environmental challenges produced by the explosive use of nonrenewable base energy generation sources. The use of these sources cannot meet the required electricity for the world's growing community due to their availability, cost, and lack of flexibility. However, modern energy systems focus on the use of renewable energy sources, where the grid transformer's interaction plays an essential role in their generation, transmission, and distribution. The lack of centralization, local monitoring, interoperability, authenticity, and precise bi‐directional flow may limit the application of current framework power grid transformers in grid renewables. In this paper, a new technical framework, called NGPGT, is developed by introducing some extended features for addressing the challenges shown in current‐generation transformers. This is structured by enabling some advanced technical features with the existing framework, which includes automatic condition monitoring, intelligent inverters, edge computing, automatic controlling, and intelligent management. This paper also illustrates the benefits and scope of the NGPGT compared to the existing transformer by assembling essential requirements and obligatory components. Additionally, this paper highlights a few difficulties of implementing NGPGT in terms of operational, communication, energy management, and economic points of view, which may enable further research scopes for the researchers.
Smart Grid Applications, Renewable energy, Power Electronics and Conversion Systems, Renewable Energy Integration, Lithium-ion Battery Management in Electric Vehicles, FOS: Mechanical engineering, power grid, Quantum mechanics, Engineering, Microgrid Control, FOS: Electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Grid, technological challenges, Transformer, Geography, Physics, Voltage, QA75.5-76.95, Power (physics), Engineering (General). Civil engineering (General), renewable energy, Computer science, emerging technologies, Power grid, Control and Systems Engineering, Electronic computers. Computer science, Electrical engineering, Physical Sciences, Automotive Engineering, Control and Synchronization in Microgrid Systems, next‐generation transformer, TA1-2040, smart transformer, Geodesy
Smart Grid Applications, Renewable energy, Power Electronics and Conversion Systems, Renewable Energy Integration, Lithium-ion Battery Management in Electric Vehicles, FOS: Mechanical engineering, power grid, Quantum mechanics, Engineering, Microgrid Control, FOS: Electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Grid, technological challenges, Transformer, Geography, Physics, Voltage, QA75.5-76.95, Power (physics), Engineering (General). Civil engineering (General), renewable energy, Computer science, emerging technologies, Power grid, Control and Systems Engineering, Electronic computers. Computer science, Electrical engineering, Physical Sciences, Automotive Engineering, Control and Synchronization in Microgrid Systems, next‐generation transformer, TA1-2040, smart transformer, Geodesy
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).6 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
