
Rinku Kumar
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Papers by Rinku Kumar
components are connected to each other. Connectivity between these components offers many advantages including consumer’s ability to
manage their electricity consumption rates and electricity bills etc. Smart grid also provides operators great extent of system visibility and
control over electricity services, supervision and control of generating units, power quality improvements and reduced fuel cost etc. Highly
connected infrastructure in smart grid threats the reliable operation of grid, especially in terms of cyber security. In automated system, where
control actions can be generated by a single command even from a great distance may lead complete shutdown of the whole system.
Failure/disoperation of power service suspends all critical services. Therefore, the electrical grid becomes the most significant target for acts of vandalism and terrorism. So an extensive security against the cyber-attacks is required in smart grid environment as compare to traditional electricity grid, where almost all control actions were taken manually or with little use of local controllers. Therefore, with control atomization modulation of traditional energy supply system into a smart network requires a huge investment to develop security strategies as a safeguard for this critical infrastructure.
frequency within small fraction of time. Frequency deviations in microgrid occur when the system supply is not sufficient to match the demand.
Efforts are required to keep the frequency deviation within acceptable limit. Using vehicle-to-grid technology, where electric vehicles are used
as energy storage elements for load frequency control in microgrid. For generating the control action to electric vehicles and energy sources in
microgrid, type-2 ANFIS has been employed for quick frequency stabilization in the presence of load and source disturbances. Diesel generator
and wind generator are DG sources considered in this paper and electric vehicles are used as energy storage element. Optimal power sharing
among the different generating units and electric vehicles is achieved by ANFIS controller. Adaptive nature of ANFIS makes it more suitable
and highly robust controller for a complex inter-connected system. Simulation results demonstrate that ANFIS controller is highly efficient as compared to PID controller, fuzzy logic controller, and interval type-2 fuzzy logic controller.
installation point. Thus by choosing proper number of PMUs the system can be made completely supervised. A
PMU costs very high, so it is important to supervise the power system network with minimum units. To monitor
the entire power system distribution network with minimized number of PMUs in smart grid, this paper
proposes a linear algorithm. For dynamic analysis and state estimation, fault diagnosis, time rate of power flow
and behavior of system under various circumstances for these events, data must be highly synchronized in time,
so that real time inspection and operation of the system can be made available for decision making in smart grid.
components are connected to each other. Connectivity between these components offers many advantages including consumer’s ability to
manage their electricity consumption rates and electricity bills etc. Smart grid also provides operators great extent of system visibility and
control over electricity services, supervision and control of generating units, power quality improvements and reduced fuel cost etc. Highly
connected infrastructure in smart grid threats the reliable operation of grid, especially in terms of cyber security. In automated system, where
control actions can be generated by a single command even from a great distance may lead complete shutdown of the whole system.
Failure/disoperation of power service suspends all critical services. Therefore, the electrical grid becomes the most significant target for acts of vandalism and terrorism. So an extensive security against the cyber-attacks is required in smart grid environment as compare to traditional electricity grid, where almost all control actions were taken manually or with little use of local controllers. Therefore, with control atomization modulation of traditional energy supply system into a smart network requires a huge investment to develop security strategies as a safeguard for this critical infrastructure.
frequency within small fraction of time. Frequency deviations in microgrid occur when the system supply is not sufficient to match the demand.
Efforts are required to keep the frequency deviation within acceptable limit. Using vehicle-to-grid technology, where electric vehicles are used
as energy storage elements for load frequency control in microgrid. For generating the control action to electric vehicles and energy sources in
microgrid, type-2 ANFIS has been employed for quick frequency stabilization in the presence of load and source disturbances. Diesel generator
and wind generator are DG sources considered in this paper and electric vehicles are used as energy storage element. Optimal power sharing
among the different generating units and electric vehicles is achieved by ANFIS controller. Adaptive nature of ANFIS makes it more suitable
and highly robust controller for a complex inter-connected system. Simulation results demonstrate that ANFIS controller is highly efficient as compared to PID controller, fuzzy logic controller, and interval type-2 fuzzy logic controller.
installation point. Thus by choosing proper number of PMUs the system can be made completely supervised. A
PMU costs very high, so it is important to supervise the power system network with minimum units. To monitor
the entire power system distribution network with minimized number of PMUs in smart grid, this paper
proposes a linear algorithm. For dynamic analysis and state estimation, fault diagnosis, time rate of power flow
and behavior of system under various circumstances for these events, data must be highly synchronized in time,
so that real time inspection and operation of the system can be made available for decision making in smart grid.