Yazar "Narayanan, K." seçeneğine göre listele

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    Power Loss Minimization through Reconfiguration Using BPSO-Based Technique
    (Taylor & Francis Inc, 2023) Kirithikaa, S.; Narayanan, K.; Sharma, Gulshan; Bokoro, Pitshou N.; Celik, Emre; Bekiroglu, Erdal
    Power loss is influenced by uncertain and ever increasing loads in the system but can be minimized by network reconfiguration where the topological structure of the system is changed by altering the switching operation. In this work, a multi-objective framework through reconfiguration is formulated with loss minimization as primary objective and reliability and voltage profile improvement as secondary objectives. A binary particle swarm optimization (BPSO) base method is developed to reconfigure the network by fulfilling all distribution network constraints. The influence of the BPSO parameters to obtain the optimal switches with minimized power loss, reliability indices, and voltage deviations are studied by a faster convergence. The results have been compared for different weights of the objective to give a comprehensive understanding of the nature of the objective attempted in this work. IEEE 33 bus and radial IEEE 69 bus systems were considered for testing the proposed method.
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    Reliability Assessment of Demand Response Strategies for Profit Maximization
    (Taylor & Francis Inc, 2023) Sivasankari, G. S.; Narayanan, K.; Sharma, Gulshan; Celik, Emre; Bekiroglu, Erdal
    The idea of renewable resource integration influences the demand-supply balance significantly. The effort taken to diminish the deviation in demand-supply balance is greatly influenced by demand response (DR) strategy. In this analysis, the concept of DR is incorporated via the approach of load management. The optimal scheduling of the load considering the available energy helps to avoid unessential load shedding. The DR strategy of load shifting is suggested at different levels in accordance with the nature of load and real-time price. The profit of the utility is enhanced by providing the customer the flexibility to schedule their load. The curtailment of load can be avoided by increased customer participation in the suggested DR programs. The operating system is designed to be both efficient and effective by utilizing the real-time tariff profile of electricity to plan the generation of renewable energy, energy storage systems that include electric vehicles, and the utilization of grid power. The scalability and generalization of the proposed DR approach make it suitable for large-scale power systems that integrate renewable energy sources. The validation of the proposed method using reliability analysis ensures the effectiveness of the formulated DR. The proposed method is tested under two different scenarios and topologies on the IEEE-33 bus system and the results accomplished are promising.