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Therefore, to overcome the energy depletion in sensor nodes, it is important to study the energy management issue in WSN. In this chapter, the significance of energy management issue is discussed first, and then the possible energy management strategies for WSN are presented and illustrated. . sumption and maximize the life time of the network. The development of communication techniques from single hop to multi ho and then the use of. . To overcome this issue, this paper proposes an Optimized Explicit Feature Interaction-Aware Graph Neural Network based Efficient Energy Management in Wireless Sensor Networks (OEFIA-GNN-EEM-WSN). We introduce an enhanced fuzzy spider monkey optimization technique and a hidden Markov model-based clustering algorithm for selecting cluster heads.
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This paper introduces a new control strategy for the DC microgrid to regulate the bus voltage and power sharing among the DGs, ESDs, resistive loads, and constant power loads (CPLs). . ergy storage based on the compensati, addressing the diverse operati oller for multiple energy storage devi nd in order to compensate the demand-generation mi instability in both e load demand may result in power system instability [3]. However, the difference of line impedance causes diversity in the state-of-charge (SoC) between. . Direct current (DC) microgrid has recently gained potential interest since it supports easy integration of distributed generators (DGs) and energy storage devices (ESDs).
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