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Related Concept Videos

Maximum Power Transfer01:16

Maximum Power Transfer

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Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
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Energy Losses in Transformers01:21

Energy Losses in Transformers

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In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be  the high resistance of the...
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Conservation of AC Power01:15

Conservation of AC Power

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The principle of power preservation is applicable to both ac and dc circuits. This principle, when applied to AC power, asserts that the complex, real, and reactive powers produced by the source are equal to the total complex, real, and reactive powers absorbed by the loads. When two load impedances are connected in parallel to an ac source V, the complex power provided by the source can be calculated using the relation
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Power Distribution in Three-phase and Single Phase Circuits01:17

Power Distribution in Three-phase and Single Phase Circuits

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Power distribution within electrical circuits is a foundational aspect of residential and industrial energy systems. While single-phase power is common in residential settings, three-phase power is the standard for industrial environments with heavy machinery. Each system is different and has advantages, and it's crucial to understand the underlying principles of power distribution and material efficiency.
Single-Phase Power Distribution:
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Energy Stored in Inductors01:16

Energy Stored in Inductors

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An inductor is ingeniously crafted to accumulate energy within its magnetic field. This field is a direct result of the current that meanders through its coiled structure. When this current maintains a steady state, there is no detectable voltage across the inductor, prompting it to mimic the behavior of a short circuit when faced with direct current.
In terms of gauging the energy stored within an inductor, it is equivalent to the integral of the power delivered at every individual moment, all...
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Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

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The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
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Area of Science:

  • Wireless Communication
  • Internet of Things (IoT)
  • Edge Computing

Background:

  • IoT devices face battery and computational limitations.
  • Simultaneous Wireless Information and Power Transfer (SWIPT) and Mobile Edge Computing (MEC) offer solutions.
  • Wireless channel fading and obstacles hinder performance.

Purpose of the Study:

  • To enhance spectral and energy efficiency in wireless networks using Intelligent Reflecting Surfaces (IRS).
  • To propose a system model for IRS-assisted uplink/downlink computation offloading and simultaneous energy transfer.
  • To minimize IoT device energy consumption under various system constraints.

Main Methods:

  • Joint optimization of CPU frequency, transmit power, computation workload, power splitting (PS) ratio, and IRS phase shifts.
  • Development of an alternating optimization (AO) iterative algorithm.
  • Application of closed-form solutions, Dinkelbach-based Lagrange dual method, and Semidefinite Relaxation (SDR).

Main Results:

  • A multi-variate coupled nonlinear problem was formulated to minimize energy consumption.
  • The proposed AO algorithm effectively optimizes system parameters.
  • Simulation results show reduced energy consumption compared to existing strategies.

Conclusions:

  • IRS-assisted systems can significantly improve energy efficiency for IoT devices.
  • The proposed optimization framework effectively addresses complex system constraints.
  • This approach offers a viable solution for sustainable IoT deployments.