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Related Concept Videos

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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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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Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

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Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
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Distributed Loads01:19

Distributed Loads

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Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
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Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

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A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
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For the first part of...
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Heuristics01:21

Heuristics

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Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
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Effective hybrid search technique based constraint mixed-integer programming for smart home residential load

Esam H Abdelhameed1, Samah Abdelraheem2,3, Yehia Sayed Mohamed3

  • 1Faculty of Energy Engineering, Aswan University, Aswan, Egypt. ehhameed@energy.aswu.edu.eg.

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This study introduces a hybrid optimization technique for smart home energy scheduling, significantly cutting electricity costs and improving user comfort. The method effectively manages residential loads under dynamic pricing and photovoltaic power systems.

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Area of Science:

  • Smart Grid Technology
  • Optimization Algorithms
  • Energy Management Systems

Background:

  • Residential load scheduling is crucial for minimizing electricity costs and enhancing user comfort.
  • Existing optimization methods struggle with the non-convex nature of smart home (SH) scheduling problems.
  • Dynamic electricity pricing and the integration of renewable energy sources like photovoltaic (PV) systems add complexity.

Purpose of the Study:

  • To develop and evaluate a novel hybrid search technique for optimizing SH residential load scheduling.
  • To minimize electricity bills while maximizing user comfort under various power supply scenarios.
  • To address the non-convexity of the multi-objective constraint mixed-integer optimization problem (CP-MIP).

Main Methods:

  • A two-stage hybrid search technique combining Relaxation and Rounding (RnR) with metaheuristic algorithms.
  • Stage 1: Relaxation using metaheuristics (BPSO, SOH-PSO, JAYA, CL-JAYA) for optimal rational solutions.
  • Stage 2: Stochastic rounding for feasible solutions, applied under Time-of-Use (ToU) pricing and dual power modes (grid-only or grid-PV).

Main Results:

  • Significant electricity bill reductions achieved: up to 20.0% in grid-only mode and 56.1% in grid-PV mode.
  • The Comprehensive Learning JAYA algorithm (CL-JAYA) demonstrated superior performance in both cost savings and user comfort.
  • The proposed hybrid technique effectively handles the complexities of SH energy management.

Conclusions:

  • The novel hybrid optimization approach is highly effective for smart home energy scheduling.
  • The technique offers substantial economic benefits and improves user satisfaction.
  • CL-JAYA emerges as a leading metaheuristic for advanced smart home energy management systems.