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Related Concept Videos

Distributed Loads: Problem Solving01:21

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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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The analysis of suspension bridges is a complex and critical process that involves multiple factors, including the shape and tension of the main cables. The main cables of suspension bridges are subjected to distributed loads, which result in changes in tensile forces and deformation of the cable. These loads must be carefully considered to ensure that the bridge is safe and capable of supporting the weight of different loads.
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Flexible cables are commonly used in various applications for support and load transmission. Consider a cable fixed at two points and subjected to multiple vertically concentrated loads. Determine the shape of the cable and the tension in each portion of the cable, given the horizontal distances between the loads and supports.
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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.
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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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Towards Feasible Solutions for Load Monitoring in Quebec Residences.

Sayed Saeed Hosseini1, Benoit Delcroix2, Nilson Henao1

  • 1Department of Electrical and Computer Engineering, Laboratoire d'innovation et de Recherche en Énergie Intelligent, Hydrogen Research Institute, Université du Québec à Trois-Rivières, Trois-Rivières, QC G8Z 4M3, Canada.

Sensors (Basel, Switzerland)
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Summary
This summary is machine-generated.

Non-Intrusive Load Monitoring (NILM) faces challenges in Quebec residences due to region-specific electricity usage. This study proposes a hybrid approach combining intrusive and non-intrusive methods to improve NILM feasibility.

Keywords:
Non-Intrusive Load Monitoring (NILM)electric baseboardselectric water heaterslow-sampling load disaggregationmachine learning algorithmsstatistical analysis

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Area of Science:

  • Energy Systems Engineering
  • Artificial Intelligence in Energy

Background:

  • Non-Intrusive Load Monitoring (NILM) aims for disaggregated energy monitoring but faces practical limitations in residential settings.
  • Existing NILM research relies heavily on European and US datasets, overlooking diverse geographical and behavioral contexts.

Purpose of the Study:

  • To investigate the barriers to implementing NILM in Quebec residences.
  • To propose a novel hybrid approach for load identification and disaggregation tailored to Quebec's specific residential context.

Main Methods:

  • Comparative statistical analysis of Quebec residential energy data.
  • Development of a combinatory load identification approach integrating sub-metering with NILM.
  • Application of supervised and unsupervised machine learning for heating demand and residual load disaggregation.

Main Results:

  • Geographically-specific electricity consumption patterns in Quebec significantly impact the performance of existing NILM methods.
  • The proposed hybrid approach demonstrates potential for alleviating NILM difficulties in the studied region.

Conclusions:

  • NILM system viability is critically dependent on addressing geographically-specific consumption characteristics.
  • Further research and tailored methodologies are essential for successful NILM implementation in diverse residential environments like Quebec.