Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

578
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.
578
Energy and Power Signals01:17

Energy and Power Signals

1.0K
In an electrical system with a resistor, voltage and current signals facilitate the measurement of power and energy across the resistor. For a continuous-time signal, the total energy over a time interval is defined as the integral of the square of the signal's magnitude over that interval. Mathematically, this is expressed as:
1.0K
Electrical Energy01:10

Electrical Energy

1.6K
Using electric appliances for a longer period of time consumes more electrical energy and results in a higher electric bill. The energy produced by the transfer of electrons from one point to another is known as electrical energy. If power is delivered at a constant rate, the electrical energy can be defined as the product of power used by the device for a period of time. The energy unit on electric bills is the kilowatt-hour, where one kilowatt-hour is equivalent to 3.6 × 106 joules.
1.6K
Maximum Power Transfer01:16

Maximum Power Transfer

811
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...
811
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

1.1K
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?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the...
1.1K
P-N junction01:11

P-N junction

1.1K
A p-n junction is formed when p-type and n-type semiconductor materials are joined together. At the interface of the p-n junction, holes from the p-side and electrons from the n-side begin to diffuse into the opposite sides due to the concentration gradient. This diffusion of carriers leads to a region around the junction where there are no free charge carriers, known as the depletion region. The charge density within the depletion region for the n-side and p-side can be described by the...
1.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Tri-Net: unified deep learning for skin lesion and symptom-based monkeypox detection.

Scientific reports·2026
Same author

Light spectrum optimizer and pyramidal dilation attention convolutional neural network for wind energy conversion system using permanent magnet synchronous generator and single-ended primary inductor converter.

Scientific reports·2026
Same author

Reinforcement learning enabled hybrid optimisation for energy-efficient multipath routing in wireless sensor networks.

Scientific reports·2026
Same author

LiWO-SRDN-based EV charging coordination for stable smart grid systems using a single-switch high step-up zeta converter.

Scientific reports·2026
Same author

Foliar Fate of Phthalate Esters in Lettuce: Uptake, Phytotoxicity, and Metabolic Responses.

Journal of agricultural and food chemistry·2026
Same author

ColoXAI-RecomNet: Explainable Recommender Framework for Colorectal Cancer Classification Using Integrated CNN Ensemble and LIME Interpretability.

Journal of imaging informatics in medicine·2026

Related Experiment Video

Updated: Jan 11, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

999

Optimized energy management of PV-Powered lighting system for smart cities using perfumer optimization algorithm and

Zakir Hussain1, Prabu Selvam2, M Sivaramkrishnan3

  • 1Department of Chemical Technology, Loyola Academy, Secunderabad, 500015, Telangana, India.

Scientific Reports
|November 17, 2025
PubMed
Summary

This study introduces a hybrid strategy for energy management in smart city PV lighting systems, integrating predictive optimization and neural networks to cut costs and boost efficiency. The new method significantly enhances operational cost-effectiveness and system performance.

Keywords:
And wind turbineEnergy management controllerEnergy management systemGridPhotovoltaicSmart homeSmart meter

More Related Videos

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K
Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

991

Related Experiment Videos

Last Updated: Jan 11, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

999
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K
Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

991

Area of Science:

  • Renewable Energy Systems
  • Smart City Infrastructure
  • Energy Management

Background:

  • Smart cities increasingly integrate renewable energy sources (RES) like PV panels and wind turbines (WT) for lighting.
  • Balancing cost and efficiency in these systems is challenging due to fluctuating supply and demand, necessitating effective energy storage (ESS) and grid integration.
  • Optimizing energy utilization and reducing reliance on conventional sources are key goals for sustainable urban development.

Purpose of the Study:

  • To propose a hybrid energy management (EM) strategy for photovoltaic (PV)-powered lighting systems in smart cities.
  • To reduce operational costs and enhance the energy efficiency of these systems.
  • To address the challenges of matching energy supply and demand with increasing RES integration.

Main Methods:

  • A hybrid strategy integrating Predictive Optimization Algorithm (POA) and a Generative Neural Network (GENN) was developed.
  • POA optimizes energy allocation among RES, grid, and ESS for resource utilization and supply-demand balance.
  • GENN enhances forecasting accuracy for energy generation and consumption patterns.

Main Results:

  • The proposed POA-GENN approach was implemented and evaluated on the MATLAB platform against existing methods.
  • The system achieved a remarkably low operational cost of 365.24 €ct.
  • An outstanding energy efficiency of 99.2% was demonstrated, validating the approach's effectiveness.

Conclusions:

  • The hybrid POA-GENN strategy effectively optimizes energy management in PV-powered smart city lighting.
  • This approach significantly improves both cost-efficiency and energy utilization in complex urban energy systems.
  • The findings highlight the potential for advanced EM strategies to support sustainable smart city development.