Digital twin for intelligent probabilistic short term load forecasting in solar based smart grids using shark algorithm

Meng, Fanjuan; Wang, Xianchang

doi:10.1016/j.solener.2023.111870

Cited by 10 publications

(1 citation statement)

References 20 publications

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“…The results are validated through a constructed prototype for real-time monitoring and control of power distribution networks. The article (Meng and Wang, 2023) proposes an evolving-based prediction model for accurate shortterm load forecasting in solar-based smart grids. It utilizes the innovative lower upper bound estimation (LUBE) trained on real-time data from the smart grid's digital twin.…”

Section: Integration Of Wireless Sensor Network (Wsns)-focus Of the R...mentioning

confidence: 99%

Digital twin technology for enhanced smart grid performance: integrating sustainability, security, and efficiency

Alharbey,

Shafiq,

Daud

et al. 2024

Front. Energy Res.

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This research paper presents the development and analysis of a multifaceted smart grid prototype. It combines various technologies for the smart grid operation. The first technology is environmental analysis of smart grid and solar panel cleaning. Secondly, radio-frequency identification (RFID)-based security and access control system has been integrated for smart grid. The third component is internet of things (IoT)-based energy monitoring and load management. For environmental analysis sensors such as temperature, humidity, light-dependent resistor, and flame sensors are connected to a NodeMCU controller for real time monitoring. Moreover, IoT based solar cleaning system is developed in the form of prototype with the help of Blynk and servo motor. The second component of prototype is smart security system which is developed with the help of Arduino and RFID module to facilitate secure access control. The third part of prototype employs voltage and current sensors with an ESP32 microcontroller and the Blynk application for real-time energy consumption analysis. This setup enables remote monitoring of voltage, power dynamics, and consumption patterns in a smart grid. It also offers an IoT based solution for load management and load shedding within the smart grid. The complete prototype overall demonstrates a comprehensive approach to 1) smart grid management, 2) environmental analysis, 3) security, and 4) energy monitoring.

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Section: Integration Of Wireless Sensor Network (Wsns)-focus Of the R...mentioning

confidence: 99%

Digital twin technology for enhanced smart grid performance: integrating sustainability, security, and efficiency

Alharbey,

Shafiq,

Daud

et al. 2024

Front. Energy Res.

View full text Add to dashboard Cite

show abstract

A novel combined probabilistic load forecasting system integrating hybrid quantile regression and knee improved multi-objective optimization strategy

Yang,

Xing,

Wang

et al. 2024

Applied Energy

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Novel abstractions and experimental validation for digital twin microgrid design: Lab scale studies and large scale proposals

Sifat,

Choudhury,

Das

et al. 2025

Applied Energy

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Digital twin for intelligent probabilistic short term load forecasting in solar based smart grids using shark algorithm

Cited by 10 publications

References 20 publications

Digital twin technology for enhanced smart grid performance: integrating sustainability, security, and efficiency

Digital twin technology for enhanced smart grid performance: integrating sustainability, security, and efficiency

A novel combined probabilistic load forecasting system integrating hybrid quantile regression and knee improved multi-objective optimization strategy

Novel abstractions and experimental validation for digital twin microgrid design: Lab scale studies and large scale proposals

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