[HTML][HTML] Digital twin for battery systems: Cloud battery management system with online state-of-charge and state-of-health estimation
Battery management is critical to enhancing the safety, reliability, and performance of the
battery systems. This paper presents a cloud battery management system for battery …
battery systems. This paper presents a cloud battery management system for battery …
Two-stage stochastic framework for energy hubs planning considering demand response programs
The integrated use of electricity and natural gas has captured great attention over recent
years, mainly due to the high efficiency and economic considerations. According to the …
years, mainly due to the high efficiency and economic considerations. According to the …
Multi-objective chimp optimizer: an innovative algorithm for multi-objective problems
Abstract The Multi-Objective Chimp Optimization Algorithm (MOChOA), a multi-objective
variation of the recently proposed ChOA, is developed in this research to address multi …
variation of the recently proposed ChOA, is developed in this research to address multi …
[HTML][HTML] A model-based parametric and optimal sizing of a battery/hydrogen storage of a real hybrid microgrid supplying a residential load: Towards island operation
In this study the optimal sizing of a hybrid battery/hydrogen Energy Storage System “ESS” is
assessed via a model-based parametric analysis in the context of a real hybrid renewable …
assessed via a model-based parametric analysis in the context of a real hybrid renewable …
Estimation of bearing capacity of piles in cohesionless soil using optimised machine learning approaches
Accurate estimation of the bearing capacity of piles requires complex modelling techniques
which are not justified by timeframe, budget, or scope of the projects. In this study, six …
which are not justified by timeframe, budget, or scope of the projects. In this study, six …
An efficient binary chaotic symbiotic organisms search algorithm approaches for feature selection problems
Feature selection is one of the main steps in preprocessing data in machine learning, and its
goal is to reduce features by removing additional and noisy features. Feature selection …
goal is to reduce features by removing additional and noisy features. Feature selection …
Energy efficient load balancing approach for avoiding energy hole problem in WSN using Grey Wolf Optimizer with novel fitness function
In general architecture of Wireless Sensor Networks (WSNs), gateways far from the Base
Station (BS) communicate with the BS via the gateways close to the BS. The energy of …
Station (BS) communicate with the BS via the gateways close to the BS. The energy of …
A novel image steganographic method based on integer wavelet transformation and particle swarm optimization
Image steganography is a technique of hiding secret data into a cover image and so as to
prevent the intruders from accessing the secret data. The efficiency of image steganography …
prevent the intruders from accessing the secret data. The efficiency of image steganography …
[HTML][HTML] Meta-heuristic techniques in microgrid management: A survey
As a small energy system, microgrid plays an important role in utilizing distributed energy
resources, improving traditional energy networks, and building intelligent integrated energy …
resources, improving traditional energy networks, and building intelligent integrated energy …
Security-aware dynamic scheduling for real-time optimization in cloud-based industrial applications
S Meng, W Huang, X Yin, MR Khosravi… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Nowadays, large number of cloud-based techniques have been used in industrial control
systems (ICS), which also brings many security threats. The emergence of security-aware …
systems (ICS), which also brings many security threats. The emergence of security-aware …