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Predictive digital twin technologies for achieving net zero carbon emissions: a critical review and future research agenda
Purpose Predictive digital twin technology, which amalgamates digital twins (DT), the
internet of Things (IoT) and artificial intelligence (AI) for data collection, simulation and …
internet of Things (IoT) and artificial intelligence (AI) for data collection, simulation and …
Electricity theft detection and prevention using technology-based models: A systematic literature review
Electricity theft comes with various disadvantages for power utilities, governments,
businesses, and the general public. This continues despite the various solutions employed …
businesses, and the general public. This continues despite the various solutions employed …
Forecasting energy consumption of a public building using transformer and support vector regression
J Huang, S Kaewunruen - Energies, 2023 - mdpi.com
Most of the Artificial Intelligence (AI) models currently used in energy forecasting are
traditional and deterministic. Recently, a novel deep learning paradigm, called 'transformer' …
traditional and deterministic. Recently, a novel deep learning paradigm, called 'transformer' …
Electricity demand error corrections with attention bi-directional neural networks
Reliable forecast of electricity demand is crucial to stability, supply, and management of
electricity grids. Short-term hourly and sub-hourly demand forecasts are difficult due to the …
electricity grids. Short-term hourly and sub-hourly demand forecasts are difficult due to the …
Deep anomaly detection framework utilizing federated learning for electricity theft zero-day cyberattacks
Smart power grids suffer from electricity theft cyber-attacks, where malicious consumers
compromise their smart meters (SMs) to downscale the reported electricity consumption …
compromise their smart meters (SMs) to downscale the reported electricity consumption …
[HTML][HTML] Electricity theft detection in smart grids using a hybrid BiGRU–BiLSTM model with feature engineering-based preprocessing
In this paper, a defused decision boundary which renders misclassification issues due to the
presence of cross-pairs is investigated. Cross-pairs retain cumulative attributes of both …
presence of cross-pairs is investigated. Cross-pairs retain cumulative attributes of both …
Implementation of an ADALINE-based adaptive control strategy for an LCLC-PV-DSTATCOM in distribution system for power quality improvement
S Mishra, S Rajashekaran, PK Mohan, SM Lokesh… - Energies, 2022 - mdpi.com
This study investigated the problem of controlling a three-phase three-wire photovoltaic (PV)-
type distribution static compensator (DSTATCOM). In order to model, simulate, and control …
type distribution static compensator (DSTATCOM). In order to model, simulate, and control …
[HTML][HTML] Advances on smart cities and smart buildings
Modern cities are facing the challenge of combining competitiveness on a global city scale
and sustainable urban development to become smart cities. A smart city is a hightech …
and sustainable urban development to become smart cities. A smart city is a hightech …
Forecasting EV Market Trends in India: A Deep Learning Approach for Two/Three-Wheelers
This research paper presents a comprehensive analysis of machine learning models for
predicting future sales of electric vehicles (EVs) in the Indian Market. With a specific focus on …
predicting future sales of electric vehicles (EVs) in the Indian Market. With a specific focus on …
基于 ISSA-NESN 的可再生能源电力需求预测研究
夏雨烁， 张新生， 王明虎 - 电网与清洁能源, 2023 - epjournal.csee.org.cn
首先将标准麻雀搜索算法SSA 加入Tent 混沌映射以及动态步长因子得到优化的麻雀搜索算法
ISSA, 以提高种群的多样性并调节种群的全局搜索能力与局部开发能力. 然后 …
ISSA, 以提高种群的多样性并调节种群的全局搜索能力与局部开发能力. 然后 …