Logical Analysis on the Strategy for a Sustainable Transition of the World to Green Energy—2050. Smart Cities and Villages Coupled to Renewable Energy Sources with Low Carbon Footprint

Chenic, Alina Ştefania; Creţu, Alin Ioan; Burlacu, Adrian; Moroianu, Nicolae; Virjan, Daniela; Huru, Dragos; Stanef-Puica, Mihaela Roberta; Enăchescu, Vladimir Aurelian

doi:10.3390/su14148622

Cited by 26 publications

(5 citation statements)

References 36 publications

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“…renewable energy development has become the core of many countries' energy transition strategies [3].…”

Section: Introductionmentioning

confidence: 99%

Anomaly detection in wind turbine blades based on PCA and convolutional kernel transform models: employing multivariate SCADA time series analysis

Meng,

Gao,

Yuan

et al. 2024

Meas. Sci. Technol.

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With the widespread application of wind power technology, the detection of abnormalities in wind turbine blades has become a key research area. The use of data from monitoring and data acquisition (SCADA) systems for data-driven fault detection research presents new challenges. This study utilizes short-term SCADA data from wind turbine generators to classify the blade abnormal and normal operational states, thereby introducing a new method called PCABSMMR. This strategy integrates principal component analysis (PCA) and borderline-synthetic minority over-sampling technique (Borderline-SMOTE) for data processing and utilizes an improved multi-dimensional time series classification (MTSC) model. It combines one-dimensional convolution from deep learning with shallow learning's rigid classifiers. PCA is used for dimensionality reduction, while Borderline-SMOTE expands the samples of minority class fault instances. Comparative analysis with various methods shows that the proposed method has an average F1-score of 0.98, outperforming many state-of-the-art MTSC models across various evaluation metrics.

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“…renewable energy development has become the core of many countries' energy transition strategies [3].…”

Section: Introductionmentioning

confidence: 99%

Anomaly detection in wind turbine blades based on PCA and convolutional kernel transform models: employing multivariate SCADA time series analysis

Meng,

Gao,

Yuan

et al. 2024

Meas. Sci. Technol.

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“…At the same time, the development of new energy vehicles in the world has entered an irreversible period, and China will be in a leading position for a long time 3 . The theme of automotive industry transition in the past 10 years is electrification, and it has become a consensus among countries and enterprises around the world that the future direction of automotive development is new energy 4–6 . Cities are not only centers of energy load but also major sources of carbon emissions.…”

Section: Introductionmentioning

confidence: 99%

“…3 The theme of automotive industry transition in the past 10 years is electrification, and it has become a consensus among countries and enterprises around the world that the future direction of automotive development is new energy. [4][5][6] Cities are not only centers of energy load but also major sources of carbon emissions. They are also key regions for transitional development.…”

Section: Introductionmentioning

confidence: 99%

Model building of urban energy system and effect analysis of green low‐carbon transition under the background of carbon peaking and carbon neutrality

Zhao

Liu

Hou

2023

Engineering Reports

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Under the carbon peaking and carbon neutrality goals background in China, cities are the main force of energy consumption and carbon emission, and their low‐carbon transition development has become the primary task of urban planning. The transitional development of cities not only puts forward higher requirements for the output proportion of new energy, but also puts forward higher requirements for the flexibility of energy system. This paper proposes an optimization model of urban energy system considering the uncertainty output of new energy and new energy vehicles. The uncertainty and operational flexibility of electric vehicles are taken into account at the planning level by using stochastic optimization method. The model considers the expansion and retirement of new energy units and various conversion devices in urban energy system, and ensures the achievement of carbon peaking and carbon reduction goals by imposing constraints on electric vehicles. The case results show that this model can effectively improve the economy and new energy consumption rate of urban energy system, and can meet the carbon reduction demand.

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“…With the emission of carbon dioxide and various harmful gases, it seriously endangers the safety of the earth's environment. Facing the disharmonious development of global climate caused by energy problems, as of 12 June 2020, 125 countries in the world have promised to achieve the goal of carbon neutrality by the middle of the 21st century (Chenic et al, 2022). Therefore, streamlining the energy structure and improving energy utilization have become the joint efforts of scholars and researchers all over the world.…”

Section: Introductionmentioning

confidence: 99%

Research on optimized SOC estimation algorithm based on extended kalman filter

Yang

Tang

et al. 2022

Front. Energy Res.

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The paper studies the estimation of state of charge (SOC) of batteries. Firstly, the research status of battery management system, battery equivalent model and SOC estimation algorithm is introduced, and the performance of common equivalent circuit model and SOC estimation algorithm in complexity and accuracy is compared and analyzed. On this basis, this paper proposes an extended Kalman filter (EKF) algorithm based on the first-order RC model, and optimizes it by piecewise fitting. The accuracy of the optimized EKF algorithm is greatly improved. Finally, the modeling and simulation are completed through MATLAB/SIMULINK, and the experimental platform is designed and built to test the SOC estimation algorithm based on EKF. The simulation and experimental results verify the accuracy of the estimation algorithm.

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Logical Analysis on the Strategy for a Sustainable Transition of the World to Green Energy—2050. Smart Cities and Villages Coupled to Renewable Energy Sources with Low Carbon Footprint

Cited by 26 publications

References 36 publications

Anomaly detection in wind turbine blades based on PCA and convolutional kernel transform models: employing multivariate SCADA time series analysis

Anomaly detection in wind turbine blades based on PCA and convolutional kernel transform models: employing multivariate SCADA time series analysis

Model building of urban energy system and effect analysis of green low‐carbon transition under the background of carbon peaking and carbon neutrality

Research on optimized SOC estimation algorithm based on extended kalman filter

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