Current Status Investigation and Predicting Carbon Dioxide Emission in Latin American Countries by Connectionist Models

Ahmadi, Mohammad Hossein; Madvar, Mohammad Dehghani; Sadeghzadeh, Milad; Rezaei, Mohammad Hossein; Herrera, Manuel; Shamshirband, Shahaboddin

doi:10.3390/en12101916

Cited by 26 publications

(6 citation statements)

References 89 publications

(113 reference statements)

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“…The diagram is illustrated in Figure 1. The governing mechanical power output of a WT is given in (1). WECS consists of WT, gearbox, generator, voltage source converters, and a power transformer.…”

Section: Wind Energy Conversion System (Wecs)mentioning

confidence: 99%

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Optimization Techniques of DFIG Controller Design for Wind Energy Conversion Systems

Bharti

2024

Preprint

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The Doubly-Fed Induction Generator (DFIG) is suggested for Wind Energy Conversion System (WECS) to extract wind power. DFIG is preferably employed due to its robustness towards variable wind and rotor speed. DFIG has the adaptable property because the system parameters are smoothly dealt with, including real power, reactive power, DC-link voltage, and the transient and dynamic responses, which are needed to analyze constantly. The analysis becomes more prominent during any unusual condition in the electrical power system. Hence, the study and improvement in the system parameters and transient response performance of DFIG are required to be accomplished using some controlling techniques. For fulfilling the task, the present work implements and compares the optimization methods for the design of the DFIG controller for WECS. The bio-inspired optimization techniques are applied to get the optimal controller design parameters for DFIG-based WECS. The optimized DFIG controllers are then used to retrieve the transient response performance of the six-order DFIG model with a step input. The results using MATLAB/Simulink show the betterment of the Firefly algorithm (FFA) over other control techniques when compared with the other controller design methods.

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Section: Wind Energy Conversion System (Wecs)mentioning

confidence: 99%

“…Renewable energy sources take over the traditional sources of electrical power generation. The prime causes to utilize renewable are the depletion of earth's energy resources and Greenhouse Gas Emissions (GHG) [1] - [3]. Wind energy is the most important favourable basis of renewable energy.…”

Section: Introductionmentioning

confidence: 99%

Optimization Techniques of DFIG Controller Design for Wind Energy Conversion Systems

Bharti

2024

Preprint

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“…Secondly, the research direction of carbon emissions mainly focuses on three aspects: the current status of carbon emissions (Xu et al, 2019), carbon peak prediction (Wang and Feng, 2024), and the influencing factors of carbon emissions (Tong, 2020;Xu, 2023). Firstly, the analysis of the current status of carbon emissions focuses on industries with high carbon concentration, regions with high carbon emissions, the carbon emissions of a certain region under China's 2030 carbon peak target, and the carbon emissions tracking of a specific location or factory (Li et al, 2016;Ahmadi et al, 2019). Secondly, regarding the research on carbon peak prediction, most of the previous researchers used big data models and scenario analysis methods to predict the future growth of carbon emissions.…”

Section: Literature Reviewmentioning

confidence: 99%

The spatial effect of integrated economy on carbon emissions in the era of big data: a case study of China

Wang,

Ke,

Lei

2024

Front. Ecol. Evol.

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The digital economy has the characteristics of resource conservation, which can solve China’s high carbon emissions problems. The digital economy can quickly integrate with the real economy, forming an integrated economy. However, it is still unclear whether an integrated economy can effectively reduce carbon emissions and achieve China’s ‘dual carbon goals’. Therefore, this study takes 30 provinces in China as the research object, constructs the integration economy index system through the statistical data from 2011-2021, and explores the spatial effect of the impact of the integration economy on carbon emissions by using principal component analysis, coupled coordination model and spatial econometric model. The research results are as follows. (1) From 2011 to 2021, the comprehensive economy showed a trend of increasing yearly (from 0.667 to 0.828), and carbon emissions showed a slow decrease (from 0.026 to 0.017). (2) Due to the infiltration of China’s economic development from the eastern to the western, the spatial distribution of the integrated economy shows a decreasing trend from east to west. The spatial distribution of carbon emissions may be related to China’s industrial layout of heavy industry in the northern, and light industry in the southern, showing a trend of low in the south and high in the north. (3) The integrated economy can significantly reduce carbon emissions (the coefficients of influence, -0.146), and the reduction effect will be more obvious if spatial spillover effects are taken into account (-0.305). (4) The eastern coast, the middle reaches of the Yangtze River, and the middle reaches of the Yellow River economic zones all increase carbon emissions at a certain level of significance (0.065, 0.148, and 3.890). The Northeast, South Coastal and Southwest economic zones significantly reduce carbon emissions (-0.220, -0.092, and -0.308). The results of the Northern Coast and Northwest are not significant (-0.022 and 0.095). (5) China should tailor regional economic development policies, such as strengthening investment in digital infrastructure in the Northwest Economic Zone and fully leveraging the spatial spillover effects of integrated economy in the Northeast, Southern Coastal, and Southwest Economic Zones to reduce carbon emissions.

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“…The conventional sources of electrical power generation are adopted by renewable energy sources. The main reasons to use renewable are the reduction of earth's energy sources as well as the emission of greenhouse gases (GHG) [1–4]. The main sources of GHG emission are transportation and electricity generation plants.…”

Section: Introductionmentioning

confidence: 99%

Controller design for DFIG‐based WT using gravitational search algorithm for wind power generation

Bharti

Sarita

Vardhan³

et al. 2021

IET Renewable Power Gen

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This paper describes the controller design aspects of DFIG-based wind turbine system (WTS) using gravitational search algorithm (GSA). The appropriate control schemes are required for efficient and reliable functioning of the DFIG-based wind energy conversion system (WECS). The control algorithms are implemented in converters which are placed in the rotor end and grid side of the WECS. The controller design schemes are optimized for accurate, reliable and stable operations of WECS using GSA. The most commonly used other design techniques are bacterial foraging optimization (BFO), and particle swarm optimization (PSO). Moreover, the transfer function modeling of DFIG is also described in this paper. The results show that the proposed GSA technique with sixths order transfer function model of DFIG improves the transient performance including time of rising the response to 90%, settling time, and amplitude of peak overshoot. The proposed GSA technique is compared with the techniques already implemented in the previous research works including PSO and BFO. The DFIG-based WTS's output waveforms of voltage at dc-link, reactive power, and active power are improved using GSA based design technique. Finally, it is concluded that the GSA technique gives better results as compared with the PSO and BFO techniques.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Current Status Investigation and Predicting Carbon Dioxide Emission in Latin American Countries by Connectionist Models

Cited by 26 publications

References 89 publications

Optimization Techniques of DFIG Controller Design for Wind Energy Conversion Systems

Optimization Techniques of DFIG Controller Design for Wind Energy Conversion Systems

The spatial effect of integrated economy on carbon emissions in the era of big data: a case study of China

Controller design for DFIG‐based WT using gravitational search algorithm for wind power generation

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