Conceptual Framework of Antecedents to Trends on Permanent Magnet Synchronous Generators for Wind Energy Conversion Systems

Padmanathan, K.; Kamalakannan, N.; Padmanaban, Sanjeevikumar; Blaabjerg, Frede; Holm‐Nielsen, Jens Bo; Uma, G.; Arul, Rajakumar; Rajesh, R; Srinivasan, A.; Baskaran, J.

doi:10.3390/en12132616

Cited by 10 publications

(9 citation statements)

References 131 publications

(205 reference statements)

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“…where A indicates true range, A hg specifies true high value, and A lw represents true low value. Here, the term A is specified as, in Equation (11).…”

Section: Extraction Of Technical Indicatorsmentioning

confidence: 99%

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A Hybrid Sailfish Whale Optimization and Deep Long Short-Term Memory (SWO-DLSTM) Model for Energy Efficient Autonomy in India by 2048

Rajamoorthy¹,

Saraswathi²,

Devaraj³

et al. 2022

Sustainability

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In order to formulate the long-term and short-term development plans to meet the energy needs, there is a great demand for accurate energy forecasting. Energy autonomy helps to decompose a large-scale grid control into a small sized decisions to attain robustness and scalability through energy independence level of a country. Most of the existing energy demand forecasting models predict the amount of energy at a regional or national scale and failed to forecast the demand for power generation for small-scale decentralized energy systems, like micro grids, buildings, and energy communities. A novel model called Sailfish Whale Optimization-based Deep Long Short- Term memory (SWO-based Deep LSTM) to forecast electricity demand in the distribution systems is proposed. The proposed SWO is designed by integrating the Sailfish Optimizer (SO) with the Whale Optimization Algorithm (WOA). The Hilbert-Schmidt Independence Criterion (HSIC) is applied on the dataset, which is collected from the Central electricity authority, Government of India, for selecting the optimal features using the technical indicators. The proposed algorithm is implemented in MATLAB software package and the study was done using real-time data. The optimal features are trained using Deep LSTM model. The results of the proposed model in terms of install capacity prediction, village electrified prediction, length of R & D lines prediction, hydro, coal, diesel, nuclear prediction, etc. are compared with the existing models. The proposed model achieves percentage improvements of 10%, 9.5%,6%, 4% and 3% in terms of Mean Squared Error (MSE) and 26%, 21%, 16%, 12% and 6% in terms of Root Mean Square Error (RMSE) for Bootstrap-based Extreme Learning Machine approach (BELM), Direct Quantile Regression (DQR), Temporally Local Gaussian Process (TLGP), Deep Echo State Network (Deep ESN) and Deep LSTM respectively. The hybrid approach using the optimization algorithm with the deep learning model leads to faster convergence rate during the training process and enables the small-scale decentralized systems to address the challenges of distributed energy resources. The time series datasets of different utilities are trained using the hybrid model and the temporal dependencies in the sequence of data are predicted with point of interval as 5 years-head. Energy autonomy of the country till the year 2048 is assessed and compared.

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“…where A indicates true range, A hg specifies true high value, and A lw represents true low value. Here, the term A is specified as, in Equation (11).…”

Section: Extraction Of Technical Indicatorsmentioning

confidence: 99%

“…100% clean and efficient power can be achieved only if the above conditions are satisfied in a more corruption-free approach. Wind Energy Conversion System (WECS) based Permanent Magnet Synchronous Generator (PMSG) gained attention at the wind energy turbine for increased efficiency in power conversion [11].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Sailfish Whale Optimization and Deep Long Short-Term Memory (SWO-DLSTM) Model for Energy Efficient Autonomy in India by 2048

Rajamoorthy¹,

Saraswathi²,

Devaraj³

et al. 2022

Sustainability

Self Cite

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show abstract

“…Future projections foresee turbines up to 250−300 m hub height. Ramanathan et al present projections of wind turbines with 250 m hub height and 20 MW capacity in an attempt of discussing improvements in wind energy conversion systems to increase exploitable wind electricity potential (Radmanathan et al, 2019). A survey discussing the decreases in wind electricity costs indicates expected hub height rises as one of the main reasons (Wiser et al, 2021).…”

Section: Technology Specifics and Considerations In The Studymentioning

confidence: 99%

Exploitable wind power potential in Turkey with technological advancement and resulting environmental-economic aspects

Kursun

2022

Energy Exploration & Exploitation

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This work's focus is determining how the improvements in wind power technology alter current onshore wind power potential and exploitable electrical energy in Turkey. Then, consequent environmental and economic benefits through substitution of imported hard coal, natural gas and local lignite resources in the Turkish electricity mix have been analyzed. Lack of potential, environmental and economic data kept offshore wind calculations out of the scope of this work. Increasing hub height and power coefficient due to better blade designs of wind turbines can increase 114 thousand MW of onshore wind power potential at 50 m up to 418 thousand MW at 300 m. Consequent wind electricity generation can change in the range of 2.3 × 105–1.95 × 106 GWh. Acknowledging several different conditions operating wind turbines can be subject to and that the whole capacity may not be used, mean value of 1.09 × 106 GWh wind electricity generation is assessed as the limit providable to the Turkish electricity grid. Installable wind power capacity (IWPC) and electricity generation potential (EGP) are both most sensitive to the changes in spacing followed by CP and aging. The level of sensitivity increases at higher hub heights for both IWPC and EGP. Environmentally, substitution of lignite and after 2040 hard coal and lignite by wind power is the most feasible option in improving environmental performance of Turkish electricity mix compared to sole substitution of hard coal, natural gas or lignite. In 2040, wind can replace all lignite hence in the years following 2040, wind can substitute lignite and a second fossil resource. Economically, hard coal and natural gas substitution result in 10.85 billion $ and 7.93 billion $ gain from 2021to 2050. Local job creation and carbon tax mechanisms to be employed in favor of wind power can create additional economic and social benefits for the country.

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“…The principle of vector control with voltage supply and current control makes it possible to impose the torque. However, regardless of the purpose of the control (torque, speed, or position control), current monitoring is still necessary (Padmanathan et al, 2019).…”

Section: Field-oriented Control Of Pmsgmentioning

confidence: 99%

Optimal tuning of proportional–integral controller using particle swarm optimization algorithm for control of permanent magnet synchronous generator based wind turbine with tip speed ratio for maximum power point tracking

et al. 2020

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This article deals with the study of the particle swarm optimization algorithm and its variants. After modeling the global system, a comparative study is carried out about the algorithms described in order to choose the best of those to be used thereafter. Then, the perturbed particle swarm optimization is presented to determine the optimal parameters of the proportional–integral controller for speed control to certify the tip speed ratio for maximum power point tracking of a wind energy conversion system. A numerical simulation is used in conjunction with the particle swarm optimization algorithm to determine the proportional–integral controller optimal parameters. From the simulations results, we observe that the proportional–integral controller designed with particle swarm optimization gives better results compared to the traditional method (proportional–integral manually) in terms of the performance index.

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Conceptual Framework of Antecedents to Trends on Permanent Magnet Synchronous Generators for Wind Energy Conversion Systems

Cited by 10 publications

References 131 publications

A Hybrid Sailfish Whale Optimization and Deep Long Short-Term Memory (SWO-DLSTM) Model for Energy Efficient Autonomy in India by 2048

A Hybrid Sailfish Whale Optimization and Deep Long Short-Term Memory (SWO-DLSTM) Model for Energy Efficient Autonomy in India by 2048

Exploitable wind power potential in Turkey with technological advancement and resulting environmental-economic aspects

Optimal tuning of proportional–integral controller using particle swarm optimization algorithm for control of permanent magnet synchronous generator based wind turbine with tip speed ratio for maximum power point tracking

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