Utilisation of alkaline electrolysers in existing distribution networks to increase the amount of integrated wind capacity

Kiaee, Mahdi; Infield, David; Cruden, Andrew

doi:10.1016/j.est.2017.12.018

Cited by 23 publications

(10 citation statements)

References 28 publications

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“…Such hydrogen energy systems or alkaline water electrolyzers can be used to stabilize the power frequency by damping the fluctuations. An additional benefit would be the reduction of the conventional spinning reserve, which reduces costs and CO 2 emissions [87,90]. A predictive control can be used for stable and efficient operation.…”

Section: Hydrogen Energy System and Power Grid Stabilizationmentioning

confidence: 99%

Alkaline Water Electrolysis Powered by Renewable Energy: A Review

2020

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Alkaline water electrolysis is a key technology for large-scale hydrogen production powered by renewable energy. As conventional electrolyzers are designed for operation at fixed process conditions, the implementation of fluctuating and highly intermittent renewable energy is challenging. This contribution shows the recent state of system descriptions for alkaline water electrolysis and renewable energies, such as solar and wind power. Each component of a hydrogen energy system needs to be optimized to increase the operation time and system efficiency. Only in this way can hydrogen produced by electrolysis processes be competitive with the conventional path based on fossil energy sources. Conventional alkaline water electrolyzers show a limited part-load range due to an increased gas impurity at low power availability. As explosive mixtures of hydrogen and oxygen must be prevented, a safety shutdown is performed when reaching specific gas contamination. Furthermore, the cell voltage should be optimized to maintain a high efficiency. While photovoltaic panels can be directly coupled to alkaline water electrolyzers, wind turbines require suitable converters with additional losses. By combining alkaline water electrolysis with hydrogen storage tanks and fuel cells, power grid stabilization can be performed. As a consequence, the conventional spinning reserve can be reduced, which additionally lowers the carbon dioxide emissions.

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Section: Hydrogen Energy System and Power Grid Stabilizationmentioning

confidence: 99%

Alkaline Water Electrolysis Powered by Renewable Energy: A Review

2020

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“…To the best of our knowledge, there are few studies focusing on forecasting wind turbine capacity (Cheng et al , 2017; Xia et al , 2020), as accurately forecasting wind turbine capacity is of great significance for policy-making and policy-planning (Kiaee et al , 2018; Wang and Li, 2019). One of the salient contributions of this paper is to explore a common and reliable approach for forecasting wind turbine capacity and then to offer data support for policy decisions.…”

Section: Literature Reviewmentioning

confidence: 99%

A novel fractional discrete nonlinear grey Bernoulli model for forecasting the wind turbine capacity of China

Xie

Liu

et al. 2021

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PurposeA new method for forecasting wind turbine capacity of China is proposed through grey modelling technique.Design/methodology/approachFirst of all, the concepts of discrete grey model are introduced into the NGBM(1,1) model to reduce the discretization error from the differential equation to its discrete forms. Then incorporating the conformable fractional accumulation into the discrete NGBM(1,1) model is carried out to further improve the predictive performance. Finally, in order to effectively seek the emerging coefficients, namely, fractional order and nonlinear coefficient, the whale optimization algorithm (WOA) is employed to determine the emerging coefficients.FindingsThe empirical results show that the newly proposed model has a better prediction performance compared to benchmark models; the wind turbine capacity from 2019 to 2021 is expected to reach 275954.42 Megawatts in 2021. According to the forecasts, policy suggestions are provided for policy-makers.Originality/valueBy combing the fractional accumulation and the concepts of discrete grey model, a new method to improve the prediction performance of the NGBM(1,1) model is proposed. The newly proposed model is firstly applied to predict wind turbine capacity of China.

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“…Consequently, power quality is not guaranteed. To address this challenge, wind power installed capacity prediction, manual guidance of wind farm operation, and reasonable scheduling are valid methods to lessen the effect of wind power upon the grid when it is connected to the grid [37,38].…”

Section: Simulation and Forecastingmentioning

confidence: 99%

Forecasting Chinese Wind Power Installed Capacity Using a Novel Grey Model with Parameters Combination Optimization

Luo

Zeng

et al. 2021

Journal of Mathematics

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The intermittent and uncertain characteristics of wind generation have brought new challenges for the hosting capacity and the integration of large-scale wind power into the power system. Consequently, reasonable forecasting wind power installed capacity (WPIC) is the most effective and applicable solution to meet this challenge. However, the single parameter optimization of the conventional grey model has some limitations in improving its modeling ability. To this end, a novel grey prediction model with parameters combination optimization is proposed in this paper. Firstly, considering the modeling mechanism and process, the order of accumulation generation of the grey prediction model is optimized by Particle Swarm Optimization (PSO) Algorithm. Secondly, as different orders of accumulation generation correspond to different parameter matrixes, the background value coefficient of the grey prediction model is optimized based on the optimal accumulation order. Finally, the novel model of combinational optimization is employed to simulate and forecast Chinese WPIC, and the comprehensive error of the novel model is only 1.34%, which is superior to the other three grey prediction models (2.82%, 1.68%, and 2.60%, respectively). The forecast shows that China’s WPIC will keep growing in the next five years, and some reasonable suggestions are put forward from the standpoint of the practitioners and governments.

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Utilisation of alkaline electrolysers in existing distribution networks to increase the amount of integrated wind capacity

Cited by 23 publications

References 28 publications

Alkaline Water Electrolysis Powered by Renewable Energy: A Review

Alkaline Water Electrolysis Powered by Renewable Energy: A Review

A novel fractional discrete nonlinear grey Bernoulli model for forecasting the wind turbine capacity of China

Forecasting Chinese Wind Power Installed Capacity Using a Novel Grey Model with Parameters Combination Optimization

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