W-IFL: An Improved Maximum Power Point Control Model to Promote Renewable-Powered Vehicles

Jin, Shuxin; Hao, Mai; Cai, Ming

doi:10.3390/app122211785

Cited by 2 publications

(2 citation statements)

References 45 publications

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“…The authors have extensive experience in classical statistical calculations related to energy production by photovoltaic systems. They also used recurrent neural networks to predict the amount of electricity produced from renewable energy sources for use in charging electric vehicles [122]. The metalog family of probability distributions turned out to be very effective, and the authors used it to select the power of the photovoltaic system for their electric vehicle and vice versa [123].…”

Section: Methodsmentioning

confidence: 99%

Strategic Model for Yellow Hydrogen Production Using the Metalog Family of Probability Distributions

Małek,

Dudziak,

Caban

et al. 2024

Energies

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Storing energy in hydrogen has been recognized by scientists as one of the most effective ways of storing energy for many reasons. The first of these reasons is the availability of technology for producing hydrogen from water using electrolytic methods. Another aspect is the availability of relatively cheap energy from renewable energy sources. Moreover, you can count on the availability of large amounts of this energy. The aim of this article is to support the decision-making processes related to the production of yellow hydrogen using a strategic model which exploits the metalog family of probability distributions. This model allows us to calculate, with accuracy regarding the probability distribution, the amount of energy produced by photovoltaic systems with a specific peak power. Using the model in question, it is possible to calculate the expected amount of electricity produced daily from the photovoltaic system and the corresponding amount of yellow hydrogen produced. Such a strategic model may be appropriate for renewable energy developers who build photovoltaic systems intended specifically for the production of yellow and green hydrogen. Based on our model, they can estimate the size of the photovoltaic system needed to produce the assumed hydrogen volume. The strategic model can also be adopted by producers of green and yellow hydrogen. Due to precise calculations, up to the probability distribution, the model allows us to calculate the probability of providing the required energy from a specific part of the energy mix.

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Section: Methodsmentioning

confidence: 99%

Strategic Model for Yellow Hydrogen Production Using the Metalog Family of Probability Distributions

Małek,

Dudziak,

Caban

et al. 2024

Energies

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“…The motivations of electric vehicle buyers are not yet well understood [3,44]. Ecological vehicle drives should be promoted and state governments should apply subsidies to the purchase of electric vehicles [20]. People who are afraid to buy an electric vehicle often buy hybrid vehicles [11].…”

Section: Introductionmentioning

confidence: 99%

The selection of an electric vehicle for the existing photovoltaic system - case study in Polish climatic conditions

Małek,

Marciniak,

Bartnik

2024

The Archives of Automotive Engineering – Archiwum Motoryzacji

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The article presents an algorithm for selecting an electric vehicle for your photovoltaic system. Generating electricity by distributed photovoltaic systems is a very visible trend across Europe. Individual and institutional owners are looking for opportunities to save large amounts of money spent on the purchase of electricity. Many times they have built a photovoltaic system larger than their current energy needs. The author suggests a solution to increase the energy produced for own needs instead of giving it to the power grid at unfavorable prices. Such a solution is the purchase of an electric vehicle that will be charged with surplus energy. Research on the selection of a vehicle for a photovoltaic system should start with a precise profile of the current energy consumption from the power grid, energy production from the photovoltaic system and transferring its excess to the power grid. The next step is to characterize the potential electric vehicle. Such characteristics include determination of the energy capacity of the traction battery and the methods of its charging. The final stage is the analytical confirmation of the choice made. For this purpose, the Metalog family of distributions was used to determine the probability of generating the appropriate hourly amount of energy needed to charge an electric vehicle.

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W-IFL: An Improved Maximum Power Point Control Model to Promote Renewable-Powered Vehicles

Cited by 2 publications

References 45 publications

Strategic Model for Yellow Hydrogen Production Using the Metalog Family of Probability Distributions

Strategic Model for Yellow Hydrogen Production Using the Metalog Family of Probability Distributions

The selection of an electric vehicle for the existing photovoltaic system - case study in Polish climatic conditions

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