Fitting regression model and experimental validation for high pressure PEM electrolyzer
نویسندگان
چکیده
منابع مشابه
Investigation of vessels pressure effect on PEM electrolyzer performance by using a new OneDimensional Dynamic Model
In recent years energy shortage and environmental impacts due to consuming fossil fuels have led to developing renewable energy sources systems. Since these sources are not reliable and are usually time dependent, an energy storing system like hydrogen production is required. In this regard, PEM electrolyzer can be efficiently used to decompose liquid water into hydrogen and oxygen. Because of ...
متن کاملHigh-efficiency Steam Electrolyzer
We are developing a novel high-efficiency, high-temperature steam electrolyzer. Although water or steam electrolysis is well known to be one of the cleanest ways to produce hydrogen, widespread utilization is hindered by high operational costs because of high electricity consumption. To decrease the electrical power input requirements in electrolysis, our approach uses natural gas as an anode d...
متن کاملHigh Efficiency Steam Electrolyzer
A novel steam electrolyzer has been developed. In conventional electrolyzers, oxygen produced from electrolysis is usually released in the air stream. In our novel design, natural gas is used to replace air in order to reduce the chemical potential difference across the electrolyzer, thus minimizing the electrical consumption. The oxygen from the electrolysis is consumed in either a total oxida...
متن کاملEffect of Water Transport on the Production of Hydrogen and Sulfuric Acid in a PEM Electrolyzer
The thermochemical cycle involving the interconversion between sulfur dioxide and sulfuric acid is a promising method for efficient, large-scale production of hydrogen. A key step in the process is the oxidation of sulfur dioxide to sulfuric acid in an electrolyzer. Gaseous SO2 fed to a proton exchange membrane PEM electrolyzer was previously investigated and was shown to be a promising system ...
متن کاملRegression Model Fitting under Differential Privacy and Model Inversion Attack
Differential privacy preserving regression models guarantee protection against attempts to infer whether a subject was included in the training set used to derive a model. It is not designed to protect attribute privacy of a target individual when model inversion attacks are launched. In model inversion attacks, an adversary uses the released model to make predictions of sensitive attributes (u...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Renewable Energy and Power Quality Journal
سال: 2009
ISSN: 2172-038X
DOI: 10.24084/repqj07.373