Computer methods for performance prediction in fuel cells

islanding detection methods for microgrids

امروزه استفاده از منابع انرژی پراکنده کاربرد وسیعی یافته است . اگر چه این منابع بسیاری از مشکلات شبکه را حل می کنند اما زیاد شدن آنها مسائل فراوانی برای سیستم قدرت به همراه دارد . استفاده از میکروشبکه راه حلی است که علاوه بر استفاده از مزایای منابع انرژی پراکنده برخی از مشکلات ایجاد شده توسط آنها را نیز منتفی می کند . همچنین میکروشبکه ها کیفیت برق و قابلیت اطمینان تامین انرژی مشترکان را افزایش ...

Implementation of Adaptive Neuro-Fuzzy Inference System (Anfis) for Performance Prediction of Fuel Cell Parameters

Fuel cells are potential candidates for storing energy in many applications; however, their implementation is limited due to poor efficiency and high initial and operating costs. The purpose of this research is to find the most influential fuel cell parameters by applying the adaptive neuro-fuzzy inference system (ANFIS). The ANFIS method is implemented to select highly influential parame...

2D Analytical Model for Direct Ethanol Fuel Cell Performance Prediction

Analytical models provide useful information for researchers to study fuel cell function. In this paper, it’s aimed to present a 2D analytical model for direct ethanol fuel cell (DEFC) performance. The model included equations inside diffusion layer, catalyst layer, and Ethanol cross-over through membrane, which all have been solved. Analytical model has been validated by some experimental tria...

Machine Learning Based Modeling for Solid Oxide Fuel Cells Power Performance Prediction

This study applies four different types of machine learning methods to model the power performance behaviour of a tubular solid oxide fuel cells (SOFC) under different operating conditions. The corresponding machine learning methods are: artificial neural network (ANN), fuzzy inference system (FIS), support vector machine (SVM), and genetic programming (GP). By using four types of inputs of the...

Computer-Based Methods of Inhibitor Prediction