Modeling and optimization of a residential PEMFC-based CHP system under different operating modes

Abstract

Proton exchange membrane fuel cell (PEMFC)-based combined heat and power (CHP) system can improve the system overall efficiency. In this study, with the electrical and thermal demand curves from a survey of 500 households as the input, a residential PEMFC-based CHP system is numerically studied to explore the system operating characteristics under different operating modes, including constant-power output, electrical-led output, and stepped electrical-led output. Effects of structural and operating parameters, such as tank volume, tank temperature, PEMFC temperature, and environmental temperature, are studied. The system performance is evaluated based on CHP efficiency, matching degree, and hydrogen consumption. The results show that while the optimal CHP efficiency is higher under the constant-power output mode, the corresponding matching degree is lower and the hydrogen consumption rate is higher. A new hybrid mode is proposed to combine the advantages of different modes, achieving both higher efficiency and matching degree. Additionally, the CHP system is compared with a conventional energy supply system in terms of carbon emission and operating costs. The critical hydrogen price for a more cost-effective CHP system than the conventional system is calculated. Furthermore, a dataset is utilized to establish the relationship between CHP efficiency and key input parameters, and an artificial neural network (ANN) model is developed to predict CHP efficiency. The ANN model demonstrates a high accuracy of 98.5% and is coupled with the genetic algorithm to optimize the system, leading to the final CHP efficiency of 95.62%.