Economical planning of fuel cell vehicle-to-grid integrated green buildings with a new hybrid optimization algorithm

摘要

Popularity of fuel cell electric vehicles (FCVs) is an important criterion for solving the global problem of reducing CO2 emissions. However, the overall cost of FCVs and hydrogen fuel production is relatively high, so FCV promotion is slow. Considering that FCVs have near-zero CO2 emissions and high endurance, which is suitable for vehicle-to-grid (V2G) systems, this study aims to analyze the economic potential of the fuel cell vehicle-to-grid (FCV2G) systems to promote FCVs to the highest level. For this purpose, a large-scale green building was first selected as the research target and an agent to provide V2G services for the power grid. Then, Monte Carlo method was used to simulate the vehicle visiting time. A discharge model was also developed. Considering CO2 emission price and self-elasticity coefficient of discharge price, an overall economic optimization model was presented. Then, the hybrid algorithm of competitive swarm optimization (CSO) and imperialist competitive algorithm (ICA) was applied to optimize the model, which not only led to definite results and reduced standard deviation, but also eliminated the weakness of the CSO, i.e., convergence speed and poor performance in some benchmark functions. The simulation results indicated the proposed algorithm had faster convergence and more accuracy in finding the optimal solution than other optimization algorithms. Moreover, the overall economic profit improved in the presence of FCVs. Finally, sensitivity analysis was performed on six parameters, including daily electricity price, battery cost, fuel cell cost, CO2 emission price, power grid carbon emission, and hydrogen cost. The results showed FCV2G system had high development potential as well as great economic profit increasing over time. (C) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.