Syrian Arab Republic
Design and Simulation Studies of Hybrid Power Systems Based on Photovoltaic, Wind, Electrolyzer, and PEM Fuel Cells
May 2021
Publication
In recent years the need to reduce environmental impacts and increase flexibility in the energy sector has led to increased penetration of renewable energy sources and the shift from concentrated to decentralized generation. A fuel cell is an instrument that produces electricity by chemical reaction. Fuel cells are a promising technology for ultimate energy conversion and energy generation. We see that this system is integrated where we find that the wind and photovoltaic energy system is complementary between them because not all days are sunny windy or night so we see that this system has higher reliability to provide continuous generation. At low load hours PV and electrolysis units produce extra power. After being compressed hydrogen is stored in tanks. The purpose of this study is to separate the Bahr AL-Najaf Area from the main power grid and make it an independent network by itself. The PEM fuel cells were analyzed and designed and it were found that one layer is equal to 570.96 Watt at 0.61 volts and 1.04 A/Cm2 . The number of layers in one stack is designed to be equal to 13 layers so that the total power of one stack is equal to 7422.48 Watt. That is the number of stacks required to generate the required energy from the fuel cells is equal to 203 stk. This study provided an analysis of the hybrid system to cover the electricity demand in the Bahr AL-Najaf region of 1.5 MW the attained hybrid power system TNPC cost was about 9573208 USD whereas the capital cost and energy cost (COE) were about 7750000 USD and 0.169 USD/kWh respectively for one year.
Robust Control for Techno-economic Efficiency Energy Management of Fuel Cell Hybrid Electric Vehicles
Apr 2022
Publication
The design of an efficient techno-economic autonomous fuel cell hybrid electric vehicle(FCHEV) is a crucial challenge. This paper investigates the design of a near optimal PI controller for an automated FCHEV where autonomy is expressed as efficient and robust tracking of a given reference speed trajectory without driver’s intervention. An impartial comparison is introduced to illustrate the effectiveness of the proposed metaheuristic-based optimal controllers in enhancing the system dynamic performance. The comprehensive optimization performance indicator is considered as a function of the vehicle dynamic characteristics while determining the optimal controller gains. In this paper the proposed effective up-to-date metaheuristic techniques are the grey wolf optimization (GWO) as well as the artificial bee colony (ABC). Using MATLAB TM /Simulink numerical simulations clearly illustrate the efficiency of near-optimal gains in the optimized tuning methodologies and the fixed manual one in realizing adequate velocity tracking. The simulation results demonstrate the superiority of both ABC and GWO rather than the manual controller for driving cycles of high acceleration and deceleration levels. In absence of these latter the manual defined gain controller is considered sufficient. Through a comprehensive sensitivity analysis the robustness of both metaheuristic-based controllers is verified under diverse driving cycles of different operation features and nature. Despite GWO results in better dynamic characteristics the ABC provides more economical feature with about 1.5% compared to manual system in extra urban driving cycle. However manual-controller has the minimum fuel cost under the United States driving cycle developed by the environmental protection agency as a New York city cycle(US EPA NYCC) and urban driving cycle (ECE). Ecologically electric vehicles have an environmentally friendly effect especially when driven with green hydrogen. Autonomous vehicles involving velocity control systems would raise car share and provide more comfort.
No more items...