Optimization of the economic-technical model for hydrogen production with an approach to utilizing solar power plants and waste-to-energy conversion

Mohammad Hossein Gholizadeh, Hossein Yousefi, Ahmad Hajinezhad, Mahmood Abdoos
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Abstract

The present research work is related to the optimization of a hybrid renewable energy system, combining Waste-to-Energy (WTE) and Photovoltaic (PV) technologies for hydrogen production by means of water electrolysis in both on-grid and off-grid operation modes. A WTE plant of 3 MW rated capacity is combined with a PV array of capacity varying from 0.5 to 3 MW. The Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Simulated Annealing (SA), Gradient Descent, and Newton's Method algorithms were used to minimize Levelized Cost of Hydrogen (LCOH) while ensuring energy reliability. In the on-grid scenario, the minimum LCOH of around -399.215 $/kg was achieved by PSO, GA, and SA, which indicates cost-effectiveness with the help of grid exportation and importation. Whereas, in the off-grid case, LCOH values are higher: the minimum value of LCOH by PSO, GA, and SA was 34.81 $/kg, while the highest was obtained from Gradient Descent with 42.85 $/kg. The main problems that the configuration faced in an off-grid setting were related to not being able to satisfy energy demand and increased curtailment rates. These findings evidence the economic advantages of on-grid systems and underline the necessity for additional measures in off-grid setups, such as energy storage, to reach higher performance and reliability.
利用太阳能发电厂和废物转化能源的制氢经济技术模型优化
目前的研究工作涉及到一个混合可再生能源系统的优化,该系统将废物发电(WTE)和光伏(PV)技术结合起来,在并网和离网两种运行模式下通过水电解制氢。额定容量为3mw的WTE电厂与容量从0.5到3mw的光伏阵列相结合。采用粒子群优化(PSO)、遗传算法(GA)、模拟退火(SA)、梯度下降(Gradient Descent)和牛顿法(Newton’s Method)算法,在保证能源可靠性的同时最小化氢的平准化成本(LCOH)。在并网场景下,PSO、GA和SA的最低LCOH约为-399.215美元/kg,这表明在电网进出口的帮助下,成本效益显著。离网条件下,PSO、GA和SA的LCOH最小值为34.81 $/kg,梯度下降法的LCOH最大值为42.85 $/kg。在离网环境下,该配置面临的主要问题与无法满足能源需求和弃风率增加有关。这些发现证明了并网系统的经济优势,并强调了在离网装置中采取额外措施(如储能)以达到更高性能和可靠性的必要性。
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