基于模型预测控制的风氢混合动力系统最优调度

Weiwei Wang, Chunjun Huang, Y. Zong
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引用次数: 0

摘要

为了实现脱碳,丹麦在电力到氢(P2H)技术的支持下,利用巨大的风能,推动了绿色氢的发展。P2H技术通过水电解将可再生能源中的电能转化为绿色氢气,通过回收其余热来提高其工作效率,可称为电氢热(P2HH)。本文将P2HH应用于大型碱性电解槽,实现了产消电、产氢、产热并作。建立了基于P2HH技术的风氢混合动力系统的数学模型,并采用经济模型预测控制(EMPC)策略对该系统的最优调度进行了经济性能研究。利用丹麦博恩霍尔姆能源岛的真实历史数据,仿真结果表明,EMPC控制器在各种系统配置、氢价格权重、循环热约束和工作温度约束等方面具有鲁棒性,能够实现最优的电力消耗、能源成本节约和最佳经济效益。在这些配置中,不受回收热量和氢气价格重量的限制,在研究案例中,60-90°C工作的电解槽可以获得最大的利润。
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Model Predictive Control based Optimal Dispatch of Wind and Hydrogen Hybrid Systems
To realize decarbonization, green hydrogen has been boosted in Denmark with the support of power to hydrogen (P2H) technology by taking advantage of enormous wind energy. The work efficiency of P2H technology, converting electricity from renewable energy into green hydrogen by water electrolysis can be improved by recycling its waste heat, which can be called power to hydrogen and heat (P2HH). In this paper, P2HH has been applied with a large-scale alkaline electrolyser, so that it works as a prosumer consuming electricity, and producing hydrogen and heat simultaneously. The mathematical model of the wind and hydrogen hybrid system with P2HH technology has been built and the economic performance of the hybrid system connected to the power grid has been investigated by applying an economic model predictive control (EMPC) strategy for its optimal dispatch. By using real-life historical data from the Bornholm energy island in Denmark, the simulation results show that the EMPC controller is capable of robustness to achieve optimal electricity consumption, energy cost savings, and the best economic benefits in terms of various system configurations, weights for hydrogen price, constraints on its recycled heat and working temperature. Among these configurations, without constraints on the recycled heat and weights for hydrogen price, the electrolyser working in the 60–90 °C can achieve the most profits in the study case.
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