Hybrid compressed air energy storage system and control strategy fora partially floating photovoltaic plant

被引:5
作者
Bassam, Ameen M. [1 ]
Elminshawy, Nabil A. S. [2 ]
Oterkus, Erkan [3 ]
Amin, Islam [1 ,3 ]
机构
[1] Port Said Univ, Fac Engn, Dept Naval Architecture & Marine Engn, Port Fouad, Egypt
[2] Port Said Univ, Fac Engn, Dept Mech Power Engn, Port Fouad, Egypt
[3] Univ Strathclyde, Dept Naval Architecture Ocean & Marine Engn, Glasgow, Scotland
关键词
Compressed air energy storage; Energy management strategy; Rule-based approach; Photovoltaic systems; MATLAB; Simulink; THERMODYNAMIC ANALYSIS; POWER-PLANT; MANAGEMENT; SIMULATION; OPTIMIZATION; PERFORMANCE; PRESSURE; DESIGN; CAES;
D O I
10.1016/j.energy.2024.133706
中图分类号
O414.1 [热力学];
学科分类号
摘要
For more efficient, reliable, and stable energy provision, energy storage plays a key role in the transition towards renewable energy sources. Compressed air energy storage (CAES) has been recognized as one of the most promising technology due to its high energy capacity, flexibility, scalability, long lifespan, maintainability, economical, and environmental viability. These potentials can be further improved by hybridizing CAES systems with thermal energy storage system. However, to realize the potentials of hybrid CAES systems, a control strategy is essential to manage the energy flow between the system components. Therefore, in this work, a novel energy management strategy is proposed to control a hybrid CAES system fora prototype of a partially floating photovoltaic plant (PFPV). The proposed control strategy is based on the rule-based approach and a mathematical model is presented to evaluate the system performance. The results indicate that, for an average hourly profile of the 5 kW PFPV platform through the year, a system round-trip efficiency of 34.1% can be obtained while the cycle and exergy efficiencies are 37.7% and 41%, respectively. Higher efficiency can be obtained by controlling the compressors operational range and rated power. Therefore, future work includes experimental work for results validation and optimization.
引用
收藏
页数:20
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