Sensitivity analysis and optimization of a compressed air energy storage (CAES) system powered by a photovoltaic plant to supply a building

被引:5
|
作者
Simpore, Sidiki [1 ]
Garde, Francois [1 ]
David, Mathieu [1 ]
Marc, Olivier [1 ]
Castaing-Lasvignottes, Jean [1 ]
机构
[1] 117 Rue Gen Ailleret, F-97430 Le Tampon, Ile De La Reuni, France
关键词
Energy storage; photovoltaic; Compressed air; Smart grid; intermittency; Renewable energy;
D O I
10.1016/j.promfg.2019.05.016
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
One of the handicaps of the large-scale integration of solar energy is due to its variability and its intermittency. The main way to overcome this issue is the energy storage technology. Knowing the high cost of batteries and their impact on the environment, we simulate a storage system based on compressed air and acting as a battery system. The CAES consists in storing the air at a high pressure in a tank during the period when the energy source is abundant, i.e., cheap, or when the energy demand is low. The compressed air is later expanded through an air turbine which generates electricity during the high demand periods, i.e. when the energy source becomes very expensive for instance. This system could be used for decentralized electricity supply or in an area with no electric grid. In order to evaluate the feasibility of a Compressed Air Energy Storage system coupled to a photovoltaic plant and a building that represents a reduced power demand, a numerical model that reflects the instant behaviour has been built. The system is composed of a photovoltaic power plant, an air compression system, a storage vessel, an expansion module, a power grid and a building. The inputs used are, on the one hand, the climate data such as ambient temperature and the global solar irradiation and, on the other hand, the load curve of a building or of the group of buildings, which has to be supplied by electricity. The overall system optimization has then been performed after having done a sensitivity analysis of the key parameters. This optimization allows us to find the most suitable size for each component of the system: compressor, tank size and photovoltaic area. (C) 2019 The Authors. Published by Elsevier B.V.
引用
收藏
页码:137 / 142
页数:6
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