Low carbon optimization of integrated energy microgrid based on life cycle analysis method and multi time scale energy storage. (April 2023)

• Record Type: Journal Article
• Authors: Dong, Haiyan; Fu, Yanbo; Jia, Qingquan; Zhang, Tie; Meng, Dequn
• Is Part Of: Renewable energy. Volume 206(2023)
• Page Start: 60
• Page End: 71
• Publication Date: 2023-04
• Subjects: Seasonal imbalance -- Multiple time scale energy storage -- Life cycle assessment -- Carbon trading mechanism; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2023.02.034
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: In monsoon regions, renewable energy output and load demand have obvious seasonal differences. As the proportion of renewable energy continues to increase, energy storage technology has been widely developed. An optimal scheduling model of integrated energy microgrid considering multi time scale energy storage is proposed. It can stabilize the seasonal imbalance of source and load and achieve the effect of seasonal energy storage. Firstly, electric energy storage and thermal energy storage are introduced into the integrated energy microgrid as short time scale energy storage, and hydrogen storage is introduced as long time scale energy storage. Secondly, the characteristics of renewable energy output and load in different seasons are analyzed. Thirdly, in order to analyze the economic and environmental benefits of microgrid, carbon emissions of different energy chains in the whole life cycle assessment analysis system are adopted. It will be combined with the carbon trading mechanism. Finally, an economic optimization model considering carbon trading is established. Optimize the charging and discharging state of multi time scale energy storage with the goal of minimizing the total cost. Numerical examples show that the allocation of multi time scale energy storage can save 16.9% of cost, with low carbon value and economic feasibility. Graphical abstract: Image 1