Break-Even Analysis of Battery Energy Storage in Buildings Considering Time-of-Use Rates

Sun, Mucun; Chang, Chih-Lun; Zhang, Jie; Mehmani, Ali; Culligan, Patricia J.

doi:10.1109/greentech.2018.00026

Cited by 8 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The energy usage of the system in a period of time is similar, and the clustering algorithm can be used to get the typical energy utilization scenarios. Weights are assigned to typical days according to the occurrence days of typical scenarios, while the operation plan of typical days is optimized to get the annual cost [13][14]. By dividing typical days, the solving difficulty of the optimization model is significantly reduced, and the solving time is also greatly shortened.…”

Section: 3algorithm Designmentioning

confidence: 99%

Optimal configuration of cooling heating and power integrated energy storage for commercial buildings

Ding

2023

5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023)

View full text Add to dashboard Cite

In this paper, the optimal configuration of cooling, heating and power energy storage (CHPES) under the typical energy system architecture of commercial buildings is studied. On the basis of meeting the user's demand for electricity, heating and cooling, the configuration capacity and power of electric, heating and cooling energy storage are optimized with the goal of minimizing the total cost of equal annual value within the life cycle of the system. By dividing typical days, the variable dimension is greatly reduced and the solving time is shortened, so that the optimization model can be solved by the commercial solver. The numerical example shows that, CHPES can significantly reduce the equal annual cost of the system, and also promote the peak shaving and valley filling of the power grid.

show abstract

Section: 3algorithm Designmentioning

confidence: 99%