Grid-connected household nano-grids are playing a key role in meeting the rapidly increasing energy demand. A long-term optimal scheduling algorithm is proposed to better organize the battery charging/discharging action in PV grid- connectedhousehold nano-grids. The algorithm is based on the rolling optimization method and the optimization problem is solved by the mixed integer linear programming. Moreover, a smoothing function is introduced to alleviate the power fluctuation of the exchanging power between the nano-grid and the main grid, caused by the intermittent PV generation and the stochastic residential loads. A battery and a supercapacitor, composing a hybrid energy storage system (HESS), are controlled to absorb the low and the high frequency components of HESS power respectively. The proposed energy management strategy has been validated by using practical PV and load data.

Energy management system (EMS), maxed integer linear programming (MILP), nano-grid, power fluctuation smoothing, rolling optimization
dx.doi.org/10.1109/PESGM40551.2019.8973404
2019 IEEE Power and Energy Society General Meeting, PESGM 2019
Department of Electronics

Ding, Y. (Yiyuan), Wang, Z. (Zhijun), Liu, S, & Wang, X. (Xiaoyu). (2019). Energy Management Strategy of PV Grid-Connected Household Nano-Grid System. In IEEE Power and Energy Society General Meeting. doi:10.1109/PESGM40551.2019.8973404