Residential Energy Storage Management With Bidirectional Energy Control

被引:47
作者
Li, Tianyi [1 ,2 ]
Dong, Min [1 ]
机构
[1] Univ Ontario Inst Technol, Dept Elect Comp & Software Engn, Oshawa, ON L1H 7K4, Canada
[2] Huawei Technol Co Ltd, Markham, ON L3R 5A4, Canada
关键词
Energy storage; renewable generation; energy selling; home energy management; Lyapunov optimization; real-time control; RENEWABLE ENERGY; POWER GRIDS; INTEGRATION;
D O I
10.1109/TSG.2018.2832621
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We consider the residential energy storage management system with integrated renewable generation and the availability of bidirectional energy flow from and to the grid through buying and selling. We propose a real-time bidirectional energy control algorithm, aiming to minimize the net system cost from energy buying and selling as well as battery deterioration and storage inefficiency within a given time period, subject to the battery operational constraints and energy buying and selling constraints. We formulate the problem as a stochastic control optimization problem. We then modify and transform this difficult problem into one that enables us to develop the real-time energy control algorithm through Lyapunov optimization. Our developed algorithm is applicable to arbitrary and unknown statistics of renewable generation, load, and electricity prices. It provides a simple clued-form control solution based on only current system states, and requires a minimum complexity for real-time implementation. Furthermore, the solution structure reveals how the battery energy level and energy prices affect the energy flow direction and storage decision. The proposed algorithm possesses a bounded performance guarantee to that of the optimal non-causal T-slot look-ahead control policy. Simulation shows the effectiveness of our proposed algorithm as compared with alternative real-time and non-causal algorithms, and demonstrates the effect of selling-to-buying price ratio and battery inefficiency on the storage behavior and system cost.
引用
收藏
页码:3596 / 3611
页数:16
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