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| A Distributed Power Allocation Strategy for Battery Energy Storage Systems Based on Competitive-Cooperative Mechanism |
| Yu Yang1,2, Li Menglu1,2, Wang Boxiao1,2, Xiang Xiaoping1,2, Liu Weiliang3 |
1. Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province North China Electric Power University Baoding 071003 China;
2. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Baoding 071003 China;
3. Baoding Key Laboratory of State Detection and Optimization Regulation for Integrated Energy System Baoding 071003 China |
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Abstract In order to reduce the lifespan loss of battery energy storage systems (BESS) when suppressing unbalanced power in microgrids, while ensuring its adjustability, this paper proposes a low loss balanced power allocation strategy for BESS based on competitive cooperation mechanism and improved bipartite consistency algorithm (IBCA). Firstly, in order to promote the balance of individual state of charge (SOC), the event driven BESS grouping model is established. Further considering the individual lifespan loss and the adjustable ability of BESS, the BESS power allocation model based on competition and cooperation mechanism is designed, which proposes the design concept of competition and cooperation mechanism, constructs four power allocation modes based on competition and cooperation mechanism, and establishes corresponding BESS power allocation objective functions. Secondly, the bipartite consistency algorithm (BCA) is selected as the BESS power allocation implementation algorithm. Taking into account communication delay, the state feedback mechanism, power allocation weighting matrix, and gauge transformation matrix are introduced into the bipartite consistency algorithm to form improved-BCA (IBCA). Subsequently, the BESS power allocation strategy based on the packet power allocation model is designed and the IBCA is utilized to complete the BESS power allocation. Finally, the performance of the proposed IBCA and power allocation strategy is verified through simulation and experiments.
Using a certain microgrid demonstration platform, a typical daily unbalanced power data was selected for simulation. In order to verify the advantages of IBCA, convergence speed, robustness, and memory usage are used as evaluation indicators and compared with the other three algorithms. The results show that due to the influence of communication delay, there are fluctuations in the initial iteration of each algorithm, while IBCA can quickly converge to steady state, with a shorter iteration time and faster convergence speed. At the same time, IBCA can quickly recover to steady state after being disturbed, and still has high convergence accuracy, indicating that IBCA has high robustness. Furthermore, by analyzing the amount of data stored in the iterative process system, it can be concluded that IBCA has a lower memory usage. In order to verify the effectiveness of the control strategy proposed in this article, the grouping power allocation effect, reducing lifespan loss effect, battery units SOC recovery and balance control effect, and power tracking effect are used as evaluation indicators, and compared with the other three schemes. The results show that the power allocation model based on competition and cooperation mechanism effectively ensures the response advantage of the power response subject group, reduces the power shock caused by units state switching, reduces BESS lifespan loss, promotes SOC recovery, and effectively improves SOC balance. In addition, the BESS grouping model based on event driven mechanism effectively achieves the reordering and grouping of battery units triggering events. The final power tracking effect diagram shows that according to the strategy proposed in this article, BESS can achieve fast and accurate tracking of power instructions, provide fast compensation for unbalanced power in microgrids, and thus improve the stability of microgrid operation.
To further verify the effectiveness of the power allocation strategy proposed in this article, a BESS hardware experimental platform was built. The experimental results show that the proposed strategy effectively reduces the lifespan loss of BESS, with an expected service life of up to 12.47 years. At the same time, proving the effectiveness of the strategy proposed in this article for battery unit grouping and SOC balance. In addition, the power tracking results indicate that BESS can achieve fast and accurate tracking of power instructions, and the experimental results are consistent with the simulation results.
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Received: 18 April 2024
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2025, Vol. 40 
