电工技术学报2026，Vol.41Issue(1)：343-358,16.DOI:10.19595/j.cnki.1000-6753.tces.241924
基于动态参与因子和自适应模型预测控制的电池储能二次调频控制策略
Secondary Frequency Modulation Control Strategy for Battery Energy Storage Based on Dynamic Participation Factor and Adaptive Model Predictive Control
摘要
Abstract
Battery energy storage,as an advanced power device with bidirectional charging and discharging capabilities,fast response speed,and high regulation precision,exhibits strong frequency regulation potential.However,existing studies on the participation of energy storage in secondary frequency regulation lack flexibility in designing the frequency regulation responsibility allocation strategy between energy storage and thermal power units.Consequently,they fail to fully leverage the advantages of energy storage and thermal power units under complex load fluctuation scenarios.Moreover,the conventional methods face conflicts between meeting system frequency regulation demands and ensuring the state of charge(SOC)recovery of energy storage.To address this issue,this paper proposes a secondary frequency regulation strategy that integrates dynamic participation factors and adaptive model predictive control(MPC)while considering SOC recovery. Firstly,based on the sensitivity principle,the relationship between the energy storage participation factor and system frequency deviation under the area control error(ACE)mode is established.A hierarchical decision-making mechanism is then designed,incorporating sensitivity,frequency deviation,and load fluctuations.A fuzzy control approach is employed to dynamically adjust the energy storage participation factor based on the load condition,optimizing the frequency regulation responsibility allocation between energy storage and thermal power units.This approach effectively exploits the rapid response capability of energy storage and the sustained regulation ability of thermal power units.On this basis,since directly using the dynamic frequency regulation responsibility signal as the energy storage power command is suboptimal,it is instead formulated as the optimization objective of an MPC controller.The MPC framework then iteratively computes the optimal power output of energy storage in real time,thereby improving the system's frequency regulation performance.Furthermore,an adaptive MPC-based energy storage regulation and SOC recovery strategy is proposed,incorporating a SOC recovery term into the MPC objective function.By segmenting the ACE signal and SOC state,the weight of this term is adaptively adjusted across different operating regions,effectively mitigating the conflict between frequency regulation and SOC recovery while enhancing the bidirectional frequency regulation capability of energy storage across all operating conditions. Simulation results demonstrate that under step load disturbances,the proposed method reduces the maximum frequency deviation to-0.209 7 Hz,achieving a 13.88%and 8.07%improvement compared to two conventional energy storage frequency regulation methods.Additionally,the frequency nadir rate is reduced to 0.252 6 Hz/s,with respective improvements of 23.22%and 32.44%compared to two conventional methods.Under continuous load disturbances,the root mean square value of frequency deviation of the proposed method is reduced by 48.84%,40.46%,and 22.32%compared to three benchmark methods.In the frequency regulation process,the integral of absolute frequency variation of the proposed method remains minimum compared with the three benchmark methods.Moreover,in extreme scenarios where the initial SOC is 0.12 or 0.88,the proposed MPC adaptive partitioning method with adjustable weights for SOC recovery ensures effective frequency regulation while simultaneously achieving significant improvements in SOC recovery.The root mean square value of SOC deviation is reduced to 2.644×10-1 and 2.686×10-1,representing reductions of 32.03%and 30.16%compared to method that disregard SOC recovery,and reductions of 13.11%and 13.55%compared to method that use fixed-weight strategies. The simulation analysis leads to the following conclusions:The dynamic participation factor and adaptive model predictive control strategy can distinguish the frequency regulation participation of thermal power units and energy storage at different stages of secondary frequency regulation.This approach enhances system frequency regulation performance while guiding the SOC of energy storage back to the ideal operating range,ensuring its long-term stable operation.关键词
电池储能/二次调频/动态参与因子/自适应模型预测控制/荷电状态Key words
Battery energy storage/secondary frequency regulation/dynamic participation factor/adaptive model predictive control/state of charge分类
信息技术与安全科学引用本文复制引用
Zhu Zhenshan,Weng Kailiang,Ouyang Haitao..基于动态参与因子和自适应模型预测控制的电池储能二次调频控制策略[J].电工技术学报,2026,41(1):343-358,16.基金项目
福建省科技创新战略联合研究项目资助(2023R0153). （2023R0153）
