首页|考虑能量效率和SOC均衡的电池储能电站双层功率分配策略

考虑能量效率和SOC均衡的电池储能电站双层功率分配策略

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电化学储能电站在应用于调频、调压等功率波动性工况时,存在能量效率较低、荷电状态(state of charge,SOC)不均衡等问题.该文提出考虑能量效率和SOC均衡的电池储能电站双层功率分配策略,其主要包括单元优化层和子系统优化层:单元优化层通过充电/放电优先级分区计算实际运行单元数量及其编号,建立以储能单元能耗最小为目标的优化模型,并采用遗传算法求解最优解集;子系统优化层引入基于电化学阻抗的电池能耗模型,以储能子系统能耗最低和SOC均衡为目标建立多目标优化模型,并采用非支配快速 排 序 遗 传 算 法(non-dominated sorting genetic algorithms-II,NSGA-II)进行求解.通过某地区锂电池储能电站实际参数验证所提策略的有效性,结果表明,与 SOC比例分配策略和单层功率分配策略相比,所提功率分配策略在降低电站能耗的同时能最大程度实现SOC均衡,保障电站双向调节能力,提高储能电站经济性.
Double-layer Power Distribution Strategy for Battery Storage Power Station Considering Energy Efficiency and State-of-charge Balance
When the electrochemical energy storage power station is applied to frequency modulation,voltage regulation,and other power fluctuation conditions,there are problems such as low energy efficiency and unbalanced state of charge(SOC).This paper proposes a double-layer power distribution strategy for battery storage power stations considering energy efficiency and SOC balance,which mainly includes the unit optimization layer and the subsystem optimization layer:The unit optimization layer calculates the quantity and number of actual operating units through charging/discharging priority partition,establishes an optimization model aiming at the minimum energy consumption of the energy storage units,and uses genetic algorithm(GA)to solve the optimal solution set;The battery energy consumption model based on electrochemical impedance is introduced into the subsystem optimization layer,and the multi-objective optimization model is established with the minimum energy consumption and SOC balance as the objectives,and the non-dominated sorting genetic algorithms-II(NSGA-II)is used to solve the problem.The effectiveness of the proposed strategy is verified by using the actual parameters of a lithium battery energy storage power station in a region.The results show that compared with the SOC proportional distribution strategy and the single-layer power distribution strategy,the proposed strategy can achieve the maximum SOC balance while reducing the energy consumption of the power station,enhancing the two-way regulation ability of the power station,and improving the economy of the energy storage power station.

energy storage plantpower allocation strategyenergy efficiencystate of charge(SOC)balance(non-dominated sorting genetic algorithms-II(NSGA-II)

叶晖、李爱魁、田刚领、谢佳、李占军

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大连理工大学电气工程学院,辽宁省 大连市 116024

华中科技大学电气与电子工程学院,湖北省 武汉市 430074

平高集团储能科技有限公司,天津市 东丽区 300399

储能电站 功率分配策略 能量效率 荷电状态均衡 非支配快速排序遗传算法

中国电气装备集团有限公司总部管理科技项目

CEE-2022-B-01-03-004-PG

2024

10.13334/j.0258-8013.pcsee.230396

中国电机工程学报
中国电机工程学会

中国电机工程学报

CSTPCD北大核心
影响因子：2.712
ISSN：0258-8013
年,卷(期)：2024.44(13)
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