计及局部阴影工况的光储直流微电网能量管理

Energy Management of Photovoltaic-Storage DC Microgrids Considering Partial Shading Conditions

中文关键词:光伏功率  自适应电导增量法  储能  自适应下垂控制  直流微电网

keywords:photovoltaic power  adaptive incremental conductance method  energy storage,adaptive droop control  DC microgrid

中文摘要:针对新能源可靠供电中的供需平衡问题，提出一种计及局部阴影工况的光储直流微电网能量管理。首先，针对光伏阵列在局部阴影等弱光照工况下，传统最大功率点跟踪方法在功率捕捉能力与能源利用效率方面的不足，利用蝠鲼优化算法（manta ray foraging optimization ，MRFO）的全局与局部搜索优势，提出一种结合MRFO的自适应电导增量法（manta ray foraging optimization-adaptive variable step-incremental conductance，MRFO-AVS-INC），以在特殊工况下实现对光伏出力的有效跟踪；其次，针对系统集成中存在的多源扰动问题，在储能系统的能量管理与控制方面，提出一种考虑蓄电池工作状态的改进下垂控制方法，通过引入蓄电池的荷电状态（state of charge ，SOC）和健康状态（state of health ，SOH）等参数，实现下垂系数的自适应调节，从而合理分配各蓄电池的输出功率；最后，在不同光照条件下对光储系统进行仿真验证。仿真结果表明，与基于粒子群算法的自适应变步长电导增量法（particle swarm optimization-adaptive variable step-incremental conductance ，PSO-AVS-INC）及传统INC相比，MRFO-AVS-INC方法在收敛速度与跟踪稳定性方面表现更优；改进的自适应下垂控制有效实现了储能单元之间的状态均衡，延长了储能系统的整体使用寿命。

Abstract:To address the issue of supply-demand balance in the reliable power supply of new energy，an energy management strategy for a photovoltaic-storage DC microgrid considering partial shading conditions is proposed. Firstly，aiming at the deficiencies of traditional maximum power point tracking methods in power capture capability and energy utilization efficiency when photovoltaic arrays operate under weak light conditions such as partial shading，the global and local search advantages of the manta ray foraging optimization （MRFO） algorithm， an MRFO-adaptive variable step-incremental conductance method is proposed，so as to achieve effective tracking of photovoltaic output under special operating conditions. Secondly，to mitigate multi-source disturbances during system integration，an improved droop control strategy for energy storage management is proposed. This method incorporates the State of Charge and State of Health of individual batteries to adaptively adjust the droop coefficients，thereby optimally distributing the output power among the batteries. Finally，simulations of the PV-storage system under different irradiance conditions are conducted to verify the feasibility of the proposed approach. Compared with the PSO-adaptive variable step-incremental conductance method and the traditional INC，the proposed MRFO-INC demonstrates superior performance in both convergence speed and tracking stability. Meanwhile，the improved adaptive droop control effectively achieves SOC and SOH balancing power among energy storage units，thereby extending the overall operational lifespan of the energy storage system.