微电网中具有放电率约束的BESSs在预设性能与间歇动态下的分布式功率分配方案
Distributed Power Allocation Scheme with Prescribed Performance and Intermittent Dynamics for BESSs with Discharge Rate Constraints in Microgrids
- Nankai University（南开大学）
- Tianjin Key Laboratory of Interventional Brain-Computer Interface and Intelligent Rehabilitation, Nankai University（南开大学介入式脑机接口与智能康复天津市重点实验室）
机构由 AI 辅助整理，请以论文原文为准。
中文总结 AI 辅助
针对多BESS网络，提出基于MASs的分布式动态平均跟踪算法，通过事件触发和自触发方案及预设性能控制，实现功率共享和SoC平衡的几乎零误差估计，并在4总线系统上验证。
中文摘要 AI 辅助
荷电状态（SoC）是电池储能系统（BESS）的重要参数，其平衡问题在多BESS网络中也是一个值得研究的课题。近期，一些研究者提出了一种功率分配方法，声称只要能够实时获取功率共享状态和SoC平衡状态，该方法不仅能维持供需平衡，还能确保任何BESS不会因储能不足而提前退出。鉴于此，我们尝试基于多智能体系统（MASs）设计一种具有预设瞬态和稳态性能的分布式动态平均跟踪算法，以分布式方式估计具有动态负载的BESSs网络的功率共享和SoC平衡状态。这里设计了两个版本的解决方案，一个是事件触发，另一个是自触发。这两种方案分别在不同程度上确保了间歇通信下估计器的性能。在每个构建的估计方案中，采用预设性能控制（PPC）方法来确保预期的稳态和动态性能，该性能被封装在一个性能函数中。因此，它实现了对快速时变的功率共享和SoC平衡状态的几乎零误差估计。此外，共识和平均跟踪性能被解耦，这为参数调整提供了便利。最后，为验证理论分析的结果，研究了一些案例，并在一个4总线系统上进行了相关仿真。
英文摘要
The State-of-Charge (SoC) is an important parameter of a battery energy storage system (BESS), and its balance problem is also an issue worth studying in a multi-BESS network. Recently, some researchers have proposed a power allocation method, claiming that as long as the power sharing state and SoC balance state can be obtained in real-time, it can not only maintain supply and demand balance, but also ensure that any BESS will not exit early due to insufficient energy storage. Considering this, we are attempting to design {a distributed dynamic average tracking algorithm} based on multi-agent systems (MASs) with prescribed transient and steady state performance to estimate the power sharing and SoC balance states \textcolor{blue}{of} a BESSs network with dynamic load in a distributed manner. Two versions of the solution are designed here, where one is event triggered and the other is self triggered. These two schemes ensure the performance of the estimators under intermittent communication to varying degrees, \textcolor{blue}{respectively}. In each constructed estimation scheme, prescribed performance control (PPC) method is implemented to ensure the expected steady-state and dynamic performance, which is encapsulated in a performance function. Thus, it achieves almost zero error estimation of the fast time-varying {power} sharing and the SoC balance states. In addition, consensus and average tracking performance are decoupled, which provides convenience for \textcolor{blue}{parameters} tuning. Finally, to verify the results of \textcolor{blue}{the} theoretical analysis, some cases are studied and relevant simulations are performed on a 4 bus system.
