混合储能系统功率分配的切换优化控制

IF 2 4区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS
Xiulan Song, Limin Meng, Lei Wang
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引用次数: 0

摘要

本文提出了一种受充电状态和功率分配约束的混合储能系统功率分配的切换优化控制方法。根据能量守恒原理,建立了连续时间开关模型来描述HESS在充放电过程中电荷量的变化。然后,利用公共控制李雅普诺夫函数的概念,构造了具有一定自由参数的解析开关状态反馈律,用于在充放电过程中分配存储单元的功率。针对存储单元功率分配要求的约束条件和性能函数,采用后退水平控制原理,通过在线求解约束优化问题,计算解析切换控制律的参数。利用公共控制Lyapunov函数的性质,在存在约束的情况下,建立了切换优化控制器的渐近稳定性和公共截面区域(0.5,∞)。通过与HESS的线性二次型调节器控制的比较,实例说明了所提出的切换优化控制器的有效性和性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Switched optimization control of power allocation of hybrid energy storage systems
In this paper, we present a switched optimization control method for power allocation of hybrid energy storage systems (HESSs) subject to constraints on the state of charge and power split. By the energy conservation principle, a continuous‐time switching model is established to describe changes of charge quantities of the HESS during its charging‐or‐discharging process. Then an analytic switched state feedback law with some free parameters is constructed by the concept of common control Lyapunov functions, which is used to allocate the power of storage units during the charging‐or‐discharging process. To cope with the constraints and performance functions formulating the power allocation requirements of storage units, the receding horizon control principle is used to compute the parameters of the analytic switched control law by online solving a constrained optimization problem. The results on asymptotical stability and common section region (0.5, ∞) of the switched optimization controller are established in the presence of constraints by using the properties of common control Lyapunov functions. By comparing to linear‐quadratic regulator control of the HESS, an example is used to illustrate the effectiveness and performance of the switched optimization controller presented here.
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来源期刊
Optimal Control Applications & Methods
Optimal Control Applications & Methods 工程技术-应用数学
CiteScore
3.90
自引率
11.10%
发文量
108
审稿时长
3 months
期刊介绍: Optimal Control Applications & Methods provides a forum for papers on the full range of optimal and optimization based control theory and related control design methods. The aim is to encourage new developments in control theory and design methodologies that will lead to real advances in control applications. Papers are also encouraged on the development, comparison and testing of computational algorithms for solving optimal control and optimization problems. The scope also includes papers on optimal estimation and filtering methods which have control related applications. Finally, it will provide a focus for interesting optimal control design studies and report real applications experience covering problems in implementation and robustness.
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