Optimal dispatch control of energy storage systems using forward-backward induction

B. Abegaz, S. Mahajan
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引用次数: 5

Abstract

The integration of distributed energy resources (DERs) into the power grid provides support for a significant share of the total power load and helps reduce transmission power losses. However, these advantages are not always guaranteed since the power profiles of DERs have high variability and the number of DERs is too many to control on an individual basis. In a hybrid energy system, these problems are counteracted through the aggregation and balancing of the variability of each distributed energy resource. This paper discusses optimal dispatch control mechanisms for 200 V, 500 Ah battery energy storage systems that support a 10 MW hybrid energy system, composed of distributed energy sources such as 1 MW solar photovoltaic (PV) generation and a 9 MW wind turbine based generation. The proposed mechanisms focus on the dispatch control of energy storage systems using forward and backward induction. For that purpose, the interdependence of frequency, state of charge (SOC), undercharge and reversible effects in the battery energy systems were used to identify the optimal operating margin for the dispatch of the energy storage systems. The hybrid energy system was implemented using Matlab-Simulink and the dispatch control mechanism was programmed using IBM CPLEX studio. With such setup, the hybrid system was able to maintain 85% capacity factor per day while the system interruption and unavailability were reduced by 65%. The results demonstrate that the functionality of DERs increases significantly while being supported by optimally dispatched energy storage systems.
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基于前向-后向感应的储能系统最优调度控制
将分布式能源(DERs)集成到电网中为总电力负荷的很大一部分提供支持,并有助于减少传输功率损耗。然而,这些优势并不总是得到保证,因为der的功率曲线具有很高的可变性,并且der的数量太多,无法在单个基础上进行控制。在混合能源系统中,这些问题通过聚合和平衡每个分布式能源的可变性来抵消。本文讨论了支持10mw混合能源系统的200v, 500ah电池储能系统的最优调度控制机制,该混合能源系统由1mw太阳能光伏发电和9mw风力发电等分布式能源组成。所提出的机制侧重于利用正向和反向感应对储能系统进行调度控制。为此,利用电池能量系统中频率、荷电状态(SOC)、欠充和可逆效应的相互依赖关系,确定储能系统调度的最佳运行裕度。混合能源系统采用Matlab-Simulink实现,调度控制机制采用IBM CPLEX studio编程。通过这样的设置,混合系统每天能够保持85%的容量系数,而系统中断和不可用性减少了65%。结果表明,在优化调度的储能系统支持下,DERs的功能显著增强。
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