混合野马优化法(WHO)和矮獴优化法(DMO)用于优化 SG 系统的能源管理

P. Ganesan, S. Arockia Edwin Xavier
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引用次数: 0

摘要

针对智能电网(SG)系统的能源管理(EM)提出了一种混合技术。该方法综合了野马优化法(WHO)和矮獴优化法(DMO),因此被命名为WHO-DMO方法。微电网(MG)绑定系统是电池、微型涡轮机(MT)、光伏(PV)和风力涡轮机(WT)的组合。建议方法的主要目的是管理 SG 模型的资源和电力,并降低电力成本。该系统的目标是改善负荷需求。世界卫生组织方法通过 DMO 方法得到了加强,从而使系统目标最小化。获取电力需求、充电状态 (SOC) 和用于存储元素的可再生能源 (RES) 被视为系统的约束条件。可再生能源发电系统依靠电池作为能源,在整个运行过程中稳定并持续输出功率。所提出的技术是在 MATLAB 平台上完成的,其实现是通过现有方法计算得出的。模拟结果表明,与现有方法相比,建议的方法成本更低,功率更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Hybrid Wild Horses Optimization (WHO) and Dwarf Mongoose Optimization (DMO) method for optimum energy management in SG system
A hybrid technique is proposed for the energy management (EM) of smart grid (SG) systems. The proposed method integrates the Wild Horse Optimization (WHO) and dwarf mongoose optimization (DMO) methods; hence, it is named the WHO–DMO approach. The Micro‐grid (MG)‐tied system is a combination of battery, micro turbine (MT), photovoltaic (PV), and Wind Turbine (WT). The key aim of the proposed approach is to manage the resources and power of the SG model and reduce the cost of electricity. The objective of the system is to improve load demand. The WHO method is enhanced by the DMO method, which minimizes the objective of the system. Access to power demand, state of charge (SOC), and renewable energy sources (RESs) for storing elements are considered constraints of the system. The unit of renewable power systems relies on batteries as energy sources to stabilize and sustain stable and consistent output power throughout the operation. The proposed technique is done in MATLAB platform and its implementation is calculated using the existing methods. From the simulation, the proposed method has less cost and higher power than the existing methods.
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