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A Novel Meta-Heuristic Hybrid Enhanced Differential Harmony Wind Driven (EDHWDO) Optimization Technique for Demand Side Management in Smart Grid

机译:一种新型元启发式混合增强型差分和声风驱动(EDHWDO)智能电网需求侧管理优化技术

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In recent decades numerous Demand Side Management (DSM) techniques have been merged for Smart Grid (SG). These techniques have been very effective in minimizing cost. However, lack in other characteristics like effective control over Peak Average Ratio (PAR) that why they are not equally beneficial for the utility. Due to different characteristic of different operations some techniques are really work well for cost and some for PAR. We have evaluated and extracted different operations from Harmony Search Algorithm (HSA), Enhanced Differential Evolution (EDE) and Wind Driven Optimization (WDO) for controlling cost along with PAR. A hybrid Enhanced Differential Harmony Wind Driven Optimization (EDHWADO) is formed that combines the cost effectiveness of WDO, HSA and PAR controlling operation through integration of EDE. The proposed hybrid engine proved to be most cost effective in comparison to Genetic Algorithm (GA), WDO along effective PAR control and User Comfort (UC) maximization. Real Time Pricing (RTP) signals are used to evaluate real time behavior of appliances. Three categories of appliances are used; fixed, elastic and shiftable. On basis of performances metrics, simulations proved that EDHWDO leads substantial cost saving along with enhancing user comfort and also helps in significant cost reduction.
机译:近几十年来,智能电网(SG)合并了许多需求侧管理(DSM)技术。这些技术在最小化成本时非常有效。然而,在其他特征中缺乏有效控制峰值平均比率(PAR),为什么它们对该实用性同样有益。由于不同操作的不同特点,某些技术对于成本而言,有些技术实际上很好地工作,有些技术是杆。我们已经评估和提取了来自和声搜索算法(HSA),增强的差分演进(EDE)和风驱动优化(WDO)的不同操作,以控制成本。形成混合增强的差分和谐风驱动优化(EDHWADO),其结合了WDO,HSA和PAR控制操作的成本效益通过EDE集成。与遗传算法(GA),WDO沿着有效的PAR控制和用户舒适度(UC)最大化,所提出的混合发动机被证明是最具成本效益的。实时定价(RTP)信号用于评估器具的实时行为。使用了三类电器;固定,弹性和可移动。在表演度量的基础上,仿真证明,EDHWDO与提高用户舒适性带来了大量成本,并有助于减少重大成本。

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