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Day ahead scheduling of generation and storage in a microgrid considering demand Side management

机译:考虑需求侧管理的微电网中的发电和存储的提前一天调度

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The problem of day-ahead scheduling of generation and storage facilities in a microgrid in the presence of Renewable sources with an objective to minimize the cost of power generation is considered in the article. The objective function is formulated considering a linear cost function for renewable generators and quadratic cost function for conventional generators. The uncertainty in available power from renewable generators and loads is modeled using a proven uncertainty model and two scenarios are drawn. Artificial Fish Swarm intelligence is used to solve the optimization part. The proposed algorithm is investigated on a numerical example with a cluster of renewable and conventional generators with different cost functions. The results obtained show that the proposed algorithm is able to utilize the cheapest sources to the extent of 100% and utilize the other generators in decreasing percentage as their cost of generation increases. The costliest source, which is grid power in the numerical example considered, is utilized only very sparingly. Apart from obtaining optimal solution for scheduling, the proposed algorithm is able to consolidate battery - microgrid power exchange and also implement load shedding when required.
机译:本文考虑了在存在可再生资源的情况下,微电网中发电和存储设施的日前调度问题,目的是最大程度地降低发电成本。目标函数的制定考虑了可再生发电机的线性成本函数和常规发电机的二次成本函数。使用经过验证的不确定性模型对可再生发电机和负载的可用功率不确定性进行建模,并绘制了两种情况。人工鱼群智能用于解决优化部分。在数值示例上研究了提出的算法,该示例包含具有不同成本函数的可再生和常规发电机组。获得的结果表明,所提出的算法能够利用最便宜的资源达到100%的程度,并随着其他发电机的发电成本的增加而使用百分比降低的发电机。在考虑的数值示例中,最昂贵的电源是电网电源,仅很少使用。除了获得最佳的调度解决方案外,该算法还可以巩固电池-微电网的电力交换,并在需要时实现减载。

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