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Intelligent energy scheduling in a microgrid with custom power devices
The International Journal of Electrical Engineering & Education ( IF 0.941 ) Pub Date : 2020-06-17 , DOI: 10.1177/0020720920929661
V Pramila 1 , S Chandramohan 1
Affiliation  

The increasing penetration of distributed generators may harm power system and its control and operations. The microgrid offers a better solution for the issues in grid operation. Undergraduate electrical engineering and postgraduate power system and power electronics students need to understand the working of microgrid with renewable energy resources along with the optimization and scheduling of power quality custom power devices. To cater better understanding of the microgrid with renewable resources, wind, solar, distributed generators, distributed energy storage devices, DSTATCOM, and plug-in electric vehicle charging load are included in this work presented. In this paper, multiobjective optimization for the operation of microgrid to account for uncertainties in a stochastic energy resources management system is considered. Nonlinear constraint optimization to reduce the running cost, losses, and voltage variations is focused for the optimization. Loss sensitivity analysis is used to find the location wind, solar, distributed generators, distributed energy storage devices, and DSTATCOM. Firefly algorithm is used to optimize the size of distributed generators and DSTATCOM. Optimization reduced the loss, power taken from the grid and improves the voltages in the system. This paper is self-explanatory to the undergraduate and postgraduate students to understand the power flow analysis of microgrid with hybrid renewable energies and optimization technique.



中文翻译:

带有定制电源设备的微电网中的智能能源调度

分布式发电机的日益普及可能会损害电力系统及其控制和运行。微电网为电网运行中的问题提供了更好的解决方案。本科电气工程,研究生电力系统和电力电子专业的学生需要了解带有可再生能源的微电网的工作原理,以及电能质量定制功率设备的优化和调度。为了更好地理解带有可再生资源的微电网,本工作包括风能,太阳能,分布式发电机,分布式能量存储设备,DSTATCOM和插入式电动汽车的充电负荷。本文考虑了微电网运行的多目标优化,以解决随机能源管理系统中的不确定性。减少运行成本,损耗和电压变化的非线性约束优化是优化的重点。损失敏感性分析用于查找风,太阳能,分布式发电机,分布式储能设备和DSTATCOM的位置。Firefly算法用于优化分布式发电机和DSTATCOM的大小。优化降低了损耗,减少了从电网获取的功率并改善了系统中的电压。本文对于本科生和研究生来说是不言自明的,以了解使用混合可再生能源和优化技术的微电网的潮流分析。分布式储能设备和DSTATCOM。Firefly算法用于优化分布式发电机和DSTATCOM的大小。优化降低了损耗,减少了从电网获取的功率并改善了系统中的电压。本文对于本科生和研究生来说是不言自明的,以了解使用混合可再生能源和优化技术的微电网的潮流分析。分布式储能设备和DSTATCOM。Firefly算法用于优化分布式发电机和DSTATCOM的大小。优化降低了损耗,减少了从电网获取的功率并改善了系统中的电压。本文对于本科生和研究生来说是不言自明的,以了解使用混合可再生能源和优化技术的微电网的潮流分析。

更新日期:2020-06-19
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