Impact of Energy Consumption Optimisation on the Electrical Self-Sufficiency of a Microgrid with Vehicle-to-Grid Technology

Q3 Engineering
Vojtech Blazek, L. Prokop, S. Mišák, Pavel Kedroň, Ivo Pergl
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引用次数: 0

Abstract

This article presents optimisation tools for optimising electric consumption in household microgrid environments with Vehicle To Grid (V2G) technology. Optimalisation tools are based on a Non-dominated sorting genetic algorithm II (NSGA-2). Furthermore, this article describes the digitalised digital twin of the physical microgrid. The physical microgrid simulates a typical Czech household whose primary stochastic energy source is a photovoltaic plant (PV). Microgrid works off-grid. The study's results showed a positive impact on optimising potential electrical self-sufficiency in the microgrid in the conditions of Central Europe. The optimization results most efficiently under tariff mode with electric vehicles (EV). The worst results are achieved in the microgrid, where optimisation is disabled, but tariff mode is activated. This article has served as an initial study of whether it Is worthwhile to use this optimisation.
能源消耗优化对车辆到电网技术微电网电力自给的影响
本文介绍了利用车辆到电网(V2G)技术优化家庭微电网环境中电力消耗的优化工具。优化工具基于非支配排序遗传算法II (NSGA-2)。此外,本文还描述了物理微电网的数字化数字孪生。物理微电网模拟了一个典型的捷克家庭,其主要随机能源是光伏电站(PV)。微电网在离网运行。该研究结果显示,在中欧条件下,对优化微电网的潜在电力自给自足具有积极影响。以电动汽车为代表的电价模式下优化效果最好。最糟糕的结果是在微电网中实现的,其中优化被禁用,但关税模式被激活。本文是关于是否值得使用这种优化的初步研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Transactions on Electrical Engineering, Electronics, and Communications
Transactions on Electrical Engineering, Electronics, and Communications Engineering-Electrical and Electronic Engineering
CiteScore
1.60
自引率
0.00%
发文量
45
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