考虑电动汽车包含的机组承诺的ORCA算法

A.N. Afandi
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引用次数: 0

摘要

在实践中,通过将不同类型的发电机组组合在一起,制定一个承诺的电力计划,以满足运行期间负荷需求的变化,从而实现电力系统最具成本效益的运行。为了在保持设定限制的同时降低总成本,发电机组的输出功率根据特定时刻的负载需求进行分配。经济调度模型用于考虑负荷需求的变化,以计算实现机组承诺(UC)的总体运行成本变化。本文以IEEE-62总线系统为模型,采用Orca算法解决UC问题,其中负载与柔性负载相关联,本文中的柔性负载由电动汽车的驾驶习惯决定。仿真结果表明,Orca算法能够以最少的迭代次数解决问题。用于计算各时间段负载需求变化的计算快速、平稳,收敛性强。UC问题是在各种功率输出下进行的,总运行费用。此外,电动汽车还具有不同的驾驶特性和高级用户,可以覆盖整个路线,提供单程和两次行驶的驾驶模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ORCA Algorithm for Unit Commitment Considering Electric Vehicle Inclusion
The most cost-effective operation of a power system is achieved in practice by combining different types of producing units to create a committed power plan to satisfy load demand changes at all periods of operation. To reduce overall costs while upholding set limitations, power outputs from generating units are distributed based on load demand at a certain moment. Economic Dispatch models are used to account for changes in load demand to compute the overall cost variations of operation to fulfill a unit commitment (UC). Orca Algorithm is used in this work to solve the UC problem with the IEEE-62 bus system as the model, where loads are linked with flexible loads where the flexible load in this study is determined by the driving habits of an electric vehicle (EV). The simulation results show that the Orca Algorithm solves the problem in the fewest iterations possible. Computations used to compute load demand changes over all periods are fast and smooth, with high convergence. UC problem is carried out in various power outputs, and total operating expenses. Furthermore, the EV has different driving characteristics as well as power users to cover the entire route for driving patterns with one-way and two trips.
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