基于Grasshopper优化算法的插电式电动汽车和可再生能源高渗透率有源配电网优化调度

Seyyed Hadi Mousavi, Varahram Janatifar, A. Abdolahi, M. Sarhangzadeh
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引用次数: 2

摘要

随着插电式混合动力汽车(PHEV)作为小型移动电站的发展,这类电站的能量管理需要更多的研究。因此,插电式混合动力汽车的充放电能力可用于主动配电网(ADN)。本文提出了一种以最小化系统运行成本为目标的电动汽车充放电调度优化方法。研究了分布式发电机组在PEVs限制下,PEVs对运行成本和系统的一些技术特性(如功率损耗和电压分布)的影响。本文采用蝗虫优化算法(grasshopper optimization algorithm, GOA)求解这一复杂的混合整数非线性规划问题,其目标是使系统的运行成本最小并找到最优解。最后,通过在改进后的IEEE 69总线系统上实现该模型,验证了该模型的充分性和熟练性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Scheduling of Active Distribution Networks with High Penetration of Plug-in Electric vehicles and Renewables Using Grasshopper Optimization Algorithm
With the development use of the plug-in hybrid electric vehicles (PHEV) as small moving power plants, energy management of these types of power plants requires more researches. So, the charging and discharging capability of PHEVs can be used in active distribution networks (ADN). This paper suggests an optimal approach for charging and discharging scheduling of PEVs in the ADNs to minimize the operating costs of system. The influence of PEVs on the operating costs and some technical characteristics of system like power losses and voltage profile has been investigated under PEVs limits, distributed generation units. In this work, the grasshopper optimization algorithm (GOA) is applied to solve this complicated mixed-integer non-linear programming problem with the goal of minimizing the operating costs of the system and find the optimal solutions. In the end, an illustrative case study is provided to acknowledge the sufficiency and proficiency of the presented model by implementing it on the modified IEEE 69-bus system.
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