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Developing a multi-objective framework for expansion planning studies of distributed energy storage systems (DESSs)

机译:为分布式能源存储系统(DESS)的扩展计划研究开发多目标框架

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摘要

This paper presents a framework for expansion planning studies of distributed energy storage systems (DESSs) in high wind penetrated power systems. The main objective is to find optimal location and capacity of DESSs in the viewpoint of independent system operator (ISO) while ensuring the maximum usage of wind farms output generation. Three different criteria are introduced for expansion planning studies. Minimizing wind curtailment cost together with transmission congestion cost are considered to properly deal with the issues associated with the curtailment of wind energy and constraints of transmission network. Furthermore, the minimum normalized profit for all DESSs' owners needs to be maximized to model the requirements of DESSs' owners in the studies. These all the crucial aspects of the DESSs expansion problem are treated via a well-organized posteriori multi-objective (MO) optimization algorithm, i.e. the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The proposed method is applied to the modified IEEE 24-bus test system, and the results are presented to verify the applicability and efficiency of the proposed DESSs planning in a renewable-based power system.
机译:本文为高风速渗透电力系统中的分布式能源存储系统(DESS)的扩展规划研究提供了一个框架。主要目标是从独立系统运营商(ISO)的角度寻找DESS的最佳位置和容量,同时确保最大程度地利用风电场的发电量。为扩展计划研究引入了三种不同的标准。考虑将风电削减成本和输电拥堵成本降至最低,可以正确处理与风电削减和输电网络约束相关的问题。此外,需要最大化所有DESS所有者的最小标准化利润,以模拟研究中DESS所有者的需求。 DESS扩展问题的所有这些关键方面都通过组织良好的后验多目标(MO)优化算法(即非支配排序遗传算法II(NSGA-II))进行处理。该方法被应用于改进的IEEE 24总线测试系统,并给出了结果,以验证该方法在基于可再生能源的电力系统中的适用性和有效性。

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  • 来源
    《Energy》 |2018年第15期|1079-1089|共11页
  • 作者单位

    Department of Electrical Engineering, Sharif University of Technology;

    Department of Energy Engineering, Sharif University of Technology;

    Department of Electrical Engineering, Sharif University of Technology;

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  • 正文语种 eng
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