Stochastic planning and scheduling of energy storage systems for congestion management in electric power systems including renewable energy resources

被引：135

作者：

Hemmati, Reza ^{[1
]}

Saboori, Hedayat ^{[1
]}

Jirdehi, Mehdi Ahmadi ^{[1
]}

机构：

[1] Kermanshah Univ Technol, Dept Elect Engn, POB 63766-67178, Kermanshah 6715685420, Iran

来源：

ENERGY | 2017年 / 133卷

关键词：

Congestion management; Energy storage system; Energy storage planning; Uncertainty management; Renewable energy; DEMAND RESPONSE; WIND FARMS; GENERATION; INTEGRATION; GRIDS;

D O I：

10.1016/j.energy.2017.05.167

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

This paper presents an optimal planning and scheduling on energy storage systems (ESSs) for congestion management in electric power systems including renewable energy resources. The proposed problem finds optimal capacity and charging-discharging regime of ESSs. The storage units are optimally charged and discharged to tackle the uncertainty related to wind-solar units as well as relief congestion in the lines. Output power of solar and wind units is modeled by Gaussian probability distribution function (PDF) and Monte-Carlo simulation (MCS) is applied to tackle the uncertainty. Simulation results demonstrate that the proposed planning can manage congestion of the network efficiently while dealing with wind and solar resources uncertainties. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：380 / 387

页数：8

共 35 条

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