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Energy and reserve management of a smart distribution system by incorporating responsive-loads /battery/wind turbines considering uncertain parameters

机译:通过考虑不确定参数的响应负载/电池/风力涡轮机,对智能配电系统的能量和储备进行管理

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摘要

Uncertainties of load demand and power output of renewable-based energy sources as well as participation of responsive loads in energy supply can be identified as the main issues of the future power networks. Accordingly, it is essential to develop practical approaches for dealing with the uncertainties of wind power and load in optimal scheduling of such systems. This paper proposes a new uncertainty-modeling approach based on Hong's two-point estimate method (T-PEM) for optimal day-ahead scheduling (ODAS) of a smart distribution system (SDS). The proposed method seeks to minimize the functional cost of energy and reserve requirements of SDS in the presence of wind turbines, diesel generators and battery energy storage system considering uncertainties of wind production and load demand. Also, according to importance of enabling consumers to contribute in energy and reserve supply of SDSs, the present work studies the implementation of two various demand response (DR) programs in energy and reserve management of a SDS. The proposed method is applied on IEEE 33-bus distribution test system to investigate the efficiency and performance of the proposed model, which confirms the validity and practicality of the presented model. (C) 2019 Elsevier Ltd. All rights reserved.
机译:负载需求和可再生能源的输出功率的不确定性以及响应性负载参与能源供应的不确定性可以确定为未来电网的主要问题。因此,在这种系统的最佳调度中,开发用于应对风力和负荷的不确定性的实用方法至关重要。本文提出了一种基于洪氏两点估计方法(T-PEM)的不确定性建模方法,用于智能配电系统(SDS)的最佳提前​​日调度(ODAS)。考虑到风力发电和负荷需求的不确定性,所提出的方法旨在在存在风力涡轮机,柴油发电机和电池储能系统的情况下,最大限度地降低SDS的能源功能成本和储备需求。另外,根据使消费者能够为SDS的能源和储备供应做出贡献的重要性,本工作研究了在SDS的能源和储备管理中两种不同的需求响应(DR)计划的实施。将该方法应用于IEEE 33总线配电测试系统,研究了该模型的效率和性能,证实了该模型的有效性和实用性。 (C)2019 Elsevier Ltd.保留所有权利。

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