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Short-term scheduling problem in smart grid considering reliability improvement in bad weather conditions

机译:考虑恶劣天气条件下可靠性提高的智能电网短期调度问题

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摘要

The worldwide needs to increase the reliability of the electrical grids and to reduce energy not supplied (ENS) are the major goals in traditional grids. Smart grids have key features such as intelligence, adaption and flexibility abilities, to reduce the effects of outages in society. This study proposes an optimised operational strategy which increases the robustness of smart grid against outages caused by bad weather conditions. The proposed method takes advantage of dynamic economic dispatch and hourly forecasted weather information. Intelligent scheduling of demand response programs and energy storage system, are formulated as a multi-objective optimisation problem considering consumer interruption costs. In this study, the objective functions consist of benefit maximisation of the distribution companies, benefit of the distributed generation and energy storage owners (DGO). In the proposed approach, line interruption rates are affected by weather conditions and consequently the ENS cost will be influenced in each time interval. DisCohas the ability to modify energy cost to overcome bad weather conditions and reduce ENS in different time periods. Simulation results show that the presented method reduces the real operation and ENS cost for DisCo. In addition, DisCo increases the benefits of DGO.
机译:全球范围内需要提高电网的可靠性并减少不提供能源(ENS)是传统电网的主要目标。智能电网具有关键功能,例如智能,适应性和灵活性,以减少停电对社会的影响。这项研究提出了一种优化的运行策略,可以提高智能电网抵御恶劣天气条件导致的停电的稳健性。该方法利用了动态经济调度和每小时天气预报信息的优势。考虑消费者中断成本,需求响应程序和能量存储系统的智能调度被表述为多目标优化问题。在这项研究中,目标功能包括分销公司的利益最大化,分布式发电和储能所有者(DGO)的利益。在提出的方法中,线路中断率受天气条件的影响,因此,ENS成本将在每个时间间隔内受到影响。 DisCo具有修改能源成本以克服恶劣天气条件并减少不同时间段ENS的能力。仿真结果表明,该方法降低了DisCo的实际运行量和ENS成本。此外,DisCo还增加了DGO的优势。

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