论文标题
使用复杂的网络理论评估具有分布式能源的电气分配系统的计划和运营弹性
Evaluating the Planning and Operational Resilience of Electrical Distribution Systems with Distributed Energy Resources using Complex Network Theory
论文作者
论文摘要
电源分配系统被分布式能源(DER)广泛渗透,以满足能量需求,以一种普遍的看法,即它增强了系统的弹性。但是,DER的集成可能会对网格操作产生不利影响并影响系统的弹性,这是由于其间歇性可用性,天气状况的动态,非线性,复杂性,恶意威胁的数量以及改善消费者的可靠性要求。本文提出了一种方法,以评估极端事件下电源分配系统的计划和操作弹性,并确定电网的承受能力。提出的框架是通过有效地采用复杂网络理论来开发的。不良配置的相关网络是根据电动网络节点上监视的主动功率的时间序列数据开发的。对于这些相关的网络,计算了网络参数,例如聚类系数,分类系数,平均程度和功率定律指数,以期预期;在极端条件下,确定网络可承受能力的渗透阈值。所提出的方法还适用于确定系统中太阳能电池板的托管能力,同时在不同的不利条件下保持弹性,并确定系统的最关键节点,这些节点可能会使系统进入非弹力。通过使用仿真软件GridLab-D生成主动的电力时间序列数据,在IEEE 123节点测试馈线上证明了该框架。渗透阈值是确定功率分配系统计划和运营弹性的有效指标。
Electrical Distribution Systems are extensively penetrated with Distributed Energy Resources (DERs) to cater the energy demands with the general perception that it enhances the system's resilience. However, integration of DERs may adversely affect the grid operation and affect the system resilience due to various factors like their intermittent availability, dynamics of weather conditions, non-linearity, complexity, number of malicious threats, and improved reliability requirements of consumers. This paper proposes a methodology to evaluate the planning and operational resilience of power distribution systems under extreme events and determines the withstand capability of the electrical network. The proposed framework is developed by effectively employing the complex network theory. Correlated networks for undesirable configurations are developed from the time series data of active power monitored at nodes of the electrical network. For these correlated networks, computed the network parameters such as clustering coefficient, assortative coefficient, average degree and power law exponent for the anticipation; and percolation threshold for the determination of the network withstand capability under extreme conditions. The proposed methodology is also suitable for identifying the hosting capacity of solar panels in the system while maintaining resilience under different unfavourable conditions and identifying the most critical nodes of the system that could drive the system into non-resilience. This framework is demonstrated on IEEE 123 node test feeder by generating active power time-series data for a variety of electrical conditions using simulation software, GridLAB-D. The percolation threshold resulted as an effective metric for the determination of the planning and operational resilience of the power distribution system.